WorldWideScience

Sample records for delay optimal scheduling

  1. Cascading Delay Risk of Airline Workforce Deployments with Crew Pairing and Schedule Optimization.

    Science.gov (United States)

    Chung, Sai Ho; Ma, Hoi Lam; Chan, Hing Kai

    2017-08-01

    This article concerns the assignment of buffer time between two connected flights and the number of reserve crews in crew pairing to mitigate flight disruption due to flight arrival delay. Insufficient crew members for a flight will lead to flight disruptions such as delays or cancellations. In reality, most of these disruption cases are due to arrival delays of the previous flights. To tackle this problem, many research studies have examined the assignment method based on the historical flight arrival delay data of the concerned flights. However, flight arrival delays can be triggered by numerous factors. Accordingly, this article proposes a new forecasting approach using a cascade neural network, which considers a massive amount of historical flight arrival and departure data. The approach also incorporates learning ability so that unknown relationships behind the data can be revealed. Based on the expected flight arrival delay, the buffer time can be determined and a new dynamic reserve crew strategy can then be used to determine the required number of reserve crews. Numerical experiments are carried out based on one year of flight data obtained from 112 airports around the world. The results demonstrate that by predicting the flight departure delay as the input for the prediction of the flight arrival delay, the prediction accuracy can be increased. Moreover, by using the new dynamic reserve crew strategy, the total crew cost can be reduced. This significantly benefits airlines in flight schedule stability and cost saving in the current big data era. © 2016 Society for Risk Analysis.

  2. Rate-Optimal Multiuser Scheduling with Reduced Feedback Load and Analysis of Delay Effects

    Directory of Open Access Journals (Sweden)

    Alouini Mohamed-Slim

    2006-01-01

    Full Text Available We propose a feedback algorithm for wireless networks that always collects feedback from the user with the best channel conditions and has a significant reduction in feedback load compared to full feedback. The algorithm is based on a carrier-to-noise threshold, and closed-form expressions for the feedback load as well as the threshold value that minimizes the feedback load have been found. We analyze two delay scenarios. The first scenario is where the scheduling decision is based on outdated channel estimates, and the second scenario is where both the scheduling decision and the adaptive modulation are based on outdated channel estimates.

  3. A Flexible Job Shop Scheduling Problem with Controllable Processing Times to Optimize Total Cost of Delay and Processing

    Directory of Open Access Journals (Sweden)

    Hadi Mokhtari

    2015-11-01

    Full Text Available In this paper, the flexible job shop scheduling problem with machine flexibility and controllable process times is studied. The main idea is that the processing times of operations may be controlled by consumptions of additional resources. The purpose of this paper to find the best trade-off between processing cost and delay cost in order to minimize the total costs. The proposed model, flexible job shop scheduling with controllable processing times (FJCPT, is formulated as an integer non-linear programming (INLP model and then it is converted into an integer linear programming (ILP model. Due to NP-hardness of FJCPT, conventional analytic optimization methods are not efficient. Hence, in order to solve the problem, a Scatter Search (SS, as an efficient metaheuristic method, is developed. To show the effectiveness of the proposed method, numerical experiments are conducted. The efficiency of the proposed algorithm is compared with that of a genetic algorithm (GA available in the literature for solving FJSP problem. The results showed that the proposed SS provide better solutions than the existing GA.

  4. Schedule Matters: Understanding the Relationship between Schedule Delays and Costs on Overruns

    Science.gov (United States)

    Majerowicz, Walt; Shinn, Stephen A.

    2016-01-01

    This paper examines the relationship between schedule delays and cost overruns on complex projects. It is generally accepted by many project practitioners that cost overruns are directly related to schedule delays. But what does "directly related to" actually mean? Some reasons or root causes for schedule delays and associated cost overruns are obvious, if only in hindsight. For example, unrealistic estimates, supply chain difficulties, insufficient schedule margin, technical problems, scope changes, or the occurrence of risk events can negatively impact schedule performance. Other factors driving schedule delays and cost overruns may be less obvious and more difficult to quantify. Examples of these less obvious factors include project complexity, flawed estimating assumptions, over-optimism, political factors, "black swan" events, or even poor leadership and communication. Indeed, is it even possible the schedule itself could be a source of delay and subsequent cost overrun? Through literature review, surveys of project practitioners, and the authors' own experience on NASA programs and projects, the authors will categorize and examine the various factors affecting the relationship between project schedule delays and cost growth. The authors will also propose some ideas for organizations to consider to help create an awareness of the factors which could cause or influence schedule delays and associated cost growth on complex projects.

  5. Transmission Scheduling and Routing Algorithms for Delay Tolerant Networks

    Science.gov (United States)

    Dudukovich, Rachel; Raible, Daniel E.

    2016-01-01

    The challenges of data processing, transmission scheduling and routing within a space network present a multi-criteria optimization problem. Long delays, intermittent connectivity, asymmetric data rates and potentially high error rates make traditional networking approaches unsuitable. The delay tolerant networking architecture and protocols attempt to mitigate many of these issues, yet transmission scheduling is largely manually configured and routes are determined by a static contact routing graph. A high level of variability exists among the requirements and environmental characteristics of different missions, some of which may allow for the use of more opportunistic routing methods. In all cases, resource allocation and constraints must be balanced with the optimization of data throughput and quality of service. Much work has been done researching routing techniques for terrestrial-based challenged networks in an attempt to optimize contact opportunities and resource usage. This paper examines several popular methods to determine their potential applicability to space networks.

  6. Optimal randomized scheduling by replacement

    Energy Technology Data Exchange (ETDEWEB)

    Saias, I.

    1996-05-01

    In the replacement scheduling problem, a system is composed of n processors drawn from a pool of p. The processors can become faulty while in operation and faulty processors never recover. A report is issued whenever a fault occurs. This report states only the existence of a fault but does not indicate its location. Based on this report, the scheduler can reconfigure the system and choose another set of n processors. The system operates satisfactorily as long as, upon report of a fault, the scheduler chooses n non-faulty processors. We provide a randomized protocol maximizing the expected number of faults the system can sustain before the occurrence of a crash. The optimality of the protocol is established by considering a closely related dual optimization problem. The game-theoretic technical difficulties that we solve in this paper are very general and encountered whenever proving the optimality of a randomized algorithm in parallel and distributed computation.

  7. A Novel Message Scheduling Framework for Delay Tolerant Networks Routing

    KAUST Repository

    Elwhishi, Ahmed

    2013-05-01

    Multicopy routing strategies have been considered the most applicable approaches to achieve message delivery in Delay Tolerant Networks (DTNs). Epidemic routing and two-hop forwarding routing are two well-reported approaches for delay tolerant networks routing which allow multiple message replicas to be launched in order to increase message delivery ratio and/or reduce message delivery delay. This advantage, nonetheless, is at the expense of additional buffer space and bandwidth overhead. Thus, to achieve efficient utilization of network resources, it is important to come up with an effective message scheduling strategy to determine which messages should be forwarded and which should be dropped in case of buffer is full. This paper investigates a new message scheduling framework for epidemic and two-hop forwarding routing in DTNs, such that the forwarding/dropping decision can be made at a node during each contact for either optimal message delivery ratio or message delivery delay. Extensive simulation results show that the proposed message scheduling framework can achieve better performance than its counterparts.

  8. Online Scheduling in Manufacturing A Cumulative Delay Approach

    CERN Document Server

    Suwa, Haruhiko

    2013-01-01

    Online scheduling is recognized as the crucial decision-making process of production control at a phase of “being in production" according to the released shop floor schedule. Online scheduling can be also considered as one of key enablers to realize prompt capable-to-promise as well as available-to-promise to customers along with reducing production lead times under recent globalized competitive markets. Online Scheduling in Manufacturing introduces new approaches to online scheduling based on a concept of cumulative delay. The cumulative delay is regarded as consolidated information of uncertainties under a dynamic environment in manufacturing and can be collected constantly without much effort at any points in time during a schedule execution. In this approach, the cumulative delay of the schedule has the important role of a criterion for making a decision whether or not a schedule revision is carried out. The cumulative delay approach to trigger schedule revisions has the following capabilities for the ...

  9. Scheduling with Bus Access Optimization for Distributed Embedded Systems

    DEFF Research Database (Denmark)

    Eles, Petru; Doboli, Alex; Pop, Paul

    2000-01-01

    In this paper, we concentrate on aspects related to the synthesis of distributed embedded systems consisting of programmable processors and application-specific hardware components. The approach is based on an abstract graph representation that captures, at process level, both dataflow and the flow...... of control. Our goal is to derive a worst case delay by which the system completes execution, such that this delay is as small as possible; to generate a logically and temporally deterministic schedule; and to optimize parameters of the communication protocol such that this delay is guaranteed. We have...... have to be considered during scheduling but also the parameters of the communication protocol should be adapted to fit the particular embedded application. The optimization algorithm, which implies both process scheduling and optimization of the parameters related to the communication protocol...

  10. Schedule optimization study implementation plan

    International Nuclear Information System (INIS)

    1993-11-01

    This Implementation Plan is intended to provide a basis for improvements in the conduct of the Environmental Restoration (ER) Program at Hanford. The Plan is based on the findings of the Schedule Optimization Study (SOS) team which was convened for two weeks in September 1992 at the request of the U.S. Department of Energy (DOE) Richland Operations Office (RL). The need for the study arose out of a schedule dispute regarding the submission of the 1100-EM-1 Operable Unit (OU) Remedial Investigation/Feasibility Study (RI/FS) Work Plan. The SOS team was comprised of independent professionals from other federal agencies and the private sector experienced in environmental restoration within the federal system. The objective of the team was to examine reasons for the lengthy RI/FS process and recommend ways to expedite it. The SOS team issued their Final Report in December 1992. The report found the most serious impediments to cleanup relate to a series of management and policy issues which are within the control of the three parties managing and monitoring Hanford -- the DOE, U.S. Environmental Protection Agency (EPA), and the State of Washington Department of Ecology (Ecology). The SOS Report identified the following eight cross-cutting issues as the root of major impediments to the Hanford Site cleanup. Each of these eight issues is quoted from the SOS Report followed by a brief, general description of the proposed approach being developed

  11. Schedule optimization study implementation plan

    Energy Technology Data Exchange (ETDEWEB)

    1993-11-01

    This Implementation Plan is intended to provide a basis for improvements in the conduct of the Environmental Restoration (ER) Program at Hanford. The Plan is based on the findings of the Schedule Optimization Study (SOS) team which was convened for two weeks in September 1992 at the request of the U.S. Department of Energy (DOE) Richland Operations Office (RL). The need for the study arose out of a schedule dispute regarding the submission of the 1100-EM-1 Operable Unit (OU) Remedial Investigation/Feasibility Study (RI/FS) Work Plan. The SOS team was comprised of independent professionals from other federal agencies and the private sector experienced in environmental restoration within the federal system. The objective of the team was to examine reasons for the lengthy RI/FS process and recommend ways to expedite it. The SOS team issued their Final Report in December 1992. The report found the most serious impediments to cleanup relate to a series of management and policy issues which are within the control of the three parties managing and monitoring Hanford -- the DOE, U.S. Environmental Protection Agency (EPA), and the State of Washington Department of Ecology (Ecology). The SOS Report identified the following eight cross-cutting issues as the root of major impediments to the Hanford Site cleanup. Each of these eight issues is quoted from the SOS Report followed by a brief, general description of the proposed approach being developed.

  12. Optimization of Hierarchically Scheduled Heterogeneous Embedded Systems

    DEFF Research Database (Denmark)

    Pop, Traian; Pop, Paul; Eles, Petru

    2005-01-01

    We present an approach to the analysis and optimization of heterogeneous distributed embedded systems. The systems are heterogeneous not only in terms of hardware components, but also in terms of communication protocols and scheduling policies. When several scheduling policies share a resource......, they are organized in a hierarchy. In this paper, we address design problems that are characteristic to such hierarchically scheduled systems: assignment of scheduling policies to tasks, mapping of tasks to hardware components, and the scheduling of the activities. We present algorithms for solving these problems....... Our heuristics are able to find schedulable implementations under limited resources, achieving an efficient utilization of the system. The developed algorithms are evaluated using extensive experiments and a real-life example....

  13. An introduction to optimal satellite range scheduling

    CERN Document Server

    Vázquez Álvarez, Antonio José

    2015-01-01

    The satellite range scheduling (SRS) problem, an important operations research problem in the aerospace industry consisting of allocating tasks among satellites and Earth-bound objects, is examined in this book. SRS principles and solutions are applicable to many areas, including: Satellite communications, where tasks are communication intervals between sets of satellites and ground stations Earth observation, where tasks are observations of spots on the Earth by satellites Sensor scheduling, where tasks are observations of satellites by sensors on the Earth. This self-contained monograph begins with a structured compendium of the problem and moves on to explain the optimal approach to the solution, which includes aspects from graph theory, set theory, game theory and belief networks. This book is accessible to students, professionals and researchers in a variety of fields, including: operations research, optimization, scheduling theory, dynamic programming and game theory. Taking account of the distributed, ...

  14. Anesthesiology Nurse Scheduling using Particle Swarm Optimization

    Directory of Open Access Journals (Sweden)

    Leopoldo Altamirano

    2012-02-01

    Full Text Available In this article we present an approach designed to solve a real world problem: the Anesthesiology Nurse Scheduling Problem (ANSP at a public French hospital. The anesthesiology nurses are one of the most shared resources in the hospital and we attempt to find a fair/balanced schedule for them, taking into account a set of constraints and the nursesarsquo; stated preferences, concerning the different shifts. We propose a particle swarm optimization algorithm to solve the ANSP. Finally, we compare our technique with previous results obtained using integer programming.

  15. Group Elevator Peak Scheduling Based on Robust Optimization Model

    OpenAIRE

    ZHANG, J.; ZONG, Q.

    2013-01-01

    Scheduling of Elevator Group Control System (EGCS) is a typical combinatorial optimization problem. Uncertain group scheduling under peak traffic flows has become a research focus and difficulty recently. RO (Robust Optimization) method is a novel and effective way to deal with uncertain scheduling problem. In this paper, a peak scheduling method based on RO model for multi-elevator system is proposed. The method is immune to the uncertainty of peak traffic flows, optimal scheduling is re...

  16. Terminal Control Area Aircraft Scheduling and Trajectory Optimization Approaches

    Directory of Open Access Journals (Sweden)

    Samà Marcella

    2017-01-01

    Full Text Available Aviation authorities are seeking optimization methods to better use the available infrastructure and better manage aircraft movements. This paper deals with the realtime scheduling of take-off and landing aircraft at a busy terminal control area and with the optimization of aircraft trajectories during the landing procedures. The first problem aims to reduce the propagation of delays, while the second problem aims to either minimize the travel time or reduce the fuel consumption. Both problems are particularly complex, since the first one is NP-hard while the second one is nonlinear and a combined solution needs to be computed in a short-time during operations. This paper proposes a framework for the lexicographic optimization of the two problems. Computational experiments are performed for the Milano Malpensa airport and show the existing gaps between the performance indicators of the two problems when different lexicographic optimization approaches are considered.

  17. Scheduling Production Orders, Taking into Account Delays and Waste

    Directory of Open Access Journals (Sweden)

    Dylewski Robert

    2014-09-01

    Full Text Available The article addresses the problem of determining the sequence of entering orders for production in a flexible manufacturing system implementing technological operations of cutting sheet metal. Adopting a specific ranking of production orders gives rise to the vector of delays and waste in the form of incompletely used sheets. A new method was postulated for determining the optimal sequence of orders in terms of two criteria: the total cost of delays and the amount of production waste. The examples illustrate the advantages of the proposed method compared with the popular heuristic principles.

  18. TTSA: An Effective Scheduling Approach for Delay Bounded Tasks in Hybrid Clouds.

    Science.gov (United States)

    Yuan, Haitao; Bi, Jing; Tan, Wei; Zhou, MengChu; Li, Bo Hu; Li, Jianqiang

    2017-11-01

    The economy of scale provided by cloud attracts a growing number of organizations and industrial companies to deploy their applications in cloud data centers (CDCs) and to provide services to users around the world. The uncertainty of arriving tasks makes it a big challenge for private CDC to cost-effectively schedule delay bounded tasks without exceeding their delay bounds. Unlike previous studies, this paper takes into account the cost minimization problem for private CDC in hybrid clouds, where the energy price of private CDC and execution price of public clouds both show the temporal diversity. Then, this paper proposes a temporal task scheduling algorithm (TTSA) to effectively dispatch all arriving tasks to private CDC and public clouds. In each iteration of TTSA, the cost minimization problem is modeled as a mixed integer linear program and solved by a hybrid simulated-annealing particle-swarm-optimization. The experimental results demonstrate that compared with the existing methods, the optimal or suboptimal scheduling strategy produced by TTSA can efficiently increase the throughput and reduce the cost of private CDC while meeting the delay bounds of all the tasks.

  19. Optimal pre-scheduling of problem remappings

    Science.gov (United States)

    Nicol, David M.; Saltz, Joel H.

    1987-01-01

    A large class of scientific computational problems can be characterized as a sequence of steps where a significant amount of computation occurs each step, but the work performed at each step is not necessarily identical. Two good examples of this type of computation are: (1) regridding methods which change the problem discretization during the course of the computation, and (2) methods for solving sparse triangular systems of linear equations. Recent work has investigated a means of mapping such computations onto parallel processors; the method defines a family of static mappings with differing degrees of importance placed on the conflicting goals of good load balance and low communication/synchronization overhead. The performance tradeoffs are controllable by adjusting the parameters of the mapping method. To achieve good performance it may be necessary to dynamically change these parameters at run-time, but such changes can impose additional costs. If the computation's behavior can be determined prior to its execution, it can be possible to construct an optimal parameter schedule using a low-order-polynomial-time dynamic programming algorithm. Since the latter can be expensive, the performance is studied of the effect of a linear-time scheduling heuristic on one of the model problems, and it is shown to be effective and nearly optimal.

  20. A Method for Determining Schedule Delay Information in a Channel Cargo Route Network Schedule

    Science.gov (United States)

    1992-06-01

    customer satisfaction. 2-1 Historically, ichiedulers repeatedly performed this important, difficult, and of- ten time-consuming, mnental and manual task...delay caused through flight scheduling, the focus must now address mneasurement of performance with respect to timeliness (or customer satisfaction). As...whIacich results ariet th smobtaione(i.. ()i t( more i3TAýTS affect cSat - tso ago eniis ro o I letireigint hion Jou irneys a reor lie a ppt oa thle in lorrn

  1. Efficient Scheduling of Pigeons for a Constrained Delay Tolerant Application

    Directory of Open Access Journals (Sweden)

    Legand Burge

    2010-01-01

    Full Text Available Information collection in the disaster area is an important application of pigeon networks—a special type of delay tolerant networks (DTNs that borrows the ancient idea of using pigeons as the telecommunication method. The aim of this paper is to explore highly efficient scheduling strategies of pigeons for such applications. The upper bound of traffic that can be supported under the deadline constraints for the basic on-demand strategy is given through the analysis. Based on the analysis, a waiting-based packing strategy is introduced. Although the latter strategy could not change the maximum traffic rate that a pigeon can support, it improves the efficiency of a pigeon largely. The analytical results are verified by the simulations.

  2. Group Elevator Peak Scheduling Based on Robust Optimization Model

    Directory of Open Access Journals (Sweden)

    ZHANG, J.

    2013-08-01

    Full Text Available Scheduling of Elevator Group Control System (EGCS is a typical combinatorial optimization problem. Uncertain group scheduling under peak traffic flows has become a research focus and difficulty recently. RO (Robust Optimization method is a novel and effective way to deal with uncertain scheduling problem. In this paper, a peak scheduling method based on RO model for multi-elevator system is proposed. The method is immune to the uncertainty of peak traffic flows, optimal scheduling is realized without getting exact numbers of each calling floor's waiting passengers. Specifically, energy-saving oriented multi-objective scheduling price is proposed, RO uncertain peak scheduling model is built to minimize the price. Because RO uncertain model could not be solved directly, RO uncertain model is transformed to RO certain model by elevator scheduling robust counterparts. Because solution space of elevator scheduling is enormous, to solve RO certain model in short time, ant colony solving algorithm for elevator scheduling is proposed. Based on the algorithm, optimal scheduling solutions are found quickly, and group elevators are scheduled according to the solutions. Simulation results show the method could improve scheduling performances effectively in peak pattern. Group elevators' efficient operation is realized by the RO scheduling method.

  3. Application of genetic algorithm for hemodialysis schedule optimization.

    Science.gov (United States)

    Choi, Jin Woo; Lee, Hajeong; Lee, Jung Chan; Lee, Saram; Kim, Yon Su; Yoon, Hyung-Jin; Kim, Hee Chan

    2017-07-01

    The conventional hemodialysis (HD) schedule has been used for decades, even though new modalities have been introduced. Many reasons limit practices of frequent dialysis, such as patients' environments and unknown optimal schedules for each patient. This research provides a theoretical recommendation of HD schedule through genetic algorithm (GA). An end-stage renal disease (ESRD) with various dialysis conditions was modeled through a classic variable-volume two-compartment kinetic model to simulate an anuric patient, and GA was implemented to search for an optimal HD schedule for each individual considering and ignoring burden consumption of each dialysis session. The adequacy of the optimized HD schedules through GA was assessed with time average concentration (TAC) and time average deviation (TAD). While ignoring the burden of dialysis sessions, GA returned schedules with slightly improved values of adequacy criteria (EKRc and std Kt/V), compared to the conventional regular uniform HD schedules. The optimized HD schedules also showed decreased TAC and TAD values compared to the conventional regular uniform HD schedules. It showed that frequent dialysis resulted in more effective treatment and higher fitness values. However, when burden was considered, less frequent dialysis schedules showed better fitness value. Through this research, GA confirmed that at least 12h of dialysis should be conducted for a week. The optimized schedules from GA indicated that evenly distributing the intervals amongst sessions is efficient, and that scheduling a session at the start and end of a week is optimal to overcome a long weekend interval. The theoretical optimal schedule of HD may help distribution of frequent dialysis and provide more schedule options to patients. Copyright © 2017 Elsevier B.V. All rights reserved.

  4. Optimal Control with Time Delays via the Penalty Method

    Directory of Open Access Journals (Sweden)

    Mohammed Benharrat

    2014-01-01

    Full Text Available We prove necessary optimality conditions of Euler-Lagrange type for a problem of the calculus of variations with time delays, where the delay in the unknown function is different from the delay in its derivative. Then, a more general optimal control problem with time delays is considered. Main result gives a convergence theorem, allowing us to obtain a solution to the delayed optimal control problem by considering a sequence of delayed problems of the calculus of variations.

  5. Bus Access Optimization for Distributed Embedded Systems Based on Schedulability Analysis

    DEFF Research Database (Denmark)

    Pop, Paul; Eles, Petru; Peng, Zebo

    2000-01-01

    We present an approach to bus access optimization and schedulability analysis for the synthesis of hard real-time distribution embedded systems. The communication model is based on a time-triggered protocol. We have developed an analysis for the communication delays proposing four different message...

  6. WE-D-BRE-04: Modeling Optimal Concurrent Chemotherapy Schedules

    International Nuclear Information System (INIS)

    Jeong, J; Deasy, J O

    2014-01-01

    Purpose: Concurrent chemo-radiation therapy (CCRT) has become a more common cancer treatment option with a better tumor control rate for several tumor sites, including head and neck and lung cancer. In this work, possible optimal chemotherapy schedules were investigated by implementing chemotherapy cell-kill into a tumor response model of RT. Methods: The chemotherapy effect has been added into a published model (Jeong et al., PMB (2013) 58:4897), in which the tumor response to RT can be simulated with the effects of hypoxia and proliferation. Based on the two-compartment pharmacokinetic model, the temporal concentration of chemotherapy agent was estimated. Log cell-kill was assumed and the cell-kill constant was estimated from the observed increase in local control due to concurrent chemotherapy. For a simplified two cycle CCRT regime, several different starting times and intervals were simulated with conventional RT regime (2Gy/fx, 5fx/wk). The effectiveness of CCRT was evaluated in terms of reduction in radiation dose required for 50% of control to find the optimal chemotherapy schedule. Results: Assuming the typical slope of dose response curve (γ50=2), the observed 10% increase in local control rate was evaluated to be equivalent to an extra RT dose of about 4 Gy, from which the cell-kill rate of chemotherapy was derived to be about 0.35. Best response was obtained when chemotherapy was started at about 3 weeks after RT began. As the interval between two cycles decreases, the efficacy of chemotherapy increases with broader range of optimal starting times. Conclusion: The effect of chemotherapy has been implemented into the resource-conservation tumor response model to investigate CCRT. The results suggest that the concurrent chemotherapy might be more effective when delayed for about 3 weeks, due to lower tumor burden and a larger fraction of proliferating cells after reoxygenation

  7. Preliminary Evaluation of BIM-based Approaches for Schedule Delay Analysis

    Science.gov (United States)

    Chou, Hui-Yu; Yang, Jyh-Bin

    2017-10-01

    The problem of schedule delay commonly occurs in construction projects. The quality of delay analysis depends on the availability of schedule-related information and delay evidence. More information used in delay analysis usually produces more accurate and fair analytical results. How to use innovative techniques to improve the quality of schedule delay analysis results have received much attention recently. As Building Information Modeling (BIM) technique has been quickly developed, using BIM and 4D simulation techniques have been proposed and implemented. Obvious benefits have been achieved especially in identifying and solving construction consequence problems in advance of construction. This study preforms an intensive literature review to discuss the problems encountered in schedule delay analysis and the possibility of using BIM as a tool in developing a BIM-based approach for schedule delay analysis. This study believes that most of the identified problems can be dealt with by BIM technique. Research results could be a fundamental of developing new approaches for resolving schedule delay disputes.

  8. Optimal investment and scheduling of distributed energy resources with uncertainty in electric vehicles driving schedules

    Energy Technology Data Exchange (ETDEWEB)

    Cardoso, Goncalo [Technical Univ. of Lisbon (Portugal); Stadler, Michael [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Center for Energy and Innovation Technologies (Austria); Bozchalui, Mohammed C. [NEC Laboratories American Inc., Irving, TX (United States); Sharma, Ratnesh [NEC Laboratories American Inc., Irving, TX (United States); Marnay, Chris [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Barbosa-Povoa, Ana [Technical Univ. of Lisbon (Portugal); Ferrao, Paulo [Technical Univ. of Lisbon (Portugal)

    2013-12-06

    The large scale penetration of electric vehicles (EVs) will introduce technical challenges to the distribution grid, but also carries the potential for vehicle-to-grid services. Namely, if available in large enough numbers, EVs can be used as a distributed energy resource (DER) and their presence can influence optimal DER investment and scheduling decisions in microgrids. In this work, a novel EV fleet aggregator model is introduced in a stochastic formulation of DER-CAM [1], an optimization tool used to address DER investment and scheduling problems. This is used to assess the impact of EV interconnections on optimal DER solutions considering uncertainty in EV driving schedules. Optimization results indicate that EVs can have a significant impact on DER investments, particularly if considering short payback periods. Furthermore, results suggest that uncertainty in driving schedules carries little significance to total energy costs, which is corroborated by results obtained using the stochastic formulation of the problem.

  9. Optimal Grid Scheduling Using Improved Artificial Bee Colony Algorithm

    OpenAIRE

    T. Vigneswari; M. A. Maluk Mohamed

    2015-01-01

    Job Scheduling plays an important role for efficient utilization of grid resources available across different domains and geographical zones. Scheduling of jobs is challenging and NPcomplete. Evolutionary / Swarm Intelligence algorithms have been extensively used to address the NP problem in grid scheduling. Artificial Bee Colony (ABC) has been proposed for optimization problems based on foraging behaviour of bees. This work proposes a modified ABC algorithm, Cluster Hete...

  10. Locomotive Schedule Optimization for Da-qin Heavy Haul Railway

    OpenAIRE

    Su, Ruiye; Zhou, Leishan; Tang, Jinjin

    2015-01-01

    The main difference between locomotive schedule of heavy haul railways and that of regular rail transportation is the number of locomotives utilized for one train. One heavy-loaded train usually has more than one locomotive, but a regular train only has one. This paper develops an optimization model for the multilocomotive scheduling problem (MLSP) through analyzing the current locomotive schedule of Da-qin Railway. The objective function of our paper is to minimize the total number of utiliz...

  11. Developing optimal nurses work schedule using integer programming

    Science.gov (United States)

    Shahidin, Ainon Mardhiyah; Said, Mohd Syazwan Md; Said, Noor Hizwan Mohamad; Sazali, Noor Izatie Amaliena

    2017-08-01

    Time management is the art of arranging, organizing and scheduling one's time for the purpose of generating more effective work and productivity. Scheduling is the process of deciding how to commit resources between varieties of possible tasks. Thus, it is crucial for every organization to have a good work schedule for their staffs. The job of Ward nurses at hospitals runs for 24 hours every day. Therefore, nurses will be working using shift scheduling. This study is aimed to solve the nurse scheduling problem at an emergency ward of a private hospital. A 7-day work schedule for 7 consecutive weeks satisfying all the constraints set by the hospital will be developed using Integer Programming. The work schedule for the nurses obtained gives an optimal solution where all the constraints are being satisfied successfully.

  12. customer-teller scheduling system for optimizing banks service

    African Journals Online (AJOL)

    els Bank Teller scheduling system for optimizing a Banks customer service. The model takes into account real time system ... Keywords: scheduler, service optimisation, queuing theory, simulation, customer satisfaction, integer programming ...... build up the customer loyalty, who will return for similar business in the future.

  13. Software Project Scheduling Management by Particle Swarm Optimization

    Directory of Open Access Journals (Sweden)

    Dinesh B. Hanchate

    2014-12-01

    Full Text Available PSO (Particle Swarm Optimization is, like GA, a heuristic global optimization method based on swarm intelligence. In this paper, we present a particle swarm optimization algorithm to solve software project scheduling problem. PSO itself inherits very efficient local search method to find the near optimal and best-known solutions for all instances given as inputs required for SPSM (Software Project Scheduling Management. At last, this paper imparts PSO and research situation with SPSM. The effect of PSO parameter on project cost and time is studied and some better results in terms of minimum SCE (Software Cost Estimation and time as compared to GA and ACO are obtained.

  14. Locomotive Schedule Optimization for Da-qin Heavy Haul Railway

    Directory of Open Access Journals (Sweden)

    Ruiye Su

    2015-01-01

    Full Text Available The main difference between locomotive schedule of heavy haul railways and that of regular rail transportation is the number of locomotives utilized for one train. One heavy-loaded train usually has more than one locomotive, but a regular train only has one. This paper develops an optimization model for the multilocomotive scheduling problem (MLSP through analyzing the current locomotive schedule of Da-qin Railway. The objective function of our paper is to minimize the total number of utilized locomotives. The MLSP is nondeterministic polynomial (NP hard. Therefore, we convert the multilocomotive traction problem into a single-locomotive traction problem. Then, the single-locomotive traction problem (SLTP can be converted into an assignment problem. The Hungarian algorithm is applied to solve the model and obtain the optimal locomotive schedule. We use the variance of detention time of locomotives at stations to evaluate the stability of locomotive schedule. In order to evaluate the effectiveness of the proposed optimization model, case studies for 20 kt and 30 kt heavy-loaded combined trains on Da-qin Railway are both conducted. Compared to the current schedules, the optimal schedules from the proposed models can save 62 and 47 locomotives for 20 kt and 30 kt heavy-loaded combined trains, respectively. Therefore, the effectiveness of the proposed model and its solution algorithm are both valid.

  15. Transitional and Steady-State Choice Behavior under an Adjusting-Delay Schedule

    Science.gov (United States)

    Torres, L. Valencia; Araujo, S. da Costa; Sanchez, C. M. Olarte; Body, S.; Bradshaw, C. M.; Szabadi, E.

    2011-01-01

    Twelve rats made repeated choices on an adjusting-delay schedule between a smaller reinforcer (A) that was delivered immediately after a response and a larger reinforcer (B) that was delivered after a delay which increased or decreased by 20% depending on the subject's choices in successive blocks of trials. In two phases of the experiment (100…

  16. Optimal investment and scheduling of distributed energy resources with uncertainty in electric vehicle driving schedules

    International Nuclear Information System (INIS)

    Cardoso, G.; Stadler, M.; Bozchalui, M.C.; Sharma, R.; Marnay, C.; Barbosa-Póvoa, A.; Ferrão, P.

    2014-01-01

    The large scale penetration of electric vehicles (EVs) will introduce technical challenges to the distribution grid, but also carries the potential for vehicle-to-grid services. Namely, if available in large enough numbers, EVs can be used as a distributed energy resource (DER) and their presence can influence optimal DER investment and scheduling decisions in microgrids. In this work, a novel EV fleet aggregator model is introduced in a stochastic formulation of DER-CAM [1], an optimization tool used to address DER investment and scheduling problems. This is used to assess the impact of EV interconnections on optimal DER solutions considering uncertainty in EV driving schedules. Optimization results indicate that EVs can have a significant impact on DER investments, particularly if considering short payback periods. Furthermore, results suggest that uncertainty in driving schedules carries little significance to total energy costs, which is corroborated by results obtained using the stochastic formulation of the problem. - Highlights: • This paper introduces a new EV aggregator model in the DER-CAM model and expands it with a stochastic formulation. • The model is used to analyze the impact of EVs in DER investment decisions in a large office building. • The uncertainty in EV driving patterns is considered through scenarios based on data from a daily commute driving survey. • Results indicate that EVs have a significant impact in optimal DER decisions, particularly when looking at short payback periods. • Furthermore, results indicate that uncertainty in EV driving schedules has little impact on DER investment decisions

  17. Optimal Time-Abstract Schedulers for CTMDPs and Markov Games

    Directory of Open Access Journals (Sweden)

    Markus Rabe

    2010-06-01

    Full Text Available We study time-bounded reachability in continuous-time Markov decision processes for time-abstract scheduler classes. Such reachability problems play a paramount role in dependability analysis and the modelling of manufacturing and queueing systems. Consequently, their analysis has been studied intensively, and techniques for the approximation of optimal control are well understood. From a mathematical point of view, however, the question of approximation is secondary compared to the fundamental question whether or not optimal control exists. We demonstrate the existence of optimal schedulers for the time-abstract scheduler classes for all CTMDPs. Our proof is constructive: We show how to compute optimal time-abstract strategies with finite memory. It turns out that these optimal schedulers have an amazingly simple structure---they converge to an easy-to-compute memoryless scheduling policy after a finite number of steps. Finally, we show that our argument can easily be lifted to Markov games: We show that both players have a likewise simple optimal strategy in these more general structures.

  18. Optimal Power Scheduling for an Islanded Hybrid Microgrid

    DEFF Research Database (Denmark)

    Hernández, Adriana Carolina Luna; Aldana, Nelson Leonardo Diaz; Savaghebi, Mehdi

    2016-01-01

    A microgrid is a system that integrates energy generation, energy storage, and loads and it is able to operate either in interconnected or islanded mode. Energy resources should be scheduled to supply the load properly in order to coordinate optimally the power exchange within the microgrid...... according to a defined objective function. In this paper, an optimal power scheduling for generation and demand side is presented to manage an islanded hybrid PV-wind-battery microgrid implemented in Shanghai-China. The optimization is addressed through a Mixed-Integer Linear Programming (MILP) mathematical......SPACE1006) in which a scaled down model of this microgrid is emulated....

  19. Optimal recombination in genetic algorithms for flowshop scheduling problems

    Science.gov (United States)

    Kovalenko, Julia

    2016-10-01

    The optimal recombination problem consists in finding the best possible offspring as a result of a recombination operator in a genetic algorithm, given two parent solutions. We prove NP-hardness of the optimal recombination for various variants of the flowshop scheduling problem with makespan criterion and criterion of maximum lateness. An algorithm for solving the optimal recombination problem for permutation flowshop problems is built, using enumeration of prefect matchings in a special bipartite graph. The algorithm is adopted for the classical flowshop scheduling problem and for the no-wait flowshop problem. It is shown that the optimal recombination problem for the permutation flowshop scheduling problem is solvable in polynomial time for almost all pairs of parent solutions as the number of jobs tends to infinity.

  20. Enhanced OTSG economics optimizing CAPEX + OPEX + Schedule

    Energy Technology Data Exchange (ETDEWEB)

    Armstrong, Peter [KTI Engineered to Perform (Canada)

    2011-07-01

    This presentation gives an insight into the economics involved in producing once-through steam (OTSG) generators in Canada and it offers a proposal for improving returns in the industry. The objective of this presentation was to show the importance of developing OTSG manufacturing based on the future of this technology. The growing demand for OTSG by oil companies was presented, suggesting that this is a good time to put effort into developing more efficient designs. After the background of this technology was discussed, several economical aspects of the process were addressed; for instance, reducing capital expenditure (CAPEX) and operation expenditure (OPEX), outsourcing production, and project scheduling and execution. Initiatives proposed included: reducing plot size, producing larger OTSGs, reducing downtime, using alternative fuels, forming a global manufacturing network, and avoiding order blockage. Finally, the idea of designing a portable OTSG was proposed, showing its flexibility in oil extraction projects.

  1. Schedulability Analysis and Optimization for the Synthesis of Multi-Cluster Distributed Embedded Systems

    DEFF Research Database (Denmark)

    Pop, Paul; Eles, Petru; Peng, Zebo

    2003-01-01

    We present an approach to schedulability analysis for the synthesis of multi-cluster distributed embedded systems consisting of time-triggered and event-triggered clusters, interconnected via gateways. We have also proposed a buffer size and worst case queuing delay analysis for the gateways......, responsible for routing inter-cluster traffic. Optimization heuristics for the priority assignment and synthesis of bus access parameters aimed at producing a schedulable system with minimal buffer needs have been proposed. Extensive experiments and a real-life example show the efficiency of our approaches....

  2. Optimal mechanisms for single machine scheduling

    NARCIS (Netherlands)

    Heydenreich, B.; Mishra, D.; Müller, R.; Uetz, Marc Jochen; Papadimitriou, C.; Zhang, S.

    2008-01-01

    We study the design of optimal mechanisms in a setting here job-agents compete for being processed by a service provider that can handle one job at a time. Each job has a processing time and incurs a waiting cost. Jobs need to be compensated for waiting. We consider two models, one where only the

  3. Optimization of time–temperature schedule for nitridation of silicon ...

    Indian Academy of Sciences (India)

    Abstract. A time–temperature schedule for formation of silicon–nitride by direct nitridation of silicon com- pact was optimized by kinetic study of the reaction, 3Si + 2N2 = Si3N4 at four different temperatures (1250°C,. 1300°C, 1350°C and 1400°C). From kinetic study, three different temperature schedules were selected each ...

  4. Electric power systems advanced forecasting techniques and optimal generation scheduling

    CERN Document Server

    Catalão, João P S

    2012-01-01

    Overview of Electric Power Generation SystemsCláudio MonteiroUncertainty and Risk in Generation SchedulingRabih A. JabrShort-Term Load ForecastingAlexandre P. Alves da Silva and Vitor H. FerreiraShort-Term Electricity Price ForecastingNima AmjadyShort-Term Wind Power ForecastingGregor Giebel and Michael DenhardPrice-Based Scheduling for GencosGovinda B. Shrestha and Songbo QiaoOptimal Self-Schedule of a Hydro Producer under UncertaintyF. Javier Díaz and Javie

  5. Optimization of injection scheduling in geothermal fields

    Energy Technology Data Exchange (ETDEWEB)

    Lovekin, J.

    1987-05-01

    This study discusses the application of algorithms developed in Operations Research to the optimization of brine reinjection in geothermal fields. The injection optimization problem is broken into two sub-problems: (1) choosing a configuration of injectors from an existing set of wells, and (2) allocating a total specified injection rate among chosen injectors. The allocation problem is solved first. The reservoir is idealized as a network of channels or arcs directly connecting each pair of wells in the field. Each arc in the network is considered to have some potential for thermal breakthrough. This potential is quantified by an arc-specific break-through index, b/sub ij/, based on user-specified parameters from tracer tests, field geometry, and operating considerations. The sum of b/sub ij/-values for all arcs is defined as the fieldwide breakthrough index, B. Injection is optimized by choosing injection wells and rates so as to minimize B subject to constraints on the number of injectors and the total amount of fluid to be produced and reinjected. The study presents four computer programs which employ linear or quadratic programming to solve the allocation problem. In addition, a program is presented which solves the injector configuration problem by a combination of enumeration and quadratic programming. The use of the various programs is demonstrated with reference both to hypothetical data and an actual data set from the Wairakei Geothermal Field in New Zealand.

  6. Scheduling Patients’ Appointments: Allocation of Healthcare Service Using Simulation Optimization

    Directory of Open Access Journals (Sweden)

    Ping-Shun Chen

    2015-01-01

    Full Text Available In the service industry, scheduling medical procedures causes difficulties for both patients and management. Factors such as fluctuations in customer demand and service time affect the appointment scheduling systems’ performance in terms of, for example, patients’ waiting time, idle time of resources, and total cost/profits. This research implements four appointment scheduling policies, i.e., constant arrival, mixed patient arrival, three-section pattern arrival, and irregular arrival, in an ultrasound department of a hospital in Taiwan. By simulating the four implemented policies’ optimization procedures, optimal or near-optimal solutions can be obtained for patients per arrival, patients’ inter-arrival time, and the number of the time slots for arrived patients. Furthermore, three objective functions are tested, and the results are discussed. The managerial implications and discussions are summarized to demonstrate how outcomes can be useful for hospital managers seeking to allocate their healthcare service capacities.

  7. Comparison Performance of Genetic Algorithm and Ant Colony Optimization in Course Scheduling Optimizing

    Directory of Open Access Journals (Sweden)

    Imam Ahmad Ashari

    2016-11-01

    Full Text Available Scheduling problems at the university is a complex type of scheduling problems. The scheduling process should be carried out at every turn of the semester's. The core of the problem of scheduling courses at the university is that the number of components that need to be considered in making the schedule, some of the components was made up of students, lecturers, time and a room with due regard to the limits and certain conditions so that no collision in the schedule such as mashed room, mashed lecturer and others. To resolve a scheduling problem most appropriate technique used is the technique of optimization. Optimization techniques can give the best results desired. Metaheuristic algorithm is an algorithm that has a lot of ways to solve the problems to the very limit the optimal solution. In this paper, we use a genetic algorithm and ant colony optimization algorithm is an algorithm metaheuristic to solve the problem of course scheduling. The two algorithm will be tested and compared to get performance is the best. The algorithm was tested using data schedule courses of the university in Semarang. From the experimental results we conclude that the genetic algorithm has better performance than the ant colony optimization  algorithm in solving the case of course scheduling.

  8. Channel access delay and buffer distribution of two-user opportunistic scheduling schemes in wireless networks

    KAUST Repository

    Hossain, Md Jahangir

    2010-07-01

    In our earlier works, we proposed rate adaptive hierarchical modulation-assisted two-best user opportunistic scheduling (TBS) and hybrid two-user scheduling (HTS) schemes. The proposed schemes are innovative in the sense that they include a second user in the transmission opportunistically using hierarchical modulations. As such the frequency of information access of the users increases without any degradation of the system spectral efficiency (SSE) compared to the classical opportunistic scheduling scheme. In this paper, we analyze channel access delay of an incoming packet at the base station (BS) buffer when our proposed TBS and HTS schemes are employed at the BS. Specifically, using a queuing analytic model we derive channel access delay as well as buffer distribution of the packets that wait at BS buffer for down-link (DL) transmission. We compare performance of the TBS and HTS schemes with that of the classical single user opportunistic schemes namely, absolute carrier-to-noise ratio (CNR)-based single user scheduling (ASS) and normalized CNR-based single user scheduling (NSS). For an independent and identically distributed (i.i.d.) fading environment, our proposed scheme can improve packet\\'s access delay performance compared to the ASS. Selected numerical results in an independent but non-identically distributed (i.n.d.) fading environment show that our proposed HTS achieves overall good channel access delay performance. © 2010 IEEE.

  9. WFIRST: Exoplanet Target Selection and Scheduling with Greedy Optimization

    Science.gov (United States)

    Keithly, Dean; Garrett, Daniel; Delacroix, Christian; Savransky, Dmitry

    2018-01-01

    We present target selection and scheduling algorithms for missions with direct imaging of exoplanets, and the Wide Field Infrared Survey Telescope (WFIRST) in particular, which will be equipped with a coronagraphic instrument (CGI). Optimal scheduling of CGI targets can maximize the expected value of directly imaged exoplanets (completeness). Using target completeness as a reward metric and integration time plus overhead time as a cost metric, we can maximize the sum completeness for a mission with a fixed duration. We optimize over these metrics to create a list of target stars using a greedy optimization algorithm based off altruistic yield optimization (AYO) under ideal conditions. We simulate full missions using EXOSIMS by observing targets in this list for their predetermined integration times. In this poster, we report the theoretical maximum sum completeness, mean number of detected exoplanets from Monte Carlo simulations, and the ideal expected value of the simulated missions.

  10. Optimal load scheduling in commercial and residential microgrids

    Science.gov (United States)

    Ganji Tanha, Mohammad Mahdi

    Residential and commercial electricity customers use more than two third of the total energy consumed in the United States, representing a significant resource of demand response. Price-based demand response, which is in response to changes in electricity prices, represents the adjustments in load through optimal load scheduling (OLS). In this study, an efficient model for OLS is developed for residential and commercial microgrids which include aggregated loads in single-units and communal loads. Single unit loads which include fixed, adjustable and shiftable loads are controllable by the unit occupants. Communal loads which include pool pumps, elevators and central heating/cooling systems are shared among the units. In order to optimally schedule residential and commercial loads, a community-based optimal load scheduling (CBOLS) is proposed in this thesis. The CBOLS schedule considers hourly market prices, occupants' comfort level, and microgrid operation constraints. The CBOLS' objective in residential and commercial microgrids is the constrained minimization of the total cost of supplying the aggregator load, defined as the microgrid load minus the microgrid generation. This problem is represented by a large-scale mixed-integer optimization for supplying single-unit and communal loads. The Lagrangian relaxation methodology is used to relax the linking communal load constraint and decompose the independent single-unit functions into subproblems which can be solved in parallel. The optimal solution is acceptable if the aggregator load limit and the duality gap are within the bounds. If any of the proposed criteria is not satisfied, the Lagrangian multiplier will be updated and a new optimal load schedule will be regenerated until both constraints are satisfied. The proposed method is applied to several case studies and the results are presented for the Galvin Center load on the 16th floor of the IIT Tower in Chicago.

  11. Human-Machine Collaborative Optimization via Apprenticeship Scheduling

    Science.gov (United States)

    2016-09-09

    have been proven op- timal within that threshold. Thus, an operator can use CO- VAS as an anytime algorithm and terminate the optimization upon...mixed-integer linear programs via branch-and-bound search. COVAS incorporates the solution produced by the apprenticeship scheduler to seed a mathe

  12. Optimal charging schedule of an electric vehicle fleet

    DEFF Research Database (Denmark)

    Hu, Junjie; You, Shi; Østergaard, Jacob

    2011-01-01

    In this paper, we propose an approach to optimize the charging schedule of an Electric Vehicle (EV) fleet both taking into account spot price and individual EV driving requirement with the goal of minimizing charging costs. A flexible and suitable mathematic model is introduced to characterize th...

  13. Optimization of the solution of the problem of scheduling theory ...

    African Journals Online (AJOL)

    This article describes the genetic algorithm used to solve the problem related to the scheduling theory. A large number of different methods is described in the scientific literature. The main issue that faced the problem in question is that it is necessary to search the optimal solution in a large search space for the set of ...

  14. Verification and Optimization of a PLC Control Schedule

    NARCIS (Netherlands)

    Brinksma, Hendrik; Mader, Angelika H.; Fehnker, Ansgar; Fehnker, Ansgar

    2002-01-01

    We report on the use of model checking techniques for both the verification of a process control program and the derivation of optimal control schedules. Most of this work has been carried out as part of a case study for the EU VHS project (Verification of Hybrid Systems), in which the program for a

  15. Verification and Optimization of a PLC Control Schedule

    NARCIS (Netherlands)

    Brinksma, Hendrik; Mader, Angelika H.; Havelund, K.; Penix, J.; Visser, W.

    We report on the use of the SPIN model checker for both the verification of a process control program and the derivation of optimal control schedules. This work was carried out as part of a case study for the EC VHS project (Verification of Hybrid Systems), in which the program for a Programmable

  16. Optimal charging schedule of an electric vehicle fleet

    DEFF Research Database (Denmark)

    Hu, Junjie; You, Shi; Østergaard, Jacob

    2011-01-01

    In this paper, we propose an approach to optimize the charging schedule of an Electric Vehicle (EV) fleet both taking into account spot price and individual EV driving requirement with the goal of minimizing charging costs. A flexible and suitable mathematic model is introduced to characterize...

  17. Optimal adaptive scheduling and control of beer membrane filtration

    NARCIS (Netherlands)

    Willigenburg, van L.G.; Vollebregt, H.M.; Sman, van der R.G.M.

    2015-01-01

    An adaptive optimal scheduling and controller design is presented that attempts to improve the performance of beer membrane filtration over the ones currently obtained by operators. The research was performed as part of a large European research project called EU Cafe with the aim to investigate the

  18. Intelligent discrete particle swarm optimization for multiprocessor task scheduling problem

    Directory of Open Access Journals (Sweden)

    S Sarathambekai

    2017-03-01

    Full Text Available Discrete particle swarm optimization is one of the most recently developed population-based meta-heuristic optimization algorithm in swarm intelligence that can be used in any discrete optimization problems. This article presents a discrete particle swarm optimization algorithm to efficiently schedule the tasks in the heterogeneous multiprocessor systems. All the optimization algorithms share a common algorithmic step, namely population initialization. It plays a significant role because it can affect the convergence speed and also the quality of the final solution. The random initialization is the most commonly used method in majority of the evolutionary algorithms to generate solutions in the initial population. The initial good quality solutions can facilitate the algorithm to locate the optimal solution or else it may prevent the algorithm from finding the optimal solution. Intelligence should be incorporated to generate the initial population in order to avoid the premature convergence. This article presents a discrete particle swarm optimization algorithm, which incorporates opposition-based technique to generate initial population and greedy algorithm to balance the load of the processors. Make span, flow time, and reliability cost are three different measures used to evaluate the efficiency of the proposed discrete particle swarm optimization algorithm for scheduling independent tasks in distributed systems. Computational simulations are done based on a set of benchmark instances to assess the performance of the proposed algorithm.

  19. Advanced sleep schedules affect circadian gene expression in young adults with delayed sleep schedules.

    Science.gov (United States)

    Zhu, Yong; Fu, Alan; Hoffman, Aaron E; Figueiro, Mariana G; Carskadon, Mary A; Sharkey, Katherine M; Rea, Mark S

    2013-05-01

    Human circadian rhythms are regulated by the interplay between circadian genes and environmental stimuli. The influence of altered sleep-wake schedules or light on human circadian gene expression patterns is not well characterized. Twenty-one young adults were asked to keep to their usual sleep schedules and two blood samples were drawn at the end of the first week from each subject based on estimated time of dim light melatonin onset (DLMO); the first sample was obtained one and a half hours before the estimated DLMO and the second three hours later, at one and a half hours after the estimated DLMO. During the second week, participants were randomized into two groups, one that received a one hour blue-light (λmax=470 nm) exposure in the morning and one that received a comparable morning dim-light exposure. Two blood samples were obtained at the same clock times as the previous week at the end of the second week. We measured the expression of 10 circadian genes in response to sleep-wake schedule advancement and morning blue-light stimulation in the peripheral blood of 21 participants during a two-week field study. We found that nine of the 10 circadian genes showed significant expression changes from the first to the second week for participants in both the blue-light and dim-light groups, likely reflecting significant advances in circadian phase. This wholesale change in circadian gene expression may reflect considerable advances in circadian phase (i.e., advance in DLMO) from the first to the second week resulting from the advanced, daily personal light exposures. Copyright © 2013 Elsevier B.V. All rights reserved.

  20. Application of multiobjective optimization to scheduling capacity expansion of urban water resource systems

    Science.gov (United States)

    Mortazavi-Naeini, Mohammad; Kuczera, George; Cui, Lijie

    2014-06-01

    Significant population increase in urban areas is likely to result in a deterioration of drought security and level of service provided by urban water resource systems. One way to cope with this is to optimally schedule the expansion of system resources. However, the high capital costs and environmental impacts associated with expanding or building major water infrastructure warrant the investigation of scheduling system operational options such as reservoir operating rules, demand reduction policies, and drought contingency plans, as a way of delaying or avoiding the expansion of water supply infrastructure. Traditionally, minimizing cost has been considered the primary objective in scheduling capacity expansion problems. In this paper, we consider some of the drawbacks of this approach. It is shown that there is no guarantee that the social burden of coping with drought emergencies is shared equitably across planning stages. In addition, it is shown that previous approaches do not adequately exploit the benefits of joint optimization of operational and infrastructure options and do not adequately address the need for the high level of drought security expected for urban systems. To address these shortcomings, a new multiobjective optimization approach to scheduling capacity expansion in an urban water resource system is presented and illustrated in a case study involving the bulk water supply system for Canberra. The results show that the multiobjective approach can address the temporal equity issue of sharing the burden of drought emergencies and that joint optimization of operational and infrastructure options can provide solutions superior to those just involving infrastructure options.

  1. Joint optimization of production scheduling and machine group preventive maintenance

    International Nuclear Information System (INIS)

    Xiao, Lei; Song, Sanling; Chen, Xiaohui; Coit, David W.

    2016-01-01

    Joint optimization models were developed combining group preventive maintenance of a series system and production scheduling. In this paper, we propose a joint optimization model to minimize the total cost including production cost, preventive maintenance cost, minimal repair cost for unexpected failures and tardiness cost. The total cost depends on both the production process and the machine maintenance plan associated with reliability. For the problems addressed in this research, any machine unavailability leads to system downtime. Therefore, it is important to optimize the preventive maintenance of machines because their performance impacts the collective production processing associated with all machines. Too lengthy preventive maintenance intervals may be associated with low scheduled machine maintenance cost, but may incur expensive costs for unplanned failure due to low machine reliability. Alternatively, too frequent preventive maintenance activities may achieve the desired high reliability machines, but unacceptably high scheduled maintenance cost. Additionally, product scheduling plans affect tardiness and maintenance cost. Two results are obtained when solving the problem; the optimal group preventive maintenance interval for machines, and the assignment of each job, including the corresponding start time and completion time. To solve this non-deterministic polynomial-time problem, random keys genetic algorithms are used, and a numerical example is solved to illustrate the proposed model. - Highlights: • Group preventive maintenance (PM) planning and production scheduling are jointed. • Maintenance interval and assignment of jobs are decided by minimizing total cost. • Relationships among system age, PM, job processing time are quantified. • Random keys genetic algorithms (GA) are used to solve the NP-hard problem. • Random keys GA and Particle Swarm Optimization (PSO) are compared.

  2. Preemptive scheduling of independent jobs on identical parallel machines subject to migration delays

    NARCIS (Netherlands)

    Sevastyanov, S. V.; Sitters, R. A.; Fishkin, A.V.

    2010-01-01

    We present hardness and approximation results for the problem of preemptive scheduling of n independent jobs on m identical parallel machines subject to a migration delay d with the objective to minimize the makespan. We give a sharp threshold on the value of d for which the complexity of the

  3. Optimal Scheduling of Residential Microgrids Considering Virtual Energy Storage System

    Directory of Open Access Journals (Sweden)

    Weiliang Liu

    2018-04-01

    Full Text Available The increasingly complex residential microgrids (r-microgrid consisting of renewable generation, energy storage systems, and residential buildings require a more intelligent scheduling method. Firstly, aiming at the radiant floor heating/cooling system widely utilized in residential buildings, the mathematical relationship between the operative temperature and heating/cooling demand is established based on the equivalent thermodynamic parameters (ETP model, by which the thermal storage capacity is analyzed. Secondly, the radiant floor heating/cooling system is treated as virtual energy storage system (VESS, and an optimization model based on mixed-integer nonlinear programming (MINLP for r-microgrid scheduling is established which takes thermal comfort level and economy as the optimization objectives. Finally, the optimal scheduling results of two typical r-microgrids are analyzed. Case studies demonstrate that the proposed scheduling method can effectively employ the thermal storage capacity of radiant floor heating/cooling system, thus lowering the operating cost of the r-microgrid effectively while ensuring the thermal comfort level of users.

  4. Routing and Scheduling in Tramp Shipping - Integrating Bunker Optimization

    DEFF Research Database (Denmark)

    Vilhelmsen, Charlotte; Lusby, Richard Martin; Larsen, Jesper

    A tramp ship operator typically has some contracted cargoes that must be carried and seeks to maximize proFIt by carrying optional cargoes. Hence, tramp ships operate much like taxies following available cargoes and not according to a fixed route network and itinerary as liner ships. Marine fuel...... and scheduling phase and present a mixed integer programming formulation for the integrated problem of optimally routing, scheduling and bunkering a tramp fleet. Aside from the integration of bunker, this model also extends standard tramp formulations by using load dependent costs, speed and bunker consumption...

  5. Tramp ship routing and scheduling with integrated bunker optimization

    DEFF Research Database (Denmark)

    Vilhelmsen, Charlotte; Lusby, Richard Martin; Larsen, Jesper

    2014-01-01

    A tramp ship operator typically has some contracted cargoes that must be carried and seeks to maximize prot by carrying optional cargoes. Hence, tramp ships operate much like taxies following available cargoes and not according to a fixed route network and itinerary as liner ships. Marine fuel...... and scheduling phase and present a mixed integer programming formulation for the integrated problem of optimally routing, scheduling and bunkering a tramp fleet. Aside from the integration of bunker, this model also extends standard tramp formulations by using load dependent costs, speed and bunker consumption...

  6. Optimal physicians schedule in an Intensive Care Unit

    Science.gov (United States)

    Hidri, L.; Labidi, M.

    2016-05-01

    In this paper, we consider a case study for the problem of physicians scheduling in an Intensive Care Unit (ICU). The objective is to minimize the total overtime under complex constraints. The considered ICU is composed of three buildings and the physicians are divided accordingly into six teams. The workload is assigned to each team under a set of constraints. The studied problem is composed of two simultaneous phases: composing teams and assigning the workload to each one of them. This constitutes an additional major hardness compared to the two phase's process: composing teams and after that assigning the workload. The physicians schedule in this ICU is used to be done manually each month. In this work, the studied physician scheduling problem is formulated as an integer linear program and solved optimally using state of the art software. The preliminary experimental results show that 50% of the overtime can be saved.

  7. Optimal Kalman Filtering for a Class of State Delay Systems with Randomly Multiple Sensor Delays

    Directory of Open Access Journals (Sweden)

    Dongyan Chen

    2014-01-01

    Full Text Available The optimal Kalman filtering problem is investigated for a class of discrete state delay stochastic systems with randomly multiple sensor delays. The phenomenon of measurement delay occurs in a random way and the delay rate for each sensor is described by a Bernoulli distributed random variable with known conditional probability. Based on the innovative analysis approach and recursive projection formula, a new linear optimal filter is designed such that, for the state delay and randomly multiple sensor delays with different delay rates, the filtering error is minimized in the sense of mean square and the filter gain is designed by solving the recursive matrix equation. Finally, a simulation example is given to illustrate the feasibility and effectiveness of the proposed filtering scheme.

  8. Optimal Intermittent Dose Schedules for Chemotherapy Using Genetic Algorithm

    Directory of Open Access Journals (Sweden)

    Nadia ALAM

    2013-08-01

    Full Text Available In this paper, a design method for optimal cancer chemotherapy schedules via genetic algorithm (GA is presented. The design targets the key objective of chemotherapy to minimize the size of cancer tumor after a predefined time with keeping toxic side effects in limit. This is a difficult target to achieve using conventional clinical methods due to poor therapeutic indices of existing anti-cancer drugs. Moreover, there are clinical limitations in treatment administration to maintain continuous treatment. Besides, carefully decided rest periods are recommended to for patient’s comfort. Three intermittent drug scheduling schemes are presented in this paper where GA is used to optimize the dose quantities and timings by satisfying several treatment constraints. All three schemes are found to be effective in total elimination of cancer tumor after an agreed treatment length. The number of cancer cells is found zero at the end of the treatment for all three cases with tolerable toxicity. Finally, two of the schemes, “Fixed interval variable dose (FIVD and “Periodic dose” that are periodic in characteristic have been emphasized due to their additional simplicity in administration along with friendliness to patients. responses to the designed treatment schedules. Therefore the proposed design method is capable of planning effective, simple, patient friendly and acceptable chemotherapy schedules.

  9. Integrating Cache-Related Pre-emption Delays into Analysis of Fixed Priority Scheduling with Pre-emption Thresholds

    NARCIS (Netherlands)

    Bril, R.J.; Altmeyer, S.; van den Heuvel, M.H.P.; Davis, R.I.; Behnam, M.

    2014-01-01

    Cache-related pre-emption delays (CRPD) have been integrated into the schedulability analysis of sporadic tasks with constrained deadlines for fixed-priority pre-emptive scheduling (FPPS). This paper generalizes that work by integrating CRPD into the schedulability analysis of tasks with arbitrary

  10. Resource-Optimal Scheduling Using Priced Timed Automata

    DEFF Research Database (Denmark)

    Larsen, Kim Guldstrand; Rasmussen, Jacob Illum; Subramani, K.

    2004-01-01

    In this paper, we show how the simple structure of the linear programs encountered during symbolic minimum-cost reachability analysis of priced timed automata can be exploited in order to substantially improve the performance of the current algorithm. The idea is rooted in duality of linear progr......-80 percent performance gain. As a main application area, we show how to solve energy-optimal task graph scheduling problems using the framework of priced timed automata....

  11. Practice Utilization of Algorithms for Analog Filter Group Delay Optimization

    Directory of Open Access Journals (Sweden)

    K. Hajek

    2007-04-01

    Full Text Available This contribution deals with an application of three different algorithms which optimize a group delay of analog filters. One of them is a part of the professional circuit simulator Micro Cap 7 and the others two original algorithms are developed in the MATLAB environment. An all-pass network is used to optimize the group delay of an arbitrary analog filter. Introduced algorithms look for an optimal order and optimal coefficients of an all-pass network transfer function. Theoretical foundations are introduced and all algorithms are tested using the optimization of testing analog filter. The optimization is always run three times because the second, third and fourth-order all-pass network is used. An equalization of the original group delay is a main objective of these optimizations. All outputs of all algorithms are critically evaluated and also described.

  12. Global Optimization of Nonlinear Blend-Scheduling Problems

    Directory of Open Access Journals (Sweden)

    Pedro A. Castillo Castillo

    2017-04-01

    Full Text Available The scheduling of gasoline-blending operations is an important problem in the oil refining industry. This problem not only exhibits the combinatorial nature that is intrinsic to scheduling problems, but also non-convex nonlinear behavior, due to the blending of various materials with different quality properties. In this work, a global optimization algorithm is proposed to solve a previously published continuous-time mixed-integer nonlinear scheduling model for gasoline blending. The model includes blend recipe optimization, the distribution problem, and several important operational features and constraints. The algorithm employs piecewise McCormick relaxation (PMCR and normalized multiparametric disaggregation technique (NMDT to compute estimates of the global optimum. These techniques partition the domain of one of the variables in a bilinear term and generate convex relaxations for each partition. By increasing the number of partitions and reducing the domain of the variables, the algorithm is able to refine the estimates of the global solution. The algorithm is compared to two commercial global solvers and two heuristic methods by solving four examples from the literature. Results show that the proposed global optimization algorithm performs on par with commercial solvers but is not as fast as heuristic approaches.

  13. Optimal Residential Load Scheduling Under Utility and Rooftop Photovoltaic Units

    Directory of Open Access Journals (Sweden)

    Ghulam Hafeez

    2018-03-01

    Full Text Available With the rapid advancement in technology, electrical energy consumption is increasing rapidly. Especially, in the residential sector, more than 80% of electrical energy is being consumed because of consumer negligence. This brings the challenging task of maintaining the balance between the demand and supply of electric power. In this paper, we focus on the problem of load balancing via load scheduling under utility and rooftop photovoltaic (PV units to reduce electricity cost and peak to average ratio (PAR in demand-side management. For this purpose, we adopted genetic algorithm (GA, binary particle swarm optimization (BPSO, wind-driven optimization (WDO, and our proposed genetic WDO (GWDO algorithm, which is a hybrid of GA and WDO, to schedule the household load. For energy cost estimation, combined real-time pricing (RTP and inclined block rate (IBR were used. The proposed algorithm shifts load from peak consumption hours to off-peak hours based on combined pricing scheme and generation from rooftop PV units. Simulation results validate our proposed GWDO algorithm in terms of electricity cost and PAR reduction while considering all three scenarios which we have considered in this work: (1 load scheduling without renewable energy sources (RESs and energy storage system (ESS, (2 load scheduling with RESs, and (3 load scheduling with RESs and ESS. Furthermore, our proposed scheme reduced electricity cost and PAR by 22.5% and 29.1% in scenario 1, 47.7% and 30% in scenario 2, and 49.2% and 35.4% in scenario 3, respectively, as compared to unscheduled electricity consumption.

  14. A probabilistic computational framework for bridge network optimal maintenance scheduling

    International Nuclear Information System (INIS)

    Bocchini, Paolo; Frangopol, Dan M.

    2011-01-01

    This paper presents a probabilistic computational framework for the Pareto optimization of the preventive maintenance applications to bridges of a highway transportation network. The bridge characteristics are represented by their uncertain reliability index profiles. The in/out of service states of the bridges are simulated taking into account their correlation structure. Multi-objective Genetic Algorithms have been chosen as numerical tool for the solution of the optimization problem. The design variables of the optimization are the preventive maintenance schedules of all the bridges of the network. The two conflicting objectives are the minimization of the total present maintenance cost and the maximization of the network performance indicator. The final result is the Pareto front of optimal solutions among which the managers should chose, depending on engineering and economical factors. A numerical example illustrates the application of the proposed approach.

  15. Optimal scheduling of micro grids based on single objective programming

    Science.gov (United States)

    Chen, Yue

    2018-04-01

    Faced with the growing demand for electricity and the shortage of fossil fuels, how to optimally optimize the micro-grid has become an important research topic to maximize the economic, technological and environmental benefits of the micro-grid. This paper considers the role of the battery and the micro-grid and power grid to allow the exchange of power not exceeding 150kW preconditions, the main study of the economy to load for the goal is to minimize the electricity cost (abandonment of wind), to establish an optimization model, and to solve the problem by genetic algorithm. The optimal scheduling scheme is obtained and the utilization of renewable energy and the impact of the battery involved in regulation are analyzed.

  16. Estimating the minimum delay optimal cycle length based on a time-dependent delay formula

    Directory of Open Access Journals (Sweden)

    Ahmed Y. Zakariya

    2016-09-01

    Full Text Available For fixed time traffic signal control, the well-known Webster’s formula is widely used to estimate the minimum delay optimal cycle length. However, this formula overestimates the cycle length for high degrees of saturation. In this paper, we propose two regression formulas for estimating the minimum delay optimal cycle length based on a time-dependent delay formula as used in the Canadian Capacity Guide and the Highway Capacity Manual (HCM. For this purpose, we develop a search algorithm to determine the minimum delay optimal cycle length required for the regression analysis. Numerical results show that the proposed formulas give a better estimation for the optimal cycle length at high intersection flow ratios compared to Webster’s formula.

  17. Routing and Scheduling Optimization Model of Sea Transportation

    Science.gov (United States)

    barus, Mika debora br; asyrafy, Habib; nababan, Esther; mawengkang, Herman

    2018-01-01

    This paper examines the routing and scheduling optimization model of sea transportation. One of the issues discussed is about the transportation of ships carrying crude oil (tankers) which is distributed to many islands. The consideration is the cost of transportation which consists of travel costs and the cost of layover at the port. Crude oil to be distributed consists of several types. This paper develops routing and scheduling model taking into consideration some objective functions and constraints. The formulation of the mathematical model analyzed is to minimize costs based on the total distance visited by the tanker and minimize the cost of the ports. In order for the model of the problem to be more realistic and the cost calculated to be more appropriate then added a parameter that states the multiplier factor of cost increases as the charge of crude oil is filled.

  18. Flow shop scheduling algorithm to optimize warehouse activities

    Directory of Open Access Journals (Sweden)

    P. Centobelli

    2016-01-01

    Full Text Available Successful flow-shop scheduling outlines a more rapid and efficient process of order fulfilment in warehouse activities. Indeed the way and the speed of order processing and, in particular, the operations concerning materials handling between the upper stocking area and a lower forward picking one must be optimized. The two activities, drops and pickings, have considerable impact on important performance parameters for Supply Chain wholesaler companies. In this paper, a new flow shop scheduling algorithm is formulated in order to process a greater number of orders by replacing the FIFO logic for the drops activities of a wholesaler company on a daily basis. The System Dynamics modelling and simulation have been used to simulate the actual scenario and the output solutions. Finally, a t-Student test validates the modelled algorithm, granting that it can be used for all wholesalers based on drop and picking activities.

  19. Optimal Sensor Networks Scheduling in Identification of Distributed Parameter Systems

    CERN Document Server

    Patan, Maciej

    2012-01-01

    Sensor networks have recently come into prominence because they hold the potential to revolutionize a wide spectrum of both civilian and military applications. An ingenious characteristic of sensor networks is the distributed nature of data acquisition. Therefore they seem to be ideally prepared for the task of monitoring processes with spatio-temporal dynamics which constitute one of most general and important classes of systems in modelling of the real-world phenomena. It is clear that careful deployment and activation of sensor nodes are critical for collecting the most valuable information from the observed environment. Optimal Sensor Network Scheduling in Identification of Distributed Parameter Systems discusses the characteristic features of the sensor scheduling problem, analyzes classical and recent approaches, and proposes a wide range of original solutions, especially dedicated for networks with mobile and scanning nodes. Both researchers and practitioners will find the case studies, the proposed al...

  20. Schedule Optimization Study, Hanford RI/FS Program

    Energy Technology Data Exchange (ETDEWEB)

    1992-12-01

    A Schedule Optimization Study (SOS) of the US Department of Energy (DOE) Hanford Site Remedial Investigation/Feasibility Study (RI/FS) Program was conducted by an independent team of professionals from other federal agencies and the private sector experienced in environmental restoration. This team spent two weeks at Hanford in September 1992 examining the reasons for the lengthy RI/FS process at Hanford and developing recommendations to expedite the process. The need for the study arose out of a schedule dispute regarding the submission of the 1100-EM-1 Operable Unit RI/FS Work Plan. This report documents the study called for in the August 29, 1991, Dispute Resolution Committee Decision Statement. Battelle's Environmental Management Operations (EMO) coordinated the effort for DOE's Richland Field Office (RL).

  1. A PSO approach for preventive maintenance scheduling optimization

    International Nuclear Information System (INIS)

    Pereira, C.M.N.A.; Lapa, C.M.F.; Mol, A.C.A.; Luz, A.F. da

    2009-01-01

    This work presents a Particle Swarm Optimization (PSO) approach for preventive maintenance policy optimization, focused in reliability and cost. The probabilistic model for reliability and cost evaluation is developed in such a way that flexible intervals between maintenance are allowed. As PSO is skilled for realcoded continuous spaces, a non-conventional codification has been developed in order to allow PSO to solve scheduling problems (which is discrete) with variable number of maintenance interventions. In order to evaluate the proposed methodology, the High Pressure Injection System (HPIS) of a typical 4-loop PWR has been considered. Results demonstrate ability in finding optimal solutions, for which expert knowledge had to be automatically discovered by PSO. (author)

  2. MDTM: Optimizing Data Transfer using Multicore-Aware I/O Scheduling

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Liang [Fermilab; Demar, Phil [Fermilab; Wu, Wenji [Fermilab; Kim, Bockjoo [Florida U.

    2017-05-09

    Bulk data transfer is facing significant challenges in the coming era of big data. There are multiple performance bottlenecks along the end-to-end path from the source to destination storage system. The limitations of current generation data transfer tools themselves can have a significant impact on end-to-end data transfer rates. In this paper, we identify the issues that lead to underperformance of these tools, and present a new data transfer tool with an innovative I/O scheduler called MDTM. The MDTM scheduler exploits underlying multicore layouts to optimize throughput by reducing delay and contention for I/O reading and writing operations. With our evaluations, we show how MDTM successfully avoids NUMA-based congestion and significantly improves end-to-end data transfer rates across high-speed wide area networks.

  3. MDTM: Optimizing Data Transfer using Multicore-Aware I/O Scheduling

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Liang [Fermilab; Demar, Phil [Fermilab; Wu, Wenji [Fermilab; Kim, Bockjoo [Florida U.

    2017-01-01

    Bulk data transfer is facing significant challenges in the coming era of big data. There are multiple performance bottlenecks along the end-to-end path from the source to destination storage system. The limitations of current generation data transfer tools themselves can have a significant impact on end-to-end data transfer rates. In this paper, we identify the issues that lead to underperformance of these tools, and present a new data transfer tool with an innovative I/O scheduler called MDTM. The MDTM scheduler exploits underlying multicore layouts to optimize throughput by reducing delay and contention for I/O reading and writing operations. With our evaluations, we show how MDTM successfully avoids NUMA-based congestion and significantly improves end-to-end data transfer rates across high-speed wide area networks.

  4. A robust optimization approach for energy generation scheduling in microgrids

    International Nuclear Information System (INIS)

    Wang, Ran; Wang, Ping; Xiao, Gaoxi

    2015-01-01

    Highlights: • A new uncertainty model is proposed for better describing unstable energy demands. • An optimization problem is formulated to minimize the cost of microgrid operations. • Robust optimization algorithms are developed to transform and solve the problem. • The proposed scheme can prominently reduce energy expenses. • Numerical results provide useful insights for future investment policy making. - Abstract: In this paper, a cost minimization problem is formulated to intelligently schedule energy generations for microgrids equipped with unstable renewable sources and combined heat and power (CHP) generators. In such systems, the fluctuant net demands (i.e., the electricity demands not balanced by renewable energies) and heat demands impose unprecedented challenges. To cope with the uncertainty nature of net demand and heat demand, a new flexible uncertainty model is developed. Specifically, we introduce reference distributions according to predictions and field measurements and then define uncertainty sets to confine net and heat demands. The model allows the net demand and heat demand distributions to fluctuate around their reference distributions. Another difficulty existing in this problem is the indeterminate electricity market prices. We develop chance constraint approximations and robust optimization approaches to firstly transform and then solve the prime problem. Numerical results based on real-world data evaluate the impacts of different parameters. It is shown that our energy generation scheduling strategy performs well and the integration of combined heat and power (CHP) generators effectively reduces the system expenditure. Our research also helps shed some illuminations on the investment policy making for microgrids.

  5. A Comparison between Fixed Priority and EDF Scheduling accounting for Cache Related Pre-emption Delays

    Directory of Open Access Journals (Sweden)

    Will Lunniss

    2014-04-01

    Full Text Available In multitasking real-time systems, the choice of scheduling algorithm is an important factor to ensure that response time requirements are met while maximising limited system resources. Two popular scheduling algorithms include fixed priority (FP and earliest deadline first (EDF. While they have been studied in great detail before, they have not been compared when taking into account cache related pre-emption delays (CRPD. Memory and cache are split into a number of blocks containing instructions and data. During a pre-emption, cache blocks from the pre-empting task can evict those of the pre-empted task. When the pre-empted task is resumed, if it then has to re-load the evicted blocks, CRPD are introduced which then affect the schedulability of the task. In this paper we compare FP and EDF scheduling algorithms in the presence of CRPD using the state-of-the-art CRPD analysis. We find that when CRPD is accounted for, the performance gains offered by EDF over FP, while still notable, are diminished. Furthermore, we find that under scenarios that cause relatively high CRPD, task layout optimisation techniques can be applied to allow FP to schedule tasksets at a similar processor utilisation to EDF. Thus making the choice of the task layout in memory as important as the choice of scheduling algorithm. This is very relevant for industry, as it is much cheaper and simpler to adjust the task layout through the linker than it is to switch the scheduling algorithm.

  6. Optimal Workflow Scheduling in Critical Infrastructure Systems with Neural Networks

    Directory of Open Access Journals (Sweden)

    S. Vukmirović

    2012-04-01

    Full Text Available Critical infrastructure systems (CISs, such as power grids, transportation systems, communication networks and water systems are the backbone of a country’s national security and industrial prosperity. These CISs execute large numbers of workflows with very high resource requirements that can span through different systems and last for a long time. The proper functioning and synchronization of these workflows is essential since humanity’s well-being is connected to it. Because of this, the challenge of ensuring availability and reliability of these services in the face of a broad range of operating conditions is very complicated. This paper proposes an architecture which dynamically executes a scheduling algorithm using feedback about the current status of CIS nodes. Different artificial neural networks (ANNs were created in order to solve the scheduling problem. Their performances were compared and as the main result of this paper, an optimal ANN architecture for workflow scheduling in CISs is proposed. A case study is shown for a meter data management system with measurements from a power distribution management system in Serbia. Performance tests show that significant improvement of the overall execution time can be achieved by ANNs.

  7. A stochastic optimization model for shift scheduling in emergency departments.

    Science.gov (United States)

    El-Rifai, Omar; Garaix, Thierry; Augusto, Vincent; Xie, Xiaolan

    2015-09-01

    Excessive waiting time in Emergency Departments (ED) can be both a cause of frustration and more importantly, a health concern for patients. Waiting time arises when the demand for work goes beyond the facility's service capacity. ED service capacity mainly depends on human resources and on beds available for patients. In this paper, we focus on human resources organization in an ED and seek to best balance between service quality and working conditions. More specifically, we address the personnel scheduling problem in order to optimize the shift distribution among employees and minimize the total expected patients' waiting time. The problem is also characterized by a multi-stage re-entrant service process. With an appropriate approximation of patients' waiting times, we first propose a stochastic mixed-integer programming model that is solved by a sample average approximation (SAA) approach. The resulting personnel schedules are then evaluated using a discrete-event simulation model. Numerical experiments are then performed with data from a French hospital to compare different personnel scheduling strategies.

  8. Microgrid optimal scheduling considering impact of high penetration wind generation

    Science.gov (United States)

    Alanazi, Abdulaziz

    The objective of this thesis is to study the impact of high penetration wind energy in economic and reliable operation of microgrids. Wind power is variable, i.e., constantly changing, and nondispatchable, i.e., cannot be controlled by the microgrid controller. Thus an accurate forecasting of wind power is an essential task in order to study its impacts in microgrid operation. Two commonly used forecasting methods including Autoregressive Integrated Moving Average (ARIMA) and Artificial Neural Network (ANN) have been used in this thesis to improve the wind power forecasting. The forecasting error is calculated using a Mean Absolute Percentage Error (MAPE) and is improved using the ANN. The wind forecast is further used in the microgrid optimal scheduling problem. The microgrid optimal scheduling is performed by developing a viable model for security-constrained unit commitment (SCUC) based on mixed-integer linear programing (MILP) method. The proposed SCUC is solved for various wind penetration levels and the relationship between the total cost and the wind power penetration is found. In order to reduce microgrid power transfer fluctuations, an additional constraint is proposed and added to the SCUC formulation. The new constraint would control the time-based fluctuations. The impact of the constraint on microgrid SCUC results is tested and validated with numerical analysis. Finally, the applicability of proposed models is demonstrated through numerical simulations.

  9. Throughput optimization for dual collaborative spectrum sensing with dynamic scheduling

    Science.gov (United States)

    Cui, Cuimei; Yang, Dezhi

    2017-07-01

    Cognitive radio technology is envisaged to alleviate both spectrum inefficiency and spectrum scarcity problems by exploiting the existing licensed spectrum opportunistically. However, cognitive radio ad hoc networks (CRAHNs) impose unique challenges due to the high dynamic scheduling in the available spectrum, diverse quality of service (QOS) requirements, as well as hidden terminals and shadow fading issues in a harsh radio environment. To solve these problems, this paper proposes a dynamic and variable time-division multiple-access scheduling mechanism (DV-TDMA) incorporated with dual collaborative spectrum sensing scheme for CRAHNs. This study involves the cross-layered cooperation between the Physical (PHY) layer and Medium Access Control (MAC) layer under the consideration of average sensing time, sensing accuracy and the average throughput of cognitive radio users (CRs). Moreover, multiple-objective optimization algorithm is proposed to maximize the average throughput of CRs while still meeting QOS requirements on sensing time and detection error. Finally, performance evaluation is conducted through simulations, and the simulation results reveal that this optimization algorithm can significantly improve throughput and sensing accuracy and reduce average sensing time.

  10. Airline Schedule Disruption Management. The impact of flight delays on connection loss

    Directory of Open Access Journals (Sweden)

    Rahil Hicham

    2017-01-01

    Full Text Available Air travel demand is important and many travellers choose to drive to larger airports instead of flying from a small airport for many reasons, especially availability of non-stop flights. Another reason is perceived reliability of service. Consultants have pointed to a large number of delays and cancellations as reasons for low passenger. However, the effect of these flight delays on actual travel times is less clear. Because connections are usually necessary when traveling from small airports, departure delays may lead to missed connections. In the case of a cancellation, need to wait several hours (often overnight for the next flight due to the small number of daily departures. This paper evaluate the impact of delays and cancellations on the profit earned through the seats captured on new opened routes. This aspect of decision-making comes in the form of multi-objective problem by testing the impact of a new opened route in terms of flight delays costs, financial gain and the quality of the service provided to a target customer. The NSGA-II algorithm is adopted to generate a front of Pareto-optimal compound of a number of optimal departure times to the new destination while ensuring the best fill rate, and a minimum flight delays. The experiences are based on the flights of the Royal Air Maroc Company on the Casablanca hub.

  11. Optimal control of a delayed SLBS computer virus model

    Science.gov (United States)

    Chen, Lijuan; Hattaf, Khalid; Sun, Jitao

    2015-06-01

    In this paper, a delayed SLBS computer virus model is firstly proposed. To the best of our knowledge, this is the first time to discuss the optimal control of the SLBS model. By using the optimal control strategy, we present an optimal strategy to minimize the total number of the breakingout computers and the cost associated with toxication or detoxication. We show that an optimal control solution exists for the control problem. Some examples are presented to show the efficiency of this optimal control.

  12. Optimal state estimation over communication channels with random delays

    KAUST Repository

    Mahmoud, Magdi S.

    2013-04-01

    This paper is concerned with the optimal estimation of linear systems over unreliable communication channels with random delays. The measurements are delivered without time stamp, and the probabilities of time delays are assumed to be known. Since the estimation is time-driven, the actual time delays are converted into virtual time delays among the formulation. The receiver of estimation node stores the sum of arrived measurements between two adjacent processing time instants and also counts the number of arrived measurements. The original linear system is modeled as an extended system with uncertain observation to capture the feature of communication, then the optimal estimation algorithm of systems with uncertain observations is proposed. Additionally, a numerical simulation is presented to show the performance of this work. © 2013 The Franklin Institute.

  13. Distributed Optimal Consensus Control for Multiagent Systems With Input Delay.

    Science.gov (United States)

    Zhang, Huaipin; Yue, Dong; Zhao, Wei; Hu, Songlin; Dou, Chunxia

    2017-06-27

    This paper addresses the problem of distributed optimal consensus control for a continuous-time heterogeneous linear multiagent system subject to time varying input delays. First, by discretization and model transformation, the continuous-time input-delayed system is converted into a discrete-time delay-free system. Two delicate performance index functions are defined for these two systems. It is shown that the performance index functions are equivalent and the optimal consensus control problem of the input-delayed system can be cast into that of the delay-free system. Second, by virtue of the Hamilton-Jacobi-Bellman (HJB) equations, an optimal control policy for each agent is designed based on the delay-free system and a novel value iteration algorithm is proposed to learn the solutions to the HJB equations online. The proposed adaptive dynamic programming algorithm is implemented on the basis of a critic-action neural network (NN) structure. Third, it is proved that local consensus errors of the two systems and weight estimation errors of the critic-action NNs are uniformly ultimately bounded while the approximated control policies converge to their target values. Finally, two simulation examples are presented to illustrate the effectiveness of the developed method.

  14. Data Processing Delay Optimization in Mobile Edge Computing

    Directory of Open Access Journals (Sweden)

    Guangshun Li

    2018-01-01

    Full Text Available With the development of Internet of Things (IoT, the number of mobile terminal devices is increasing rapidly. Because of high transmission delay and limited bandwidth, in this paper, we propose a novel three-layer network architecture model which combines cloud computing and edge computing (abbreviated as CENAM. In edge computing layer, we propose a computational scheme of mutual cooperation between the edge devices and use the Kruskal algorithm to compute the minimum spanning tree of weighted undirected graph consisting of edge nodes, so as to reduce the communication delay between them. Then we divide and assign the tasks based on the constrained optimization problem and solve the computation delay of edge nodes by using the Lagrange multiplier method. In cloud computing layer, we focus on the balanced transmission method to solve the data transmission delay from edge devices to cloud servers and obtain an optimal allocation matrix, which reduces the data communication delay. Finally, according to the characteristics of cloud servers, we solve the computation delay of cloud computing layer. Simulation shows that the CENAM has better performance in data processing delay than traditional cloud computing.

  15. Incorporating High-Speed, Optimizing, Interleaving, Configurable/Composable Scheduling into NASA's EUROPA Planning Architecture Project

    Data.gov (United States)

    National Aeronautics and Space Administration — Advanced, robust, autonomous planning systems have not focused on the scheduling decisions made by the planner. And high quality, optimizing schedulers have rarely...

  16. OPTIMIZATION OF WOOD MILLING SCHEDULE – A CASE STUDY

    Directory of Open Access Journals (Sweden)

    Emilia-Adela SALCA

    2015-12-01

    Full Text Available The paper presents the results of a case study applied to the milling process of solid wood specimens made of black alder wood (Alnus glutinosa L. Gaertn. with a view to find the optimal cutting schedule when two main criteria, such as the minimum power consumption and the best surface quality are fulfilled.The experimental work was performed with black alder wood originating from mature trees from the Buzau Valley region in Romania. All samples were processed on their longitudinal edges by straight milling with a milling cutter having glued straight plates on the vertical milling machine under different cutting schedules. An electronic device connected to the machine engine and an acquisition board were used to record and compute the power consumption during milling. Roughness measurements of the samples were performed by employing an optical profilometer. All data were processed using the regression method and variance analysis. The study revealed that best results are to be obtained in terms of cutting power and surface quality when processing with low feed speeds and light cutting depths.

  17. Biopharmaceutical Process Optimization with Simulation and Scheduling Tools.

    Science.gov (United States)

    Petrides, Demetri; Carmichael, Doug; Siletti, Charles; Koulouris, Alexandros

    2014-09-29

    Design and assessment activities associated with a biopharmaceutical process are performed at different levels of detail, based on the stage of development that the product is in. Preliminary "back-of-the envelope" assessments are performed early in the development lifecycle, whereas detailed design and evaluation are performed prior to the construction of a new facility. Both the preliminary and detailed design of integrated biopharmaceutical processes can be greatly assisted by the use of process simulators, discrete event simulators or finite capacity scheduling tools. This report describes the use of such tools for bioprocess development, design, and manufacturing. The report is divided into three sections. Section One provides introductory information and explains the purpose of bioprocess simulation. Section Two focuses on the detailed modeling of a single batch bioprocess that represents the manufacturing of a therapeutic monoclonal antibody (MAb). This type of analysis is typically performed by engineers engaged in the development and optimization of such processes. Section Three focuses on production planning and scheduling models for multiproduct plants.

  18. Biopharmaceutical Process Optimization with Simulation and Scheduling Tools

    Directory of Open Access Journals (Sweden)

    Demetri Petrides

    2014-09-01

    Full Text Available Design and assessment activities associated with a biopharmaceutical process are performed at different levels of detail, based on the stage of development that the product is in. Preliminary “back-of-the envelope” assessments are performed early in the development lifecycle, whereas detailed design and evaluation are performed prior to the construction of a new facility. Both the preliminary and detailed design of integrated biopharmaceutical processes can be greatly assisted by the use of process simulators, discrete event simulators or finite capacity scheduling tools. This report describes the use of such tools for bioprocess development, design, and manufacturing. The report is divided into three sections. Section One provides introductory information and explains the purpose of bioprocess simulation. Section Two focuses on the detailed modeling of a single batch bioprocess that represents the manufacturing of a therapeutic monoclonal antibody (MAb. This type of analysis is typically performed by engineers engaged in the development and optimization of such processes. Section Three focuses on production planning and scheduling models for multiproduct plants.

  19. Optimal Rules for Single Machine Scheduling with Stochastic Breakdowns

    Directory of Open Access Journals (Sweden)

    Jinwei Gu

    2014-01-01

    Full Text Available This paper studies the problem of scheduling a set of jobs on a single machine subject to stochastic breakdowns, where jobs have to be restarted if preemptions occur because of breakdowns. The breakdown process of the machine is independent of the jobs processed on the machine. The processing times required to complete the jobs are constants if no breakdown occurs. The machine uptimes are independently and identically distributed (i.i.d. and are subject to a uniform distribution. It is proved that the Longest Processing Time first (LPT rule minimizes the expected makespan. For the large-scale problem, it is also showed that the Shortest Processing Time first (SPT rule is optimal to minimize the expected total completion times of all jobs.

  20. Circadian phase, dynamics of subjective sleepiness and sensitivity to blue light in young adults complaining of a delayed sleep schedule.

    Science.gov (United States)

    Moderie, Christophe; Van der Maren, Solenne; Dumont, Marie

    2017-06-01

    To assess factors that might contribute to a delayed sleep schedule in young adults with sub-clinical features of delayed sleep phase disorder. Two groups of 14 young adults (eight women) were compared: one group complaining of a delayed sleep schedule and a control group with an earlier bedtime and no complaint. For one week, each subject maintained a target bedtime reflecting their habitual sleep schedule. Subjects were then admitted to the laboratory for the assessment of circadian phase (dim light melatonin onset), subjective sleepiness, and non-visual light sensitivity. All measures were timed relative to each participant's target bedtime. Non-visual light sensitivity was evaluated using subjective sleepiness and salivary melatonin during 1.5-h exposure to blue light, starting one hour after target bedtime. Compared to control subjects, delayed subjects had a later circadian phase and a slower increase of subjective sleepiness in the late evening. There was no group difference in non-visual sensitivity to blue light, but we found a positive correlation between melatonin suppression and circadian phase within the delayed group. Our results suggest that a late circadian phase, a slow build-up of sleep need, and an increased circadian sensitivity to blue light contribute to the complaint of a delayed sleep schedule. These findings provide targets for strategies aiming to decreasing the severity of a sleep delay and the negative consequences on daytime functioning and health. Copyright © 2017 Elsevier B.V. All rights reserved.

  1. Seeking optimality in fruit pulping schedules: A case study*

    Directory of Open Access Journals (Sweden)

    J.H. Van Vuuren

    2014-01-01

    Full Text Available The process of scheduling fruit pulping for the production of fruit juices is of great importance in the beverage industry. Decisions have to be made regarding available processing time, the disposal of fruit that will not be pulped before stock loss due to spoilage, the fulfilment of customer demand and an optimal financial position. Sheduling depends on the capacity of the work force, pulping machine limitations and delivery deadlines. However, the situation is often encountered where the plant manager has to decide which fruit batches (usually from stock piles of overwhelming proportions during the harvesting season are to be pulped in order to minimize losses due to fruit deterioration. Such decisions are usually done manually, based on intuition and experience. A mathematical model is presented here which constructs a pulping strategy while minimising cascading financial losses associated with fruit grade drops within the stock pile. It is shown in particular that a minimisation of fruit losses is not a good criterion for optimality, and that substantial financial gains may be accomplished when minimising financial losses in stead of fruit losses, which is currently standard practice at most fruit pulping plants.

  2. Fairness in optimizing bus-crew scheduling process.

    Directory of Open Access Journals (Sweden)

    Jihui Ma

    Full Text Available This work proposes a model considering fairness in the problem of crew scheduling for bus drivers (CSP-BD using a hybrid ant-colony optimization (HACO algorithm to solve it. The main contributions of this work are the following: (a a valid approach for cases with a special cost structure and constraints considering the fairness of working time and idle time; (b an improved algorithm incorporating Gamma heuristic function and selecting rules. The relationships of each cost are examined with ten bus lines collected from the Beijing Public Transport Holdings (Group Co., Ltd., one of the largest bus transit companies in the world. It shows that unfair cost is indirectly related to common cost, fixed cost and extra cost and also the unfair cost approaches to common and fixed cost when its coefficient is twice of common cost coefficient. Furthermore, the longest time for the tested bus line with 1108 pieces, 74 blocks is less than 30 minutes. The results indicate that the HACO-based algorithm can be a feasible and efficient optimization technique for CSP-BD, especially with large scale problems.

  3. Optimizing Maximum Flow Time and Maximum Throughput in Broadcast Scheduling

    OpenAIRE

    Im, Sungjin; Sviridenko, Maxim

    2013-01-01

    We consider the pull-based broadcast scheduling model. In this model, there are n unit-sized pages of information available at the server. Requests arrive over time at the server asking for a specific page. When the server transmits a page, all outstanding requests for the page are simultaneously satisfied, and this is what distinguishes broadcast scheduling from the standard scheduling setting where each job must be processed separately by the server. Broadcast scheduling has received a cons...

  4. Optimal control for parabolic-hyperbolic system with time delay

    International Nuclear Information System (INIS)

    Kowalewski, A.

    1985-07-01

    In this paper we consider an optimal control problem for a system described by a linear partial differential equation of the parabolic-hyperbolic type with time delay in the state. The right-hand side of this equation and the initial conditions are not continuous functions usually, but they are measurable functions belonging to L 2 or Lsup(infinity) spaces. Therefore, the solution of this equation is given by a certain Sobolev space. The time delay in the state is constant, but it can be also a function of time. The control time T is fixed in our problem. Making use of the Milutin-Dubovicki theorem, necessary and sufficient conditions of optimality with the quadratic performance functional and constrained control are derived for the Dirichlet problem. The flow chart of the algorithm which can be used in the numerical solving of certain optimization problems for distributed systems is also presented. (author)

  5. Optimal Temporal Decoupling in Task Scheduling with Preferences

    NARCIS (Netherlands)

    Endhoven, L.; Klos, T.B.; Witteveen, C.

    2011-01-01

    Multi-agent planning and scheduling concerns finding a joint plan to achieve some set of common goals with several independent agents each aiming to find a plan or schedule for their part of the goals. To avoid conflicts in these individual plans or schedules decoupling is used. Such a decoupling

  6. Optimal scheduling for distributed hybrid system with pumped hydro storage

    International Nuclear Information System (INIS)

    Kusakana, Kanzumba

    2016-01-01

    Highlights: • Pumped hydro storage is proposed for isolated hybrid PV–Wind–Diesel systems. • Optimal control is developed to dispatch power flow economically. • A case study is conducted using the model for an isolated load. • Effects of seasons on the system’s optimal scheduling are examined through simulation. - Abstract: Photovoltaic and wind power generations are currently seen as sustainable options of in rural electrification, particularly in standalone applications. However the variable character of solar and wind resources as well as the variable load demand prevent these generation systems from being totally reliable without suitable energy storage system. Several research works have been conducted on the use of photovoltaic and wind systems in rural electrification; however most of these works have not considered other ways of storing energy except for conventional battery storage systems. In this paper, an energy dispatch model that satisfies the load demand, taking into account the intermittent nature of the solar and wind energy sources and variations in demand, is presented for a hybrid system consisting of a photovoltaic unit, a wind unit, a pumped hydro storage system and a diesel generator. The main purpose of the developed model is to minimize the hybrid system’s operation cost while optimizing the system’s power flow considering the different component’s operational constraints. The simulations have been performed using “fmincon” implemented in Matlab. The model have been applied to two test examples; the simulation results are analyzed and compared to the case where the diesel generator is used alone to supply the given load demand. The results show that using the developed control model for the proposed hybrid system, fuel saving can be achieved compared to the case where the diesel is used alone to supply the same load patters.

  7. Optimizing the Shunting Schedule of Electric Multiple Units Depot Using an Enhanced Particle Swarm Optimization Algorithm

    Directory of Open Access Journals (Sweden)

    Jiaxi Wang

    2016-01-01

    Full Text Available The shunting schedule of electric multiple units depot (SSED is one of the essential plans for high-speed train maintenance activities. This paper presents a 0-1 programming model to address the problem of determining an optimal SSED through automatic computing. The objective of the model is to minimize the number of shunting movements and the constraints include track occupation conflicts, shunting routes conflicts, time durations of maintenance processes, and shunting running time. An enhanced particle swarm optimization (EPSO algorithm is proposed to solve the optimization problem. Finally, an empirical study from Shanghai South EMU Depot is carried out to illustrate the model and EPSO algorithm. The optimization results indicate that the proposed method is valid for the SSED problem and that the EPSO algorithm outperforms the traditional PSO algorithm on the aspect of optimality.

  8. Optimal Scheduling of Doctors Outpatient Departments Based on Patients’ Behavior

    Directory of Open Access Journals (Sweden)

    Zongwei Ren

    2016-01-01

    Full Text Available The low operational efficiency in the field of medical and health care has become a serious problem in China; the long time that the patients have to wait for is the main phenomenon of difficult medical service. Medical industry is service-oriented and its main purpose is to make profits, so the benefits and competitiveness of a hospital depend on patient satisfaction. This paper makes a survey on a large hospital in Harbin of China and collects relevant data and then uses the prospect theory to analyze patients’ and doctors’ behavioral characteristics and the model of patient satisfaction is established based on fuzzy theory with a triplet α/β/γ. The optimal scheduling of clinic is described as a problem with the rule of first come, first served which maximizes patient satisfaction for the main goal and minimizes operating costs for the secondary goal. And the corresponding mathematical model is established. Finally, a solution method named plant growth simulation algorithm (PGSA is presented. Then, by means of calculating of the example and comparing with genetic algorithm, the results show that the optimum can be reached; meanwhile the efficiency of the presented algorithm is better than the genetic algorithm.

  9. Resource Allocation and Outpatient Appointment Scheduling Using Simulation Optimization

    Directory of Open Access Journals (Sweden)

    Carrie Ka Yuk Lin

    2017-01-01

    Full Text Available This paper studies the real-life problems of outpatient clinics having the multiple objectives of minimizing resource overtime, patient waiting time, and waiting area congestion. In the clinic, there are several patient classes, each of which follows different treatment procedure flow paths through a multiphase and multiserver queuing system with scarce staff and limited space. We incorporate the stochastic factors for the probabilities of the patients being diverted into different flow paths, patient punctuality, arrival times, procedure duration, and the number of accompanied visitors. We present a novel two-stage simulation-based heuristic algorithm to assess various tactical and operational decisions for optimizing the multiple objectives. In stage I, we search for a resource allocation plan, and in stage II, we determine a block appointment schedule by patient class and a service discipline for the daily operational level. We also explore the effects of the separate strategies and their integration to identify the best possible combination. The computational experiments are designed on the basis of data from a study of an ophthalmology clinic in a public hospital. Results show that our approach significantly mitigates the undesirable outcomes by integrating the strategies and increasing the resource flexibility at the bottleneck procedures without adding resources.

  10. Managing daily surgery schedules in a teaching hospital: a mixed-integer optimization approach.

    Science.gov (United States)

    Pulido, Raul; Aguirre, Adrian M; Ortega-Mier, Miguel; García-Sánchez, Álvaro; Méndez, Carlos A

    2014-10-15

    This study examined the daily surgical scheduling problem in a teaching hospital. This problem relates to the use of multiple operating rooms and different types of surgeons in a typical surgical day with deterministic operation durations (preincision, incision, and postincision times). Teaching hospitals play a key role in the health-care system; however, existing models assume that the duration of surgery is independent of the surgeon's skills. This problem has not been properly addressed in other studies. We analyze the case of a Spanish public hospital, in which continuous pressures and budgeting reductions entail the more efficient use of resources. To obtain an optimal solution for this problem, we developed a mixed-integer programming model and user-friendly interface that facilitate the scheduling of planned operations for the following surgical day. We also implemented a simulation model to assist the evaluation of different dispatching policies for surgeries and surgeons. The typical aspects we took into account were the type of surgeon, potential overtime, idling time of surgeons, and the use of operating rooms. It is necessary to consider the expertise of a given surgeon when formulating a schedule: such skill can decrease the probability of delays that could affect subsequent surgeries or cause cancellation of the final surgery. We obtained optimal solutions for a set of given instances, which we obtained through surgical information related to acceptable times collected from a Spanish public hospital. We developed a computer-aided framework with a user-friendly interface for use by a surgical manager that presents a 3-D simulation of the problem. Additionally, we obtained an efficient formulation for this complex problem. However, the spread of this kind of operation research in Spanish public health hospitals will take a long time since there is a lack of knowledge of the beneficial techniques and possibilities that operational research can offer for

  11. Remote optimal state estimation over communication channels with random delays

    KAUST Repository

    Mahmoud, Magdi S.

    2014-01-22

    This paper considers the optimal estimation of linear systems over unreliable communication channels with random delays. In this work, it is assumed that the system to be estimated is far away from the filter. The observations of the system are capsulized without time stamp and then transmitted to the network node at which the filter is located. The probabilities of time delays are assumed to be known. The event-driven estimation scheme is applied in this paper and the estimate of the states is updated only at each time instant when any measurement arrives. To capture the feature of communication, the system considered is augmented, and the arrived measurements are regarded as the uncertain observations of the augmented system. The corresponding optimal estimation algorithm is proposed and additionally, a numerical simulation represents the performance of this work. © 2014 The authors. Published by Oxford University Press on behalf of the Institute of Mathematics and its Applications. All rights reserved.

  12. An Optimal Static Scheduling Algorithm for Hard Real-Time Systems Specified in a Prototyping Language

    Science.gov (United States)

    1989-12-01

    Time Systems Specified in a Prototyping Language by Julian Jaime Cervantes Capitao Engenheiro, Forga A~rea Brasileira B.S., Instituto Tecnologico de...a dynamic scheduling algorithm progressively determines the schedule for tasks on-line. A scheduling algorithm is said to guarantee a newly arriving...by finding optimal subsequences for progressively larger modules, until all the tasks are sequenced. To guarantee optimality of such algorithms, the

  13. Online Algorithms for Adaptive Optimization in Heterogeneous Delay Tolerant Networks

    Directory of Open Access Journals (Sweden)

    Wissam Chahin

    2013-12-01

    Full Text Available Delay Tolerant Networks (DTNs are an emerging type of networks which do not need a predefined infrastructure. In fact, data forwarding in DTNs relies on the contacts among nodes which may possess different features, radio range, battery consumption and radio interfaces. On the other hand, efficient message delivery under limited resources, e.g., battery or storage, requires to optimize forwarding policies. We tackle optimal forwarding control for a DTN composed of nodes of different types, forming a so-called heterogeneous network. Using our model, we characterize the optimal policies and provide a suitable framework to design a new class of multi-dimensional stochastic approximation algorithms working for heterogeneous DTNs. Crucially, our proposed algorithms drive online the source node to the optimal operating point without requiring explicit estimation of network parameters. A thorough analysis of the convergence properties and stability of our algorithms is presented.

  14. Optimizing Air Transportation Service to Metroplex Airports. Par 2; Analysis Using the Airline Schedule Optimization Model (ASOM)

    Science.gov (United States)

    Donoue, George; Hoffman, Karla; Sherry, Lance; Ferguson, John; Kara, Abdul Qadar

    2010-01-01

    The air transportation system is a significant driver of the U.S. economy, providing safe, affordable, and rapid transportation. During the past three decades airspace and airport capacity has not grown in step with demand for air transportation; the failure to increase capacity at the same rate as the growth in demand results in unreliable service and systemic delay. This report describes the results of an analysis of airline strategic decision-making that affects geographic access, economic access, and airline finances, extending the analysis of these factors using historic data (from Part 1 of the report). The Airline Schedule Optimization Model (ASOM) was used to evaluate how exogenous factors (passenger demand, airline operating costs, and airport capacity limits) affect geographic access (markets-served, scheduled flights, aircraft size), economic access (airfares), airline finances (profit), and air transportation efficiency (aircraft size). This analysis captures the impact of the implementation of airport capacity limits, as well as the effect of increased hedged fuel prices, which serve as a proxy for increased costs per flight that might occur if auctions or congestion pricing are imposed; also incorporated are demand elasticity curves based on historical data that provide information about how passenger demand is affected by airfare changes.

  15. Optimization of Online Patient Scheduling with Urgencies and Preferences

    NARCIS (Netherlands)

    I.B. Vermeulen (Ivan); S.M. Bohte (Sander); P.A.N. Bosman (Peter); S.G. Elkhuizen; P.J.M. Bakker; J.A. La Poutré (Han); C. Combi; Y. Shahar; A. Abu-Hanna

    2009-01-01

    htmlabstractWe consider the online problem of scheduling patients with urgencies and preferences on hospital resources with limited capacity. To solve this complex scheduling problem effectively we have to address the following sub problems: determining the allocation of capacity to patient

  16. An interpolated activity during the knowledge-of-results delay interval eliminates the learning advantages of self-controlled feedback schedules.

    Science.gov (United States)

    Carter, Michael J; Ste-Marie, Diane M

    2017-03-01

    The learning advantages of self-controlled knowledge-of-results (KR) schedules compared to yoked schedules have been linked to the optimization of the informational value of the KR received for the enhancement of one's error-detection capabilities. This suggests that information-processing activities that occur after motor execution, but prior to receiving KR (i.e., the KR-delay interval) may underlie self-controlled KR learning advantages. The present experiment investigated whether self-controlled KR learning benefits would be eliminated if an interpolated activity was performed during the KR-delay interval. Participants practiced a waveform matching task that required two rapid elbow extension-flexion reversals in one of four groups using a factorial combination of choice (self-controlled, yoked) and KR-delay interval (empty, interpolated). The waveform had specific spatial and temporal constraints, and an overall movement time goal. The results indicated that the self-controlled + empty group had superior retention and transfer scores compared to all other groups. Moreover, the self-controlled + interpolated and yoked + interpolated groups did not differ significantly in retention and transfer; thus, the interpolated activity eliminated the typically found learning benefits of self-controlled KR. No significant differences were found between the two yoked groups. We suggest the interpolated activity interfered with information-processing activities specific to self-controlled KR conditions that occur during the KR-delay interval and that these activities are vital for reaping the associated learning benefits. These findings add to the growing evidence that challenge the motivational account of self-controlled KR learning advantages and instead highlights informational factors associated with the KR-delay interval as an important variable for motor learning under self-controlled KR schedules.

  17. Sleep/wake scheduling scheme for minimizing end-to-end delay in multi-hop wireless sensor networks

    Directory of Open Access Journals (Sweden)

    Madani Sajjad

    2011-01-01

    Full Text Available Abstract We present a sleep/wake schedule protocol for minimizing end-to-end delay for event driven multi-hop wireless sensor networks. In contrast to generic sleep/wake scheduling schemes, our proposed algorithm performs scheduling that is dependent on traffic loads. Nodes adapt their sleep/wake schedule based on traffic loads in response to three important factors, (a the distance of the node from the sink node, (b the importance of the node's location from connectivity's perspective, and (c if the node is in the proximity where an event occurs. Using these heuristics, the proposed scheme reduces end-to-end delay and maximizes the throughput by minimizing the congestion at nodes having heavy traffic load. Simulations are carried out to evaluate the performance of the proposed protocol, by comparing its performance with S-MAC and Anycast protocols. Simulation results demonstrate that the proposed protocol has significantly reduced the end-to-end delay, as well as has improved the other QoS parameters, like average energy per packet, average delay, packet loss ratio, throughput, and coverage lifetime.

  18. OPTIMIZED PARTICLE SWARM OPTIMIZATION BASED DEADLINE CONSTRAINED TASK SCHEDULING IN HYBRID CLOUD

    Directory of Open Access Journals (Sweden)

    Dhananjay Kumar

    2016-01-01

    Full Text Available Cloud Computing is a dominant way of sharing of computing resources that can be configured and provisioned easily. Task scheduling in Hybrid cloud is a challenge as it suffers from producing the best QoS (Quality of Service when there is a high demand. In this paper a new resource allocation algorithm, to find the best External Cloud provider when the intermediate provider’s resources aren’t enough to satisfy the customer’s demand is proposed. The proposed algorithm called Optimized Particle Swarm Optimization (OPSO combines the two metaheuristic algorithms namely Particle Swarm Optimization and Ant Colony Optimization (ACO. These metaheuristic algorithms are used for the purpose of optimization in the search space of the required solution, to find the best resource from the pool of resources and to obtain maximum profit even when the number of tasks submitted for execution is very high. This optimization is performed to allocate job requests to internal and external cloud providers to obtain maximum profit. It helps to improve the system performance by improving the CPU utilization, and handle multiple requests at the same time. The simulation result shows that an OPSO yields 0.1% - 5% profit to the intermediate cloud provider compared with standard PSO and ACO algorithms and it also increases the CPU utilization by 0.1%.

  19. Optimization of time–temperature schedule for nitridation of silicon ...

    Indian Academy of Sciences (India)

    weight gain. Green compact of density 66%, the nitridation schedule was maneuvered for complete nitridation. Iron promotes nitridation reaction. Higher weight loss during nitridation of iron doped compact is the main cause of lower ...

  20. Optimized Waterspace Management and Scheduling Using Mixed-Integer Linear Programming

    Science.gov (United States)

    2016-01-01

    simulations were performed using the IBM’s ILOG CPLEX optimization software [35]. All simulations were performed on a 2.8 GHz quad-core CPU equipped with...temporal schedule of the overall mission. The MILP optimization software was run with a cutoff time of 10 minutes for each optimization phase (Survey-RI, and...1 RI UUV 2 PMA Vehicle Schedule Dock Deploy Move Survey RI RI PMA Figure 5: Simulated MCM Schedule. Gantt chart represents the duration of each action

  1. Susceptibility of optimal train schedules to stochastic disturbances of process times

    DEFF Research Database (Denmark)

    Larsen, Rune; Pranzo, Marco; D’Ariano, Andrea

    2013-01-01

    This work focuses on the stochastic evaluation of train schedules computed by a microscopic scheduler of railway operations based on deterministic information. The research question is to assess the degree of sensitivity of various rescheduling algorithms to variations in process times (running...... and dwell times). In fact, the objective of railway traffic management is to reduce delay propagation and to increase disturbance robustness of train schedules at a network scale. We present a quantitative study of traffic disturbances and their effects on the schedules computed by simple and advanced...... rescheduling algorithms. Computational results are based on a complex and densely occupied Dutch railway area; train delays are computed based on accepted statistical distributions, and dwell and running times of trains are subject to additional stochastic variations. From the results obtained on a real case...

  2. Application-Oriented Optimal Shift Schedule Extraction for a Dual-Motor Electric Bus with Automated Manual Transmission

    Directory of Open Access Journals (Sweden)

    Mingjie Zhao

    2018-02-01

    Full Text Available The conventional battery electric buses (BEBs have limited potential to optimize the energy consumption and reach a better dynamic performance. A practical dual-motor equipped with 4-speed Automated Manual Transmission (AMT propulsion system is proposed, which can eliminate the traction interruption in conventional AMT. A discrete model of the dual-motor-AMT electric bus (DMAEB is built and used to optimize the gear shift schedule. Dynamic programming (DP algorithm is applied to find the optimal results where the efficiency and shift time of each gear are considered to handle the application problem of global optimization. A rational penalty factor and a proper shift time delay based on bench test results are set to reduce the shift frequency by 82.5% in Chinese-World Transient Vehicle Cycle (C-WTVC. Two perspectives of applicable shift rule extraction methods, i.e., the classification method based on optimal operating points and clustering method based on optimal shifting points, are explored and compared. Eventually, the hardware-in-the-loop (HIL simulation results demonstrate that the proposed structure and extracted shift schedule can realize a significant improvement in reducing energy loss by 20.13% compared to traditional empirical strategies.

  3. An Automated Tool for Optimizing Waste Transportation Routing and Scheduling

    International Nuclear Information System (INIS)

    Berry, L.E.; Branch, R.D.; White, H.A.; Whitehead, H. D. Jr.; Becker, B.D.

    2006-01-01

    An automated software tool has been developed and implemented to increase the efficiency and overall life-cycle productivity of site cleanup by scheduling vehicle and container movement between waste generators and disposal sites on the Department of Energy's Oak Ridge Reservation. The software tool identifies the best routes or accepts specifically requested routes and transit times, looks at fleet availability, selects the most cost effective route for each waste stream, and creates a transportation schedule in advance of waste movement. This tool was accepted by the customer and has been implemented. (authors)

  4. Contribution of Schedule Delays to Cost Growth: How to Make Peace with a Marching Army

    Science.gov (United States)

    Majerowicz, Walt; Bitten, Robert; Emmons, Debra; Shinn, Stephen A.

    2016-01-01

    Numerous research papers have shown that cost and schedule growth are interrelated for NASA space science missions. Although there has shown to be a strong correlation of cost growth with schedule growth, it is unclear what percentage of cost growth is caused by schedule growth and how schedule growth can be controlled. This paper attempts to quantify this percentage by looking at historical data and show detailed examples of how schedule growth influences cost growth. The paper also addresses a methodology to show an alternate approach for assessing and setting a robust baseline schedule and use schedule performance metrics to help assess if the project is performing to plan. Finally, recommendations are presented to help control schedule growth in order to minimize cost growth for NASA space science missions.

  5. Sensitivity of the optimal parameter settings for a LTE packet scheduler

    NARCIS (Netherlands)

    Fernandez-Diaz, I.; Litjens, R.; van den Berg, C.A.; Dimitrova, D.C.; Spaey, K.

    Advanced packet scheduling schemes in 3G/3G+ mobile networks provide one or more parameters to optimise the trade-off between QoS and resource efficiency. In this paper we study the sensitivity of the optimal parameter setting for packet scheduling in LTE radio networks with respect to various

  6. Optimal therapies of a virus replication model with pharmacological delays based on reverse transcriptase inhibitors and protease inhibitors

    International Nuclear Information System (INIS)

    Pei, Yongzhen; Li, Changguo; Liang, Xiyin

    2017-01-01

    A short delay in the pharmacological effect on account of the time required for drug absorption, distribution, and penetration into target cells after application of any anti-viral drug, is defined by the pharmacological delay (Herz et al 1996 Proc. Natl Acad. Sci. USA 93 7247–51). In this paper, a virus replication model with Beddington–DeAngelis incidence rate and the pharmacological and intracellular delays is presented to describe the treatment to cure the virus infection. The optimal controls represent the efficiency of reverse transcriptase inhibitors and protease inhibitors in suppressing viral production and prohibiting new infections. Due to the fact that both the control and state variables contain delays, we derive a necessary conditions for our optimal problem. Based on these results, numerical simulations are implemented not only to show the optimal therapeutic schedules for different infection and release rates, but also to compare the effective of three treatment programs. Furthermore, comparison of therapeutic effects under different maximum tolerable dosages is shown. Our research indicates that (1) the proper and specific treatment program should be determined according to the infection rates of different virus particles; (2) the optimal combined drug treatment is the most efficient; (3) the appropriate proportion of medicament must be formulated during the therapy due to the non-monotonic relationship between maximum tolerable dosages and therapeutic effects; (4) the therapeutic effect is advantageous when the pharmacological delay is considered. (paper)

  7. Optimal therapies of a virus replication model with pharmacological delays based on reverse transcriptase inhibitors and protease inhibitors

    Science.gov (United States)

    Pei, Yongzhen; Li, Changguo; Liang, Xiyin

    2017-11-01

    A short delay in the pharmacological effect on account of the time required for drug absorption, distribution, and penetration into target cells after application of any anti-viral drug, is defined by the pharmacological delay (Herz et al 1996 Proc. Natl Acad. Sci. USA 93 7247-51). In this paper, a virus replication model with Beddington-DeAngelis incidence rate and the pharmacological and intracellular delays is presented to describe the treatment to cure the virus infection. The optimal controls represent the efficiency of reverse transcriptase inhibitors and protease inhibitors in suppressing viral production and prohibiting new infections. Due to the fact that both the control and state variables contain delays, we derive a necessary conditions for our optimal problem. Based on these results, numerical simulations are implemented not only to show the optimal therapeutic schedules for different infection and release rates, but also to compare the effective of three treatment programs. Furthermore, comparison of therapeutic effects under different maximum tolerable dosages is shown. Our research indicates that (1) the proper and specific treatment program should be determined according to the infection rates of different virus particles; (2) the optimal combined drug treatment is the most efficient; (3) the appropriate proportion of medicament must be formulated during the therapy due to the non-monotonic relationship between maximum tolerable dosages and therapeutic effects; (4) the therapeutic effect is advantageous when the pharmacological delay is considered.

  8. customer-teller scheduling system for optimizing banks service

    African Journals Online (AJOL)

    due to idle times. On the other hand, good scheduling results in low waiting cost, good. Teller utilization, customer satisfaction, and more profit. Operations managers are faced with the problem of ... As service speeds up, time spent waiting on queue decreases. ... Nigerian Journal of Technology. Vol. 30, No. 1, March 2011.

  9. Military Free Fall Scheduling And Manifest Optimization Model

    Science.gov (United States)

    2016-12-01

    SEALs successfully conducted an MFF operation into Somalia to rescue American aid worker Jessica Buchanan and Danish aid worker Poul Thisted (Mazzetti...Since 2005, the Chilean Professional Soccer Association has used operations research techniques to schedule professional leagues in Chile . These

  10. Computing Optimal Schedules of Battery Usage in Embedded Systems

    NARCIS (Netherlands)

    Jongerden, M.R.; Mereacre, Alexandru; Bohnenkamp, H.C.; Haverkort, Boudewijn R.H.M.; Katoen, Joost P.

    2010-01-01

    The use of mobile devices is often limited by the battery lifetime. Some devices have the option to connect an extra battery, or to use smart battery-packs with multiple cells to extend the lifetime. In these cases, scheduling the batteries or battery cells over the load to exploit the recovery

  11. Scheduling with Optimized Communication for Time-Triggered Embedded Systems

    DEFF Research Database (Denmark)

    Pop, Paul; Eles, Petru; Peng, Zebo

    1999-01-01

    We present an approach to process scheduling for synthesis of safety-critical distributed embedded systems.Our system model captures both the flow of data and that of control. The communication model is based on a time-triggered protocol. We take into consideration overheads due to communication...

  12. Customer-Teller Scheduling System for Optimizing Banks Service ...

    African Journals Online (AJOL)

    Customer satisfaction is a concern to service industries as customers expect to be served promptly when they arrive. Demand for service is highly variable: depends on hour of the day, or day of the week, or even dates of the month. For a service industry like a Bank, there is a need for effcient Bank Teller scheduling system ...

  13. An integration of spreadsheet and project management software for cost optimal time scheduling in construction

    Directory of Open Access Journals (Sweden)

    Valenko Tadej

    2017-12-01

    Full Text Available Successful performance and completion of construction projects highly depend on an adequate time scheduling of the project activities. On implementation of time scheduling, the execution modes of activities are most often required to be set in a manner that enables in achieving the minimum total project cost. This paper presents an approach to cost optimal time scheduling, which integrates a spreadsheet application and data transfer to project management software (PMS. At this point, the optimization problem of project time scheduling is modelled employing Microsoft Excel and solved to optimality using Solver while organization of data is dealt by macros. Thereupon, Microsoft Project software is utilized for further managing and presentation of optimized time scheduling solution. In this way, the data flow between programs is automated and possibilities of error occurrence during scheduling process are reduced to a minimum. Moreover, integration of spreadsheet and PMS for cost optimal time scheduling in construction is performed within well-known program environment that increases the possibilities of its wider use in practice. An application example is shown in this paper to demonstrate the advantages of proposed approach.

  14. DAILY SCHEDULING OF SMALL HYDRO POWER PLANTS DISPATCH WITH MODIFIED PARTICLES SWARM OPTIMIZATION

    Directory of Open Access Journals (Sweden)

    Sinvaldo Rodrigues Moreno

    2015-04-01

    Full Text Available This paper presents a new approach for short-term hydro power scheduling of reservoirs using an algorithm-based Particle Swarm Optimization (PSO. PSO is a population-based algorithm designed to find good solutions to optimization problems, its characteristics have encouraged its adoption to tackle a variety of problems in different fields. In this paper the authors consider an optimization problem related to a daily scheduling of small hydro power dispatch. The goal is construct a feasible solution that maximize the cascade electricity production, following the environmental constraints and water balance. The paper proposes an improved Particle Swarm Optimization (PSO algorithm, which takes advantage of simplicity and facility of implementation. The algorithm was successfully applied to the optimization of the daily schedule strategies of small hydro power plants, considering maximum water utilization and all constraints related to simultaneous water uses. Extensive computational tests and comparisons with other heuristics methods showed the effectiveness of the proposed approach.

  15. Scheduling algorithm for data relay satellite optical communication based on artificial intelligent optimization

    Science.gov (United States)

    Zhao, Wei-hu; Zhao, Jing; Zhao, Shang-hong; Li, Yong-jun; Wang, Xiang; Dong, Yi; Dong, Chen

    2013-08-01

    Optical satellite communication with the advantages of broadband, large capacity and low power consuming broke the bottleneck of the traditional microwave satellite communication. The formation of the Space-based Information System with the technology of high performance optical inter-satellite communication and the realization of global seamless coverage and mobile terminal accessing are the necessary trend of the development of optical satellite communication. Considering the resources, missions and restraints of Data Relay Satellite Optical Communication System, a model of optical communication resources scheduling is established and a scheduling algorithm based on artificial intelligent optimization is put forwarded. According to the multi-relay-satellite, multi-user-satellite, multi-optical-antenna and multi-mission with several priority weights, the resources are scheduled reasonable by the operation: "Ascertain Current Mission Scheduling Time" and "Refresh Latter Mission Time-Window". The priority weight is considered as the parameter of the fitness function and the scheduling project is optimized by the Genetic Algorithm. The simulation scenarios including 3 relay satellites with 6 optical antennas, 12 user satellites and 30 missions, the simulation result reveals that the algorithm obtain satisfactory results in both efficiency and performance and resources scheduling model and the optimization algorithm are suitable in multi-relay-satellite, multi-user-satellite, and multi-optical-antenna recourses scheduling problem.

  16. Congestion game scheduling for virtual drug screening optimization

    Science.gov (United States)

    Nikitina, Natalia; Ivashko, Evgeny; Tchernykh, Andrei

    2018-02-01

    In virtual drug screening, the chemical diversity of hits is an important factor, along with their predicted activity. Moreover, interim results are of interest for directing the further research, and their diversity is also desirable. In this paper, we consider a problem of obtaining a diverse set of virtual screening hits in a short time. To this end, we propose a mathematical model of task scheduling for virtual drug screening in high-performance computational systems as a congestion game between computational nodes to find the equilibrium solutions for best balancing the number of interim hits with their chemical diversity. The model considers the heterogeneous environment with workload uncertainty, processing time uncertainty, and limited knowledge about the input dataset structure. We perform computational experiments and evaluate the performance of the developed approach considering organic molecules database GDB-9. The used set of molecules is rich enough to demonstrate the feasibility and practicability of proposed solutions. We compare the algorithm with two known heuristics used in practice and observe that game-based scheduling outperforms them by the hit discovery rate and chemical diversity at earlier steps. Based on these results, we use a social utility metric for assessing the efficiency of our equilibrium solutions and show that they reach greatest values.

  17. A Comparison between Fixed Priority and EDF Scheduling accounting for Cache Related Pre-emption Delays

    NARCIS (Netherlands)

    Lunniss, W.; Altmeyer, S.; Davis, R.I.

    2014-01-01

    In multitasking real-time systems, the choice of scheduling algorithm is an important factor to ensure that response time requirements are met while maximising limited system resources. Two popular scheduling algorithms include fixed priority (FP) and earliest deadline first (EDF). While they have

  18. Contracting, equal, and expanding learning schedules: the optimal distribution of learning sessions depends on retention interval.

    Science.gov (United States)

    Küpper-Tetzel, Carolina E; Kapler, Irina V; Wiseheart, Melody

    2014-07-01

    In laboratory and applied learning experiments, researchers have extensively investigated the optimal distribution of two learning sessions (i.e., initial learning and one relearning session) for the learning of verbatim materials. However, research has not yet provided a satisfying and conclusive answer to the optimal scheduling of three learning sessions (i.e., initial learning and two relearning sessions) across educationally relevant time intervals. Should the to-be-learned material be repeated at decreasing intervals (contracting schedule), constant intervals (equal schedule), or increasing intervals (expanding schedule) between learning sessions? Different theories and memory models (e.g., study-phase retrieval theory, contextual variability theory, ACT-R, and the Multiscale Context Model) make distinct predictions about the optimal learning schedule. We discuss the extant theories and derive clear predictions from each of them. To test these predictions empirically, we conducted an experiment in which participants studied and restudied paired associates with a contracting, equal, or expanding learning schedule. Memory performance was assessed immediately, 1 day, 7 days, or 35 days later with free- and cued-recall tests. Our results revealed that the optimal learning schedule is conditional on the length of the retention interval: A contracting learning schedule was beneficial for retention intervals up to 7 days, but both equal and expanding learning schedules were better for a long retention interval of 35 days. Our findings can be accommodated best by the contextual variability theory and indicate that revisions are needed to existing memory models. Our results are practically relevant, and their implications for real-world learning are discussed.

  19. An intelligent scheduling method based on improved particle swarm optimization algorithm for drainage pipe network

    Science.gov (United States)

    Luo, Yaqi; Zeng, Bi

    2017-08-01

    This paper researches the drainage routing problem in drainage pipe network, and propose an intelligent scheduling method. The method relates to the design of improved particle swarm optimization algorithm, the establishment of the corresponding model from the pipe network, and the process by using the algorithm based on improved particle swarm optimization to find the optimum drainage route in the current environment.

  20. Optimal Scheduling of a Multi-Carrier Energy Hub Supplemented By Battery Energy Storage Systems

    DEFF Research Database (Denmark)

    Javadi, Mohammad Sadegh; Anvari-Moghaddam, Amjad; Guerrero, Josep M.

    2017-01-01

    systems (ESSs), and heating/cooling devices such as electrical heater, heat-pumps and absorption chillers. The optimal scheduling and management of the examined energy hub assets in line with electrical transactions with distribution network is modeled as a mixed-integer non-linear optimization problem...

  1. Optimal Power Scheduling for a Grid-Connected Hybrid PV-Wind-Battery Microgrid System

    DEFF Research Database (Denmark)

    Hernández, Adriana Carolina Luna; Aldana, Nelson Leonardo Diaz; Savaghebi, Mehdi

    2016-01-01

    In this paper, a lineal mathematical model is proposed to schedule optimally the power references of the distributed energy resources in a grid-connected hybrid PVwind-battery microgrid. The optimization of the short term scheduling problem is addressed through a mixed-integer linear programming...... mathematical model, wherein the cost of energy purchased from the main grid is minimized and profits for selling energy generated by photovoltaic arrays are maximized by considering both physical constraints and requirements for a feasible deployment in the real system. The optimization model is tested...

  2. Geometric Distribution-Based Readers Scheduling Optimization Algorithm Using Artificial Immune System

    Directory of Open Access Journals (Sweden)

    Litian Duan

    2016-11-01

    Full Text Available In the multiple-reader environment (MRE of radio frequency identification (RFID system, multiple readers are often scheduled to interrogate the randomized tags via operating at different time slots or frequency channels to decrease the signal interferences. Based on this, a Geometric Distribution-based Multiple-reader Scheduling Optimization Algorithm using Artificial Immune System (GD-MRSOA-AIS is proposed to fairly and optimally schedule the readers operating from the viewpoint of resource allocations. GD-MRSOA-AIS is composed of two parts, where a geometric distribution function combined with the fairness consideration is first introduced to generate the feasible scheduling schemes for reader operation. After that, artificial immune system (including immune clone, immune mutation and immune suppression quickly optimize these feasible ones as the optimal scheduling scheme to ensure that readers are fairly operating with larger effective interrogation range and lower interferences. Compared with the state-of-the-art algorithm, the simulation results indicate that GD-MRSOA-AIS could efficiently schedules the multiple readers operating with a fairer resource allocation scheme, performing in larger effective interrogation range.

  3. A Human-in-the Loop Evaluation of a Coordinated Arrival Departure Scheduling Operations for Managing Departure Delays at LaGuardia Airport

    Science.gov (United States)

    Lee, Paul U.; Smith, Nancy M.; Bienert, Nancy; Brasil, Connie; Buckley, Nathan; Chevalley, Eric; Homola, Jeffrey; Omar, Faisal; Parke, Bonny; Yoo, Hyo-Sang

    2016-01-01

    LaGuardia (LGA) departure delay was identified by the stakeholders and subject matter experts as a significant bottleneck in the New York metropolitan area. Departure delay at LGA is primarily due to dependency between LGA's arrival and departure runways: LGA departures cannot begin takeoff until arrivals have cleared the runway intersection. If one-in one-out operations are not maintained and a significant arrival-to-departure imbalance occurs, the departure backup can persist through the rest of the day. At NASA Ames Research Center, a solution called "Departure-sensitive Arrival Spacing" (DSAS) was developed to maximize the departure throughput without creating significant delays in the arrival traffic. The concept leverages a Terminal Sequencing and Spacing (TSS) operations that create and manage the arrival schedule to the runway threshold and added an interface enhancement to the traffic manager's timeline to provide the ability to manually adjust inter-arrival spacing to build precise gaps for multiple departures between arrivals. A more complete solution would include a TSS algorithm enhancement that could automatically build these multi-departure gaps. With this set of capabilities, inter-arrival spacing could be controlled for optimal departure throughput. The concept was prototyped in a human-in-the- loop (HITL) simulation environment so that operational requirements such as coordination procedures, timing and magnitude of TSS schedule adjustments, and display features for Tower, TRACON and Traffic Management Unit could be determined. A HITL simulation was conducted in August 2014 to evaluate the concept in terms of feasibility, controller workload impact, and potential benefits. Three conditions were tested, namely a Baseline condition without scheduling, TSS condition that schedules the arrivals to the runway threshold, and TSS+DSAS condition that adjusts the arrival schedule to maximize the departure throughput. The results showed that during high

  4. A Novel Scheme for Optimal Control of a Nonlinear Delay Differential Equations Model to Determine Effective and Optimal Administrating Chemotherapy Agents in Breast Cancer.

    Science.gov (United States)

    Ramezanpour, H R; Setayeshi, S; Akbari, M E

    2011-01-01

    Determining the optimal and effective scheme for administrating the chemotherapy agents in breast cancer is the main goal of this scientific research. The most important issue here is the amount of drug or radiation administrated in chemotherapy and radiotherapy for increasing patient's survival. This is because in these cases, the therapy not only kills the tumor cells, but also kills some of the healthy tissues and causes serious damages. In this paper we investigate optimal drug scheduling effect for breast cancer model which consist of nonlinear ordinary differential time-delay equations. In this paper, a mathematical model of breast cancer tumors is discussed and then optimal control theory is applied to find out the optimal drug adjustment as an input control of system. Finally we use Sensitivity Approach (SA) to solve the optimal control problem. The goal of this paper is to determine optimal and effective scheme for administering the chemotherapy agent, so that the tumor is eradicated, while the immune systems remains above a suitable level. Simulation results confirm the effectiveness of our proposed procedure. In this paper a new scheme is proposed to design a therapy protocol for chemotherapy in Breast Cancer. In contrast to traditional pulse drug delivery, a continuous process is offered and optimized, according to the optimal control theory for time-delay systems.

  5. Trusted Service Scheduling and Optimization Strategy Design of Service Recommendation

    Directory of Open Access Journals (Sweden)

    Xiaona Xia

    2017-01-01

    Full Text Available More and more Web services raise the demands of personalized service recommendation; there exist some recommendation technologies, which improve the qualities of service recommendation by using service ranking and collaborative filtering. However, privacy and security are also important issues in service scheduling process; social relationships have been the key factors of interpersonal communication; service selection based on user preferences has become an inevitable trend. Starting from user demand preferences, this paper analyzes social topology and service demand information and obtains trusted social relationships; then we construct the fusion model of service historical preferences and potential ones; according to social service recommendation demands, TSRSR algorithm has completed designing. Through experiments, TSRSR algorithm is much better than the others, which can effectively improve potential preferences’ learning. Furthermore, the research results of this paper have more significance to study the security and privacy of service recommendation.

  6. Scheduling Internal Audit Activities: A Stochastic Combinatorial Optimization Problem

    NARCIS (Netherlands)

    Rossi, R.; Tarim, S.A.; Hnich, B.; Prestwich, S.; Karacaer, S.

    2010-01-01

    The problem of finding the optimal timing of audit activities within an organisation has been addressed by many researchers. We propose a stochastic programming formulation with Mixed Integer Linear Programming (MILP) and Constraint Programming (CP) certainty-equivalent models. In experiments

  7. optimal scheduling of petroleum products distribution in nigeria

    African Journals Online (AJOL)

    MECHANICAL ENGINEERING

    of varying supply from refineries and demand at storage depots. The optimal solution was ... demand point j. Dj. –. Demand point requirement j. DPK –. Dual purpose kerosene. MT. –. Metric tonne. NNPC –. Nigeria National. Petroleum Corporation. PMS –. Premium ..... “Supply and Distribution Planning. Support for Amoco ...

  8. Optimization of Multiperiod Mixed Train Schedule on High-Speed Railway

    Directory of Open Access Journals (Sweden)

    Wenliang Zhou

    2015-01-01

    Full Text Available For providing passengers with periodic operation trains and making trains’ time distribution better fit that of passengers, the multiperiod mixed train schedule is first proposed in this paper. It makes each type of train having same origin, destination, route, and stop stations operate based on a periodic basis and allows different types of train to have various operation periods. Then a model of optimizing multiperiod mixed train schedule is built to minimize passengers generalized travel costs with the constraints of trains of same type operating periodically, safe interval requirements of trains’ departure, and arrival times, and so forth. And its heuristic algorithm is designed to optimize the multiperiod mixed train schedule beginning with generating an initial solution by scheduling all types of train type by type and then repeatedly improving their periodic schedules until the objective value cannot be reduced or the iteration number reaches its maximum. Finally, example results illustrate that the proposed model and algorithm can effectively gain a better multiperiod mixed train schedule. However, its passengers deferred times and advanced times are a little higher than these of an aperiodic train schedule.

  9. Schedulability Analysis and Optimization for the Synthesis of Multi-Cluster Distributed Embedded Systems

    DEFF Research Database (Denmark)

    Pop, Paul; Eles, Petru; Peng, Zebo

    2003-01-01

    An approach to schedulability analysis for the synthesis of multi-cluster distributed embedded systems consisting of time-triggered and event-triggered clusters, interconnected via gateways, is presented. A buffer size and worst case queuing delay analysis for the gateways, responsible for routing...... inter-cluster traffic, is also proposed. Optimisation heuristics for the priority assignment and synthesis of bus access parameters aimed at producing a schedulable system with minimal buffer needs have been proposed. Extensive experiments and a real-life example show the efficiency of the approaches....

  10. Stochastic Optimization for Network-Constrained Power System Scheduling Problem

    Directory of Open Access Journals (Sweden)

    D. F. Teshome

    2015-01-01

    Full Text Available The stochastic nature of demand and wind generation has a considerable effect on solving the scheduling problem of a modern power system. Network constraints such as power flow equations and transmission capacities also need to be considered for a comprehensive approach to model renewable energy integration and analyze generation system flexibility. Firstly, this paper accounts for the stochastic inputs in such a way that the uncertainties are modeled as normally distributed forecast errors. The forecast errors are then superimposed on the outputs of load and wind forecasting tools. Secondly, it efficiently models the network constraints and tests an iterative algorithm and a piecewise linear approximation for representing transmission losses in mixed integer linear programming (MILP. It also integrates load shedding according to priority factors set by the system operator. Moreover, the different interactions among stochastic programming, network constraints, and prioritized load shedding are thoroughly investigated in the paper. The stochastic model is tested on a power system adopted from Jeju Island, South Korea. Results demonstrate the impact of wind speed variability and network constraints on the flexibility of the generation system. Further analysis shows the effect of loss modeling approaches on total cost, accuracy, computational time, and memory requirement.

  11. Optimal Electric Vehicle Scheduling: A Co-Optimized System and Customer Perspective

    Science.gov (United States)

    Maigha

    Electric vehicles provide a two pronged solution to the problems faced by the electricity and transportation sectors. They provide a green, highly efficient alternative to the internal combustion engine vehicles, thus reducing our dependence on fossil fuels. Secondly, they bear the potential of supporting the grid as energy storage devices while incentivising the customers through their participation in energy markets. Despite these advantages, widespread adoption of electric vehicles faces socio-technical and economic bottleneck. This dissertation seeks to provide solutions that balance system and customer objectives under present technological capabilities. The research uses electric vehicles as controllable loads and resources. The idea is to provide the customers with required tools to make an informed decision while considering the system conditions. First, a genetic algorithm based optimal charging strategy to reduce the impact of aggregated electric vehicle load has been presented. A Monte Carlo based solution strategy studies change in the solution under different objective functions. This day-ahead scheduling is then extended to real-time coordination using a moving-horizon approach. Further, battery degradation costs have been explored with vehicle-to-grid implementations, thus accounting for customer net-revenue and vehicle utility for grid support. A Pareto front, thus obtained, provides the nexus between customer and system desired operating points. Finally, we propose a transactive business model for a smart airport parking facility. This model identifies various revenue streams and satisfaction indices that benefit the parking lot owner and the customer, thus adding value to the electric vehicle.

  12. OPTIMAL WORK-REST SCHEDULE FOR COMPUTER USERS

    Directory of Open Access Journals (Sweden)

    Mervat Abdelrahman Mohamed

    2017-04-01

    Full Text Available Background: Musculoskeletal disorders are the most common health problems for computer users who work for an extended period. The aim of this study was to identify the best work-rest schedule with the three different work-rest groups: no rest break, mid-rest break, and multiple- rest breaks, which was associated with the least EMG activities of the upper trapezius muscle and would be beneficial for musculoskeletal health. Methods: Forty-five right-handed females complaining of neck discomfort were randomly assigned into three equal groups, Group1 (no rest break they were be engaged in sixty minutes of typing followed by ten minutes break (60-10, group 2 (mid-rest break thirty minutes of typing followed by five minutes break (30-5, and group 3 (multiple rest breaks fifteen minutes of typing followed by 2.5 minutes break (15-2.5. Surface EMG was used to pick up the electrical activity of right and left upper trapezius throughout the computer typing task. Results: There was a statistically significant reduction of normalized RMS (p<0.05 between the three groups for both right and left upper trapezius. Also, our results demonstrated a positive effect of mid and multiple rest breaks regarding reduced muscle activity in the upper trapezius muscle during a computer work. Conclusion: There is a positive effect of mid and multiple rest breaks regarding reduced muscle activity in the upper trapezius muscle throughout a computer work in subjects with neck and shoulder discomfort.

  13. Transition Delay in Hypersonic Boundary Layers via Optimal Perturbations

    Science.gov (United States)

    Paredes, Pedro; Choudhari, Meelan M.; Li, Fei

    2016-01-01

    The effect of nonlinear optimal streaks on disturbance growth in a Mach 6 axisymmetric flow over a 7deg half-angle cone is investigated in an e ort to expand the range of available techniques for transition control. Plane-marching parabolized stability equations are used to characterize the boundary layer instability in the presence of azimuthally periodic streaks. The streaks are observed to stabilize nominally planar Mack mode instabilities, although oblique Mack mode disturbances are destabilized. Experimentally measured transition onset in the absence of any streaks correlates with an amplification factor of N = 6 for the planar Mack modes. For high enough streak amplitudes, the transition threshold of N = 6 is not reached by the Mack mode instabilities within the length of the cone, but subharmonic first mode instabilities, which are destabilized by the presence of the streaks, reach N = 6 near the end of the cone. These results suggest a passive flow control strategy of using micro vortex generators to induce streaks that would delay transition in hypersonic boundary layers.

  14. Constructing optimized binary masks for reservoir computing with delay systems

    Science.gov (United States)

    Appeltant, Lennert; van der Sande, Guy; Danckaert, Jan; Fischer, Ingo

    2014-01-01

    Reservoir computing is a novel bio-inspired computing method, capable of solving complex tasks in a computationally efficient way. It has recently been successfully implemented using delayed feedback systems, allowing to reduce the hardware complexity of brain-inspired computers drastically. In this approach, the pre-processing procedure relies on the definition of a temporal mask which serves as a scaled time-mutiplexing of the input. Originally, random masks had been chosen, motivated by the random connectivity in reservoirs. This random generation can sometimes fail. Moreover, for hardware implementations random generation is not ideal due to its complexity and the requirement for trial and error. We outline a procedure to reliably construct an optimal mask pattern in terms of multipurpose performance, derived from the concept of maximum length sequences. Not only does this ensure the creation of the shortest possible mask that leads to maximum variability in the reservoir states for the given reservoir, it also allows for an interpretation of the statistical significance of the provided training samples for the task at hand.

  15. Necessary optimality conditions of the second oder in a stochastic optimal control problem with delay argument

    Directory of Open Access Journals (Sweden)

    Rashad O. Mastaliev

    2016-12-01

    Full Text Available The optimal control problem of nonlinear stochastic systems which mathematical model is given by Ito stochastic differential equation with delay argument is considered. Assuming that the concerned region is open for the control by the first and the second variation (classical sense of the quality functional we obtain the necessary optimality condition of the first and the second order. In the particular case we receive the stochastic analog of the Legendre—Clebsch condition and some constructively verified conclusions from the second order necessary condition. We investigate the Legendre–Clebsch conditions for the degeneration case and obtain the necessary conditions of optimality for a special control, in the classical sense.

  16. Simulated Stochastic Approximation Annealing for Global Optimization With a Square-Root Cooling Schedule

    KAUST Repository

    Liang, Faming

    2014-04-03

    Simulated annealing has been widely used in the solution of optimization problems. As known by many researchers, the global optima cannot be guaranteed to be located by simulated annealing unless a logarithmic cooling schedule is used. However, the logarithmic cooling schedule is so slow that no one can afford to use this much CPU time. This article proposes a new stochastic optimization algorithm, the so-called simulated stochastic approximation annealing algorithm, which is a combination of simulated annealing and the stochastic approximation Monte Carlo algorithm. Under the framework of stochastic approximation, it is shown that the new algorithm can work with a cooling schedule in which the temperature can decrease much faster than in the logarithmic cooling schedule, for example, a square-root cooling schedule, while guaranteeing the global optima to be reached when the temperature tends to zero. The new algorithm has been tested on a few benchmark optimization problems, including feed-forward neural network training and protein-folding. The numerical results indicate that the new algorithm can significantly outperform simulated annealing and other competitors. Supplementary materials for this article are available online.

  17. Scheduling delay in suspected cases of oral cancer Atraso de agendamento em casos suspeitos de câncer bucal

    Directory of Open Access Journals (Sweden)

    Luciana Meneses Souza

    2011-12-01

    Full Text Available The objective of the study was to evaluate scheduling delay of dental exams in the city of São Paulo of patients suspected of having oral cancer. A cross-sectional study was performed in which telephone conversations simulated clinical situations that represented two types of patients: one presenting symptoms suggestive of oral cancer (CA, and another one suggesting the need for prostheses (PR. The scheduling delay was evaluated by the days until an appointment for care; and among public offices, by type of schedule (emergency or routine. Negative binomial regression was used (95% statistical significance. Five hundred and seventy-five public and private dental offices participated in the study. The mean scheduling delay for the CA group was 2.88 days, and for the PR group, 4.34 days (p = 0.01. The mean scheduling delay was shorter in private dental offices (2.59 days than in offices that accepted health insurance (2.74 days (p = 0.01; the delay was shorter when performed by the dentist rather than by the dental assistant, 2.45 versus 4.21 days (p = 0.01. In public services, 69% of patients in the cancer group were sent to the emergency service. Dental services were accessible for scheduling clinical examinations among patients suspected of having oral cancer.O objetivo do estudo foi avaliar o atraso de agendamento de pacientes com suspeita de câncer bucal aos exames odontológicos na cidade de São Paulo. Realizou-se estudo transversal, em que conversações telefônicas simularam situações clínicas, representando dois tipos de pacientes-padrão: um com sintomas sugestivos de câncer bucal e outro com necessidade de prótese. O atraso do agendamento foi avaliado pelo tempo de agendamento para a consulta e, no caso de estabelecimentos públicos, pelo tipo de agendamento (rotina ou urgência. Utilizou-se regressão binomial negativa (95% de nível de significância. Participaram do estudo 575 estabelecimentos públicos e privados. O tempo m

  18. Optimizing the Steel Plate Storage Yard Crane Scheduling Problem Using a Two Stage Planning/Scheduling Approach

    DEFF Research Database (Denmark)

    Hansen, Anders Dohn; Clausen, Jens

    This paper presents the Steel Plate Storage Yard Crane Scheduling Problem. The task is to generate a schedule for two gantry cranes sharing tracks. The schedule must comply with a number of constraints and at the same time be cost efficient. We propose some ideas for a two stage planning/scheduli....../scheduling solution approach to the problem.......This paper presents the Steel Plate Storage Yard Crane Scheduling Problem. The task is to generate a schedule for two gantry cranes sharing tracks. The schedule must comply with a number of constraints and at the same time be cost efficient. We propose some ideas for a two stage planning...

  19. Optimal daily strategy scheduling for operation and sizing of power generating units

    International Nuclear Information System (INIS)

    Trashlieva, V.

    2012-01-01

    This paper deals with mixed integer programming application for elaborating an optimal schedule for power generation and operation so that the demand will be completely met with a minimum costs. An appropriate cost structure and different constraints are considered. A large scale optimization problem is formulated. The built in function for linear programming optimization is modified so the mixed-integer problem is successfully solved using the branch and bound technique. A specific Graphical User Interface for data input, problem solving and results representation is developed. This application offers a convenient tool for Matlab optimization features utilization. (Author)

  20. Operational Excellence through Schedule Optimization and Production Simulation of Application Specific Integrated Circuits.

    Energy Technology Data Exchange (ETDEWEB)

    Flory, John Andrew [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Padilla, Denise D. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Gauthier, John H. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Zwerneman, April Marie [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Miller, Steven P [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2016-05-01

    Upcoming weapon programs require an aggressive increase in Application Specific Integrated Circuit (ASIC) production at Sandia National Laboratories (SNL). SNL has developed unique modeling and optimization tools that have been instrumental in improving ASIC production productivity and efficiency, identifying optimal operational and tactical execution plans under resource constraints, and providing confidence in successful mission execution. With ten products and unprecedented levels of demand, a single set of shared resources, highly variable processes, and the need for external supplier task synchronization, scheduling is an integral part of successful manufacturing. The scheduler uses an iterative multi-objective genetic algorithm and a multi-dimensional performance evaluator. Schedule feasibility is assessed using a discrete event simulation (DES) that incorporates operational uncertainty, variability, and resource availability. The tools provide rapid scenario assessments and responses to variances in the operational environment, and have been used to inform major equipment investments and workforce planning decisions in multiple SNL facilities.

  1. Discrete Optimization Model for Vehicle Routing Problem with Scheduling Side Cosntraints

    Science.gov (United States)

    Juliandri, Dedy; Mawengkang, Herman; Bu'ulolo, F.

    2018-01-01

    Vehicle Routing Problem (VRP) is an important element of many logistic systems which involve routing and scheduling of vehicles from a depot to a set of customers node. This is a hard combinatorial optimization problem with the objective to find an optimal set of routes used by a fleet of vehicles to serve the demands a set of customers It is required that these vehicles return to the depot after serving customers’ demand. The problem incorporates time windows, fleet and driver scheduling, pick-up and delivery in the planning horizon. The goal is to determine the scheduling of fleet and driver and routing policies of the vehicles. The objective is to minimize the overall costs of all routes over the planning horizon. We model the problem as a linear mixed integer program. We develop a combination of heuristics and exact method for solving the model.

  2. Optimal trajectory planning and train scheduling for urban rail transit systems

    CERN Document Server

    Wang, Yihui; van den Boom, Ton; De Schutter, Bart

    2016-01-01

    This book contributes to making urban rail transport fast, punctual and energy-efficient –significant factors in the importance of public transportation systems to economic, environmental and social requirements at both municipal and national levels. It proposes new methods for shortening passenger travel times and for reducing energy consumption, addressing two major topics: (1) train trajectory planning: the authors derive a nonlinear model for the operation of trains and present several approaches for calculating optimal and energy-efficient trajectories within a given schedule; and (2) train scheduling: the authors develop a train scheduling model for urban rail systems and optimization approaches with which to balance total passenger travel time with energy efficiency and other costs to the operator. Mixed-integer linear programming and pseudospectral methods are among the new methods proposed for single- and multi-train systems for the solution of the nonlinear trajectory planning problem which involv...

  3. Cost Minimization for Joint Energy Management and Production Scheduling Using Particle Swarm Optimization

    Science.gov (United States)

    Shah, Rahul H.

    Production costs account for the largest share of the overall cost of manufacturing facilities. With the U.S. industrial sector becoming more and more competitive, manufacturers are looking for more cost and resource efficient working practices. Operations management and production planning have shown their capability to dramatically reduce manufacturing costs and increase system robustness. When implementing operations related decision making and planning, two fields that have shown to be most effective are maintenance and energy. Unfortunately, the current research that integrates both is limited. Additionally, these studies fail to consider parameter domains and optimization on joint energy and maintenance driven production planning. Accordingly, production planning methodology that considers maintenance and energy is investigated. Two models are presented to achieve well-rounded operating strategy. The first is a joint energy and maintenance production scheduling model. The second is a cost per part model considering maintenance, energy, and production. The proposed methodology will involve a Time-of-Use electricity demand response program, buffer and holding capacity, station reliability, production rate, station rated power, and more. In practice, the scheduling problem can be used to determine a joint energy, maintenance, and production schedule. Meanwhile, the cost per part model can be used to: (1) test the sensitivity of the obtained optimal production schedule and its corresponding savings by varying key production system parameters; and (2) to determine optimal system parameter combinations when using the joint energy, maintenance, and production planning model. Additionally, a factor analysis on the system parameters is conducted and the corresponding performance of the production schedule under variable parameter conditions, is evaluated. Also, parameter optimization guidelines that incorporate maintenance and energy parameter decision making in the

  4. Path Planning and Vehicle Scheduling Optimization for Logistic Distribution of Hazardous Materials in Full Container Load

    OpenAIRE

    Huo Chai; Ruichun He; Changxi Ma; Cunjie Dai; Kun Zhou

    2017-01-01

    Mathematical models for path planning and vehicle scheduling for logistic distribution of hazardous materials in full container load (FCL) are established, with their problem-solving methods proposed. First, a two-stage multiobjective optimization algorithm is designed for path planning. In the first stage, pulse algorithm is used to obtain the Pareto paths from the distribution center to each destination. In the second stage, a multiobjective optimization method based on Nondominated Sorting...

  5. Optimizing Intermodal Train Schedules with a Design Balanced Network Design Model

    DEFF Research Database (Denmark)

    Pedersen, Michael Berliner; Crainic, Teodor Gabriel

    We present a modeling approach for optimizing intermodal trains schedules based on an infrastructure divided into time-dependent train paths. The formulation can be generalized to a capacitated multi commodity network design model with additional design balance constraints. We present a Tabu Search...

  6. Optimization of Temperature Schedule Parameters on Heat Supply in Power-and-Heat Supply Systems

    Directory of Open Access Journals (Sweden)

    V. A. Sednin

    2009-01-01

    Full Text Available The paper considers problems concerning optimization of a temperature schedule in the district heating systems with steam-turbine thermal power stations having average initial steam parameters. It has been shown in the paper that upkeeping of an optimum network water temperature permits to increase an energy efficiency of heat supply due to additional systematic saving of fuel. 

  7. Optimal routes scheduling for municipal waste disposal garbage trucks using evolutionary algorithm and artificial immune system

    Directory of Open Access Journals (Sweden)

    Bogna MRÓWCZYŃSKA

    2011-01-01

    Full Text Available This paper describes an application of an evolutionary algorithm and an artificial immune systems to solve a problem of scheduling an optimal route for waste disposal garbage trucks in its daily operation. Problem of an optimisation is formulated and solved using both methods. The results are presented for an area in one of the Polish cities.

  8. Robust Optimization-Based Generation Self-Scheduling under Uncertain Price

    Directory of Open Access Journals (Sweden)

    Xiao Luo

    2011-01-01

    Full Text Available This paper considers generation self-scheduling in electricity markets under uncertain price. Based on the robust optimization (denoted as RO methodology, a new self-scheduling model, which has a complicated max-min optimization structure, is set up. By using optimal dual theory, the proposed model is reformulated to an ordinary quadratic and quadratic cone programming problems in the cases of box and ellipsoidal uncertainty, respectively. IEEE 30-bus system is used to test the new model. Some comparisons with other methods are done, and the sensitivity with respect to the uncertain set is analyzed. Comparing with the existed uncertain self-scheduling approaches, the new method has twofold characteristics. First, it does not need a prediction of distribution of random variables and just requires an estimated value and the uncertain set of power price. Second, the counterpart of RO corresponding to the self-scheduling is a simple quadratic or quadratic cone programming. This indicates that the reformulated problem can be solved by many ordinary optimization algorithms.

  9. Optimal joint scheduling of electrical and thermal appliances in a smart home environment

    International Nuclear Information System (INIS)

    Shirazi, Elham; Zakariazadeh, Alireza; Jadid, Shahram

    2015-01-01

    Highlights: • Thermal appliances are scheduled based on desired temperature and energy prices. • A discomfort index has been introduced within the home energy scheduling model. • Appliances are scheduled based on activity probability and desired options. • Starting probability depends on the social random factor and consumption behavior. - Abstract: With the development of home area network, residents have the opportunity to schedule their power usage in the home by themselves aiming at reducing electricity expenses. Moreover, as renewable energy sources are deployed in home, a home energy management system needs to consider both energy consumption and generation simultaneously to minimize the energy cost. In this paper, a smart home energy management model has been presented in which electrical and thermal appliances are jointly scheduled. The proposed method aims at minimizing the electricity cost of a residential customer by scheduling various type of appliances considering the residents consumption behavior, seasonal probability, social random factor, discomfort index and appliances starting probability functions. In this model, the home central controller receives the electricity price information, environmental factors data as well as the resident desired options in order to optimally schedule appliances including electrical and thermal. The scheduling approach is tested on a typical home including variety of home appliances, a small wind turbine, photovoltaic panel, combined heat and power unit, boiler and electrical and thermal storages over a 24-h period. The results show that the scheduling of different appliances can be reached simultaneously by using the proposed formulation. Moreover, simulation results evidenced that the proposed home energy management model exhibits a lower cost and, therefore, is more economical.

  10. Risk-Based, genetic algorithm approach to optimize outage maintenance schedule

    International Nuclear Information System (INIS)

    Hadavi, S. Mohammad Hadi

    2008-01-01

    A huge number of components are typically scheduled for maintenance when a nuclear power plant is shut down for its planned outage. Among these components, a number of them are risk significant so that their operability as well as reliability is of prime concern. Lack of proper maintenance for such components during the outage would impose substantial risk on the nuclear power plant (NPP) operation. In this paper, a new approach based on genetic algorithm (GA) is presented for the optimization of the NPP maintenance schedule during plant outage/overhaul, and an optimizer is developed accordingly. The developed optimizer, coupled with the suggested risk-cost model, compromises the cost in favor of maintaining the risk imposed by each schedule below regulatory/industry set limits. The suggested cost model consists of two elements, one considering the cost incurred by maintenance activities and the other incorporating the loss of revenues if needed, but unscheduled component maintenance causes further plant shutdown. The optimizer is developed in such a way that any risk and/or cost models the user desires can be applied. The performance of the developed GA/optimizer is evaluated by comparing its predictions with Monte Carlo simulation results. It is shown that the GA/optimizer performs significantly better

  11. Mix-oriented manufacturing control (MOMC): a quasi-optimal procedure for dynamic scheduling control

    Science.gov (United States)

    Cristofari, Marco; Caron, Franco; McDuffie, Ernest L.

    1997-12-01

    The total system throughput (ST) is one of the most important decision variables at the planning/scheduling phase of a manufacturing system. Material requirement planning (MRP) and master production schedule (MPS) are based on the assumption that ST is known. All the subsequent developments (e.g. jobs- release, system work-load, input-product mix, etc.) depends on such an assumption. If this assumption is incorrect, the production activity control (PAC) will not be able to satisfy the planned targets during the scheduling phase. Delays and bottlenecks will be unavoidable in the system. In case of random flexible manufacturing system (FMS) (or, in general, job-shop production), the measure of ST can not be evaluated a priori without running simulations or observing the actual flow of the operations in the system. The way entities enter the system (sequencing and percentage of the input products) effects the value of ST in such a way that estimation based on historical data are highly risky. The methodology proposed in this paper allows the scheduler to assess the analytical functions which link ST, and other output performance variables, to the input product mix (IPM). This way the robustness of the scheduling plan can be verified before the actual release of the jobs into the system.

  12. Optimal power system generation scheduling by multi-objective genetic algorithms with preferences

    International Nuclear Information System (INIS)

    Zio, E.; Baraldi, P.; Pedroni, N.

    2009-01-01

    Power system generation scheduling is an important issue both from the economical and environmental safety viewpoints. The scheduling involves decisions with regards to the units start-up and shut-down times and to the assignment of the load demands to the committed generating units for minimizing the system operation costs and the emission of atmospheric pollutants. As many other real-world engineering problems, power system generation scheduling involves multiple, conflicting optimization criteria for which there exists no single best solution with respect to all criteria considered. Multi-objective optimization algorithms, based on the principle of Pareto optimality, can then be designed to search for the set of nondominated scheduling solutions from which the decision-maker (DM) must a posteriori choose the preferred alternative. On the other hand, often, information is available a priori regarding the preference values of the DM with respect to the objectives. When possible, it is important to exploit this information during the search so as to focus it on the region of preference of the Pareto-optimal set. In this paper, ways are explored to use this preference information for driving a multi-objective genetic algorithm towards the preferential region of the Pareto-optimal front. Two methods are considered: the first one extends the concept of Pareto dominance by biasing the chromosome replacement step of the algorithm by means of numerical weights that express the DM' s preferences; the second one drives the search algorithm by changing the shape of the dominance region according to linear trade-off functions specified by the DM. The effectiveness of the proposed approaches is first compared on a case study of literature. Then, a nonlinear, constrained, two-objective power generation scheduling problem is effectively tackled

  13. A feasibility study: Selection of a personalized radiotherapy fractionation schedule using spatiotemporal optimization

    International Nuclear Information System (INIS)

    Kim, Minsun; Stewart, Robert D.; Phillips, Mark H.

    2015-01-01

    Purpose: To investigate the impact of using spatiotemporal optimization, i.e., intensity-modulated spatial optimization followed by fractionation schedule optimization, to select the patient-specific fractionation schedule that maximizes the tumor biologically equivalent dose (BED) under dose constraints for multiple organs-at-risk (OARs). Methods: Spatiotemporal optimization was applied to a variety of lung tumors in a phantom geometry using a range of tumor sizes and locations. The optimal fractionation schedule for a patient using the linear-quadratic cell survival model depends on the tumor and OAR sensitivity to fraction size (α/β), the effective tumor doubling time (T d ), and the size and location of tumor target relative to one or more OARs (dose distribution). The authors used a spatiotemporal optimization method to identify the optimal number of fractions N that maximizes the 3D tumor BED distribution for 16 lung phantom cases. The selection of the optimal fractionation schedule used equivalent (30-fraction) OAR constraints for the heart (D mean ≤ 45 Gy), lungs (D mean ≤ 20 Gy), cord (D max ≤ 45 Gy), esophagus (D max ≤ 63 Gy), and unspecified tissues (D 05 ≤ 60 Gy). To assess plan quality, the authors compared the minimum, mean, maximum, and D 95 of tumor BED, as well as the equivalent uniform dose (EUD) for optimized plans to conventional intensity-modulated radiation therapy plans prescribing 60 Gy in 30 fractions. A sensitivity analysis was performed to assess the effects of T d (3–100 days), tumor lag-time (T k = 0–10 days), and the size of tumors on optimal fractionation schedule. Results: Using an α/β ratio of 10 Gy, the average values of tumor max, min, mean BED, and D 95 were up to 19%, 21%, 20%, and 19% larger than those from conventional prescription, depending on T d and T k used. Tumor EUD was up to 17% larger than the conventional prescription. For fast proliferating tumors with T d less than 10 days, there was no

  14. Scheduling of multi load AGVs in FMS by modified memetic particle swarm optimization algorithm

    Directory of Open Access Journals (Sweden)

    V.K. Chawla

    2018-01-01

    Full Text Available Use of Automated guided vehicles (AGVs is highly significant in Flexible Manufacturing Sys-tem (FMS in which material handling in form of jobs is performed from one work center to an-other work center. A multifold increase in through put of FMS can be observed by application of multi load AGVs. In this paper, Particle Swarm Optimization (PSO integrated with Memetic Algorithm (MA named as Modified Memetic Particle Swarm Optimization Algorithm (MMP-SO is applied to yield initial feasible solutions for scheduling of multi load AGVs for minimum travel and waiting time in the FMS. The proposed MMPSO algorithm exhibits balanced explora-tion and exploitation for global search method of standard Particle Swarm Optimization (PSO algorithm and local search method of Memetic Algorithm (MA which further results into yield of efficient and effective initial feasible solutions for the multi load AGVs scheduling problem.

  15. Optimization of Time Structures in Manufacturing Management by using Scheduling Software Lekin

    Directory of Open Access Journals (Sweden)

    Michal Balog

    2016-08-01

    Full Text Available In each manufacturing plant it is one of the basic requirements to produce the largest quantity of products in the shortest time and at the lowest price. In performance of these requirements used are diverse modern methods, technologies and software which ensure the efficiency improvement of manufacturing, costs minimization, production time minimization etc. Presented article is focused on time structures optimization of real manufacturing process of engineering component by using scheduling software Lekin. It is based on theoretical scientific knowledge on which is afterwards found the optimal layout of the manufacturing process in practice. The optimal layout it created by construction and analysis of Gantt charts in scheduling software Lekin with minimum production time condition.

  16. Optimal treatment scheduling of ionizing radiation and sunitinib improves the antitumor activity and allows dose reduction

    International Nuclear Information System (INIS)

    Kleibeuker, Esther A; Hooven, Matthijs A ten; Castricum, Kitty C; Honeywell, Richard; Griffioen, Arjan W; Verheul, Henk M; Slotman, Ben J; Thijssen, Victor L

    2015-01-01

    The combination of radiotherapy with sunitinib is clinically hampered by rare but severe side effects and varying results with respect to clinical benefit. We studied different scheduling regimes and dose reduction in sunitinib and radiotherapy in preclinical tumor models to improve potential outcome of this combination treatment strategy. The chicken chorioallantoic membrane (CAM) was used as an angiogenesis in vivo model and as a xenograft model with human tumor cells (HT29 colorectal adenocarcinoma, OE19 esophageal adenocarcinoma). Treatment consisted of ionizing radiation (IR) and sunitinib as single therapy or in combination, using different dose-scheduling regimes. Sunitinib potentiated the inhibitory effect of IR (4 Gy) on angiogenesis. In addition, IR (4 Gy) and sunitinib (4 days of 32.5 mg/kg per day) inhibited tumor growth. Ionizing radiation induced tumor cell apoptosis and reduced proliferation, whereas sunitinib decreased tumor angiogenesis and reduced tumor cell proliferation. When IR was applied before sunitinib, this almost completely inhibited tumor growth, whereas concurrent IR was less effective and IR after sunitinib had no additional effect on tumor growth. Moreover, optimal scheduling allowed a 50% dose reduction in sunitinib while maintaining comparable antitumor effects. This study shows that the therapeutic efficacy of combination therapy improves when proper dose-scheduling is applied. More importantly, optimal treatment regimes permit dose reductions in the angiogenesis inhibitor, which will likely reduce the side effects of combination therapy in the clinical setting. Our study provides important leads to optimize combination treatment in the clinical setting

  17. A DAG Scheduling Scheme on Heterogeneous Computing Systems Using Tuple-Based Chemical Reaction Optimization

    Science.gov (United States)

    Jiang, Yuyi; Shao, Zhiqing; Guo, Yi

    2014-01-01

    A complex computing problem can be solved efficiently on a system with multiple computing nodes by dividing its implementation code into several parallel processing modules or tasks that can be formulated as directed acyclic graph (DAG) problems. The DAG jobs may be mapped to and scheduled on the computing nodes to minimize the total execution time. Searching an optimal DAG scheduling solution is considered to be NP-complete. This paper proposed a tuple molecular structure-based chemical reaction optimization (TMSCRO) method for DAG scheduling on heterogeneous computing systems, based on a very recently proposed metaheuristic method, chemical reaction optimization (CRO). Comparing with other CRO-based algorithms for DAG scheduling, the design of tuple reaction molecular structure and four elementary reaction operators of TMSCRO is more reasonable. TMSCRO also applies the concept of constrained critical paths (CCPs), constrained-critical-path directed acyclic graph (CCPDAG) and super molecule for accelerating convergence. In this paper, we have also conducted simulation experiments to verify the effectiveness and efficiency of TMSCRO upon a large set of randomly generated graphs and the graphs for real world problems. PMID:25143977

  18. Analysis and optimization of RC delay in vertical nanoplate FET

    Science.gov (United States)

    Woo, Changbeom; Ko, Kyul; Kim, Jongsu; Kim, Minsoo; Kang, Myounggon; Shin, Hyungcheol

    2017-10-01

    In this paper, we have analyzed short channel effects (SCEs) and RC delay with Vertical nanoplate FET (VNFET) using 3-D Technology computer-aided design (TCAD) simulation. The device is based on International Technology Road-map for Semiconductor (ITRS) 2013 recommendations, and it has initially gate length (LG) of 12.2 nm, channel thickness (Tch) of 4 nm, and spacer length (LSD) of 6 nm. To obtain improved performance by reducing RC delay, each dimension is adjusted (LG = 12.2 nm, Tch = 6 nm, LSD = 11.9 nm). It has each characteristic in this dimension (Ion/Ioff = 1.64 × 105, Subthreshold swing (S.S.) = 73 mV/dec, Drain-induced barrier lowering (DIBL) = 60 mV/V, and RC delay = 0.214 ps). Furthermore, with long shallow trench isolation (STI) length and thick insulator thickness (Ti), we can reduce RC delay from 0.214 ps to 0.163 ps. It is about a 23.8% reduction. Without decreasing drain current, there is a reduction of RC delay as reducing outer fringing capacitance (Cof). Finally, when source/drain spacer length is set to be different, we have verified RC delay to be optimum.

  19. System and method for optimal load and source scheduling in context aware homes

    Energy Technology Data Exchange (ETDEWEB)

    Shetty, Pradeep; Foslien Graber, Wendy; Mangsuli, Purnaprajna R.; Kolavennu, Soumitri N.; Curtner, Keith L.

    2018-01-23

    A controller for controlling energy consumption in a home includes a constraints engine to define variables for multiple appliances in the home corresponding to various home modes and persona of an occupant of the home. A modeling engine models multiple paths of energy utilization of the multiple appliances to place the home into a desired state from a current context. An optimal scheduler receives the multiple paths of energy utilization and generates a schedule as a function of the multiple paths and a selected persona to place the home in a desired state.

  20. Maximization of a nuclear system availability through maintenance scheduling optimization using a genetic algorithm

    International Nuclear Information System (INIS)

    Lapa, C.M.F.; Pereira, C.M.N.A.; Mol, A.C.D.A.

    2000-01-01

    In this paper, a method for preventive maintenance scheduling optimization of standby systems, based on genetic algorithm and probabilistic safety analysis, is described. The goal of this approach is to improve the average availability of the system through the optimization of the preventive maintenance policy. Here, the genetic modeling propitiates unconstrained optimization, allowing nonconstant intervals between maintenance, adapting them to the aging parameter of the Weibull distribution used. In order to demonstrate the effectiveness of the proposed method, it is applied to a nuclear system of a two-loop pressurized water reactor. The results, when compared with those obtained by some standard maintenance policies, reveal gains at safety level. (orig.)

  1. Optimal Scheduling for Retrieval Jobs in Double-Deep AS/RS by Evolutionary Algorithms

    Directory of Open Access Journals (Sweden)

    Kuo-Yang Wu

    2013-01-01

    Full Text Available We investigate the optimal scheduling of retrieval jobs for double-deep type Automated Storage and Retrieval Systems (AS/RS in the Flexible Manufacturing System (FMS used in modern industrial production. Three types of evolutionary algorithms, the Genetic Algorithm (GA, the Immune Genetic Algorithm (IGA, and the Particle Swarm Optimization (PSO algorithm, are implemented to obtain the optimal assignments. The objective is to minimize the working distance, that is, the shortest retrieval time travelled by the Storage and Retrieval (S/R machine. Simulation results and comparisons show the advantages and feasibility of the proposed methods.

  2. Joint Scheduling Optimization of Virtual Power Plants and Equitable Profit Distribution Using Shapely Value Theory

    Directory of Open Access Journals (Sweden)

    Zhong-fu Tan

    2018-01-01

    Full Text Available The installation capacity of wind and solar photovoltaic power is continually increasing, which makes renewable energy grid connection and power generation an important link of China’s power structure optimization. A virtual power plant (VPP is an important way to help distributed energy resource grid connection and promote renewable energy industry development. To study the economic scheduling problem of various distributed energy resources and the profit distribution problem of VPP alliance, this study builds a separate operation scheduling model for individual VPP and a joint operation scheduling model for VPP alliance, as well as the profit distribution model. The case study verifies the feasibility and effectiveness of the proposed model. The sensitivity analysis provides information about VPP decision-making in accordance with the policy environment development trend.

  3. Optimization of operating schedule of machines in granite industry using evolutionary algorithms

    International Nuclear Information System (INIS)

    Loganthurai, P.; Rajasekaran, V.; Gnanambal, K.

    2014-01-01

    Highlights: • Operating time of machines in granite industries was studied. • Operating time has been optimized using evolutionary algorithms such as PSO, DE. • The maximum demand has been reduced. • Hence the electricity cost of the industry and feeder stress have been reduced. - Abstract: Electrical energy consumption cost plays an important role in the production cost of any industry. The electrical energy consumption cost is calculated as two part tariff, the first part is maximum demand cost and the second part is energy consumption cost or unit cost (kW h). The maximum demand cost can be reduced without affecting the production. This paper focuses on the reduction of maximum demand by proper operating schedule of major equipments. For this analysis, various granite industries are considered. The major equipments in granite industries are cutting machine, polishing machine and compressor. To reduce the maximum demand, the operating time of polishing machine is rescheduled by optimization techniques such as Differential Evolution (DE) and particle swarm optimization (PSO). The maximum demand costs are calculated before and after rescheduling. The results show that if the machines are optimally operated, the cost is reduced. Both DE and PSO algorithms reduce the maximum demand cost at the same rate for all the granite industries. However, the optimum scheduling obtained by DE reduces the feeder power flow than the PSO scheduling

  4. Preventive maintenance optimization for a multi-component system under changing job shop schedule

    International Nuclear Information System (INIS)

    Zhou Xiaojun; Lu Zhiqiang; Xi Lifeng

    2012-01-01

    Variability and small lot size is a common feature for many discrete manufacturing processes designed to meet a wide array of customer needs. Because of this, job shop schedule often has to be continuously updated in reaction to changes in production plan. Generally, the aim of preventive maintenance is to ensure production effectiveness and therefore the preventive maintenance models must have the ability to be adaptive to changes in job shop schedule. In this paper, a dynamic opportunistic preventive maintenance model is developed for a multi-component system with considering changes in job shop schedule. Whenever a job is completed, preventive maintenance opportunities arise for all the components in the system. An optimal maintenance practice is dynamically determined by maximizing the short-term cumulative opportunistic maintenance cost savings for the system. The numerical example shows that the scheme obtained by the proposed model can effectively address the preventive maintenance scheduling problem caused by the changes in job shop schedule and is more efficient than the ones based on two other commonly used preventive maintenance models.

  5. Path Planning and Vehicle Scheduling Optimization for Logistic Distribution of Hazardous Materials in Full Container Load

    Directory of Open Access Journals (Sweden)

    Huo Chai

    2017-01-01

    Full Text Available Mathematical models for path planning and vehicle scheduling for logistic distribution of hazardous materials in full container load (FCL are established, with their problem-solving methods proposed. First, a two-stage multiobjective optimization algorithm is designed for path planning. In the first stage, pulse algorithm is used to obtain the Pareto paths from the distribution center to each destination. In the second stage, a multiobjective optimization method based on Nondominated Sorting Genetic Algorithm II (NSGA-II is designed to obtain candidate transport paths. Second, with analysis on the operating process of vehicles with hazardous materials in FCL, the vehicle scheduling problem is converted to Vehicle Routing Problem with Time Windows (VRPTW. A problem-solving method based on estimation of distribution is adopted. A transport timetable for all vehicles based on their transport paths is calculated, with participation of the decision-makers. A visual vehicle scheduling plan is presented for the decision-makers. Last, two examples are used to test the method proposed in this study: distribution of hazardous materials in a small-scale test network and distribution of oil products for sixteen gas stations in the main districts of Lanzhou city. In both examples, our method is used to obtain the path selection and vehicle scheduling plan, proving that validity of our method is verified.

  6. An Improved Harmony Search algorithm for optimal scheduling of the diesel generators in oil rig platforms

    International Nuclear Information System (INIS)

    Yadav, Parikshit; Kumar, Rajesh; Panda, S.K.; Chang, C.S.

    2011-01-01

    Harmony Search (HS) algorithm is music based meta-heuristic optimization method which is analogous with the music improvisation process where musician continue to polish the pitches in order to obtain better harmony. The paper focuses on the optimal scheduling of the generators to reduce the fuel consumption in the oil rig platform. The accurate modeling of the specific fuel consumption is significant in this optimization. The specific fuel consumption has been modeled using cubic spline interpolation. The SFC curve is non-linear and discrete in nature, hence conventional methods fail to give optimal solution. HS algorithm has been used for optimal scheduling of the generators of both equal and unequal rating. Furthermore an Improved Harmony Search (IHS) method for generating new solution vectors that enhances accuracy and convergence rate of HS has been employed. The paper also focuses on the impacts of constant parameters on Harmony Search algorithm. Numerical results show that the IHS method has good convergence property. Moreover, the fuel consumption for IHS algorithm is lower when compared to HS and other heuristic or deterministic methods and is a powerful search algorithm for various engineering optimization problems.

  7. An ant colony optimization heuristic for an integrated production and distribution scheduling problem

    Science.gov (United States)

    Chang, Yung-Chia; Li, Vincent C.; Chiang, Chia-Ju

    2014-04-01

    Make-to-order or direct-order business models that require close interaction between production and distribution activities have been adopted by many enterprises in order to be competitive in demanding markets. This article considers an integrated production and distribution scheduling problem in which jobs are first processed by one of the unrelated parallel machines and then distributed to corresponding customers by capacitated vehicles without intermediate inventory. The objective is to find a joint production and distribution schedule so that the weighted sum of total weighted job delivery time and the total distribution cost is minimized. This article presents a mathematical model for describing the problem and designs an algorithm using ant colony optimization. Computational experiments illustrate that the algorithm developed is capable of generating near-optimal solutions. The computational results also demonstrate the value of integrating production and distribution in the model for the studied problem.

  8. An Optimal CDS Construction Algorithm with Activity Scheduling in Ad Hoc Networks

    Directory of Open Access Journals (Sweden)

    Chakradhar Penumalli

    2015-01-01

    Full Text Available A new energy efficient optimal Connected Dominating Set (CDS algorithm with activity scheduling for mobile ad hoc networks (MANETs is proposed. This algorithm achieves energy efficiency by minimizing the Broadcast Storm Problem [BSP] and at the same time considering the node’s remaining energy. The Connected Dominating Set is widely used as a virtual backbone or spine in mobile ad hoc networks [MANETs] or Wireless Sensor Networks [WSN]. The CDS of a graph representing a network has a significant impact on an efficient design of routing protocol in wireless networks. Here the CDS is a distributed algorithm with activity scheduling based on unit disk graph [UDG]. The node’s mobility and residual energy (RE are considered as parameters in the construction of stable optimal energy efficient CDS. The performance is evaluated at various node densities, various transmission ranges, and mobility rates. The theoretical analysis and simulation results of this algorithm are also presented which yield better results.

  9. An Optimal CDS Construction Algorithm with Activity Scheduling in Ad Hoc Networks.

    Science.gov (United States)

    Penumalli, Chakradhar; Palanichamy, Yogesh

    2015-01-01

    A new energy efficient optimal Connected Dominating Set (CDS) algorithm with activity scheduling for mobile ad hoc networks (MANETs) is proposed. This algorithm achieves energy efficiency by minimizing the Broadcast Storm Problem [BSP] and at the same time considering the node's remaining energy. The Connected Dominating Set is widely used as a virtual backbone or spine in mobile ad hoc networks [MANETs] or Wireless Sensor Networks [WSN]. The CDS of a graph representing a network has a significant impact on an efficient design of routing protocol in wireless networks. Here the CDS is a distributed algorithm with activity scheduling based on unit disk graph [UDG]. The node's mobility and residual energy (RE) are considered as parameters in the construction of stable optimal energy efficient CDS. The performance is evaluated at various node densities, various transmission ranges, and mobility rates. The theoretical analysis and simulation results of this algorithm are also presented which yield better results.

  10. A New Software for Management, Scheduling, and Optimization for the Light Hydrocarbon Pipeline Network System of Daqing Oilfield

    Directory of Open Access Journals (Sweden)

    Yongtu Liang

    2014-01-01

    Full Text Available This paper presents the new software which specifically developed based on Visual Studio 2010 for Daqing Oilfield China includes the most complex light hydrocarbon pipeline network system in Asia, has become a powerful auxiliary tool to manage field data, makes scheduling plans for batching operation, and optimizes pumping plans. Firstly, DMM for recording and managing field data is summarized. Then, the batch scheduling simulation module called SSM for the difficult batch-scheduling issues of the multiple-source pipeline network system is introduced. Finally, SOM, that is Scheduling Optimization Module, is indicated for solving the problem of the pumps being started up/shut-down frequently.

  11. Optimization of horizontal microcode within and beyond basic blocks: an application of processor scheduling with resources

    Energy Technology Data Exchange (ETDEWEB)

    Fisher, J.A.

    1979-10-01

    Microprogram optimization is the rearrangement of microcode written vertically, with one operation issued per step, into legal horizontal microinstructions, in which several operations are issued each instruction cycle. The rearrangement is done in a way that approximately minimizes the running time of the code. This problem is identified with the problem of processor scheduling with resource constraints. Thus, the problem of optimizing basic blocks of microcode can be seen to be np-complete; however, approximate methods for basic blocks which have good records in other, similar scheduling environments can be used. In priority list scheduling the tasks are ordered according to some evaluation function, and then schedules are found by repeated scans of the list. Several evaluation functions are shown to perform very well on large samples of various classes of random data-precedence graphs with characteristics similar to those derived from microprograms. A method of spotting resource bottlenecks in the derived data-precedence graph enables one to obtain a resource-considerate evaluation function, in which tasks which contribute directly to or precede bottlenecks have their priorities raised. The complexity of the calculations necessary to compute the lower bound was greatly reduced. A method is suggested for optimizing beyond basic blocks. Groups of basic blocks are treated as if they were one block; the information necessary to control the motion of tasks between blocks is encoded as data-precedence constraints on the conditional tasks. Long paths of code can thus be optimized, with no back branches, by the same methods used for basic blocks. 9 figures, 6 tables.

  12. Joint Scheduling Optimization of Virtual Power Plants and Equitable Profit Distribution Using Shapely Value Theory

    OpenAIRE

    Tan, Zhong-fu; Li, Huan-huan; Ju, Li-wei; Tan, Qing-kun

    2018-01-01

    The installation capacity of wind and solar photovoltaic power is continually increasing, which makes renewable energy grid connection and power generation an important link of China’s power structure optimization. A virtual power plant (VPP) is an important way to help distributed energy resource grid connection and promote renewable energy industry development. To study the economic scheduling problem of various distributed energy resources and the profit distribution problem of VPP allianc...

  13. Scheduling a Wind Hydro-Pumped-Storage Unit Considering the Economical Optimization

    OpenAIRE

    Ghaisi, Milad; Rahmani, Milad; Gharghabi, Pedram; Zoghi, Ali; Hosseinian, Seyed Hossein

    2017-01-01

    International audience; In this paper a new approach has been introduced to find the optimum capacity of a wind farm to cooperate with a hydro-pumped-storage in order to maximize the income and optimize the payback period of their combination. First, Monte Carlo method has been used to generate the annual price and wind speed values. Then, an operating policy has been considered to schedule each unit generating and saving the produced energy by the wind farm. Subsequently, simulations have be...

  14. Influence of the atrio-ventricular delay optimization on the intra left ventricular delay in cardiac resynchronization therapy

    Directory of Open Access Journals (Sweden)

    Nienaber Christoph A

    2006-01-01

    Full Text Available Abstract Background Cardiac Resynchronization Therapy (CRT leads to a reduction of left-ventricular dyssynchrony and an acute and sustained hemodynamic improvement in patients with chronic heart failure. Furthermore, an optimized AV-delay leads to an improved myocardial performance in pacemaker patients. The focus of this study is to investigate the acute effect of an optimized AV-delay on parameters of dyssynchrony in CRT patients. Method 11 chronic heart failure patients with CRT who were on stable medication were included in this study. The optimal AV-delay was defined according to the method of Ismer (mitral inflow and trans-oesophageal lead. Dyssynchrony was assessed echocardiographically at three different settings: AVDOPT; AVDOPT-50 ms and AVDOPT+50 ms. Echocardiographic assessment included 2D- and M-mode echo for the assessment of volumes and hemodynamic parameters (CI, SV and LVEF and tissue Doppler echo (strain, strain rate, Tissue Synchronisation Imaging (TSI and myocardial velocities in the basal segments Results The AVDOPT in the VDD mode (atrially triggered was 105.5 ± 38.1 ms and the AVDOPT in the DDD mode (atrially paced was 186.9 ± 52.9 ms. Intra-individually, the highest LVEF was measured at AVDOPT. The LVEF at AVDOPT was significantly higher than in the AVDOPT-50setting (p = 0.03. However, none of the parameters of dyssynchrony changed significantly in the three settings. Conclusion An optimized AV delay in CRT patients acutely leads to an improved systolic left ventricular ejection fraction without improving dyssynchrony.

  15. Reliability-based optimization of maintenance scheduling of mechanical components under fatigue.

    Science.gov (United States)

    Beaurepaire, P; Valdebenito, M A; Schuëller, G I; Jensen, H A

    2012-05-01

    This study presents the optimization of the maintenance scheduling of mechanical components under fatigue loading. The cracks of damaged structures may be detected during non-destructive inspection and subsequently repaired. Fatigue crack initiation and growth show inherent variability, and as well the outcome of inspection activities. The problem is addressed under the framework of reliability based optimization. The initiation and propagation of fatigue cracks are efficiently modeled using cohesive zone elements. The applicability of the method is demonstrated by a numerical example, which involves a plate with two holes subject to alternating stress.

  16. Application of genetic algorithms to the maintenance scheduling optimization in a nuclear system basing on reliability

    International Nuclear Information System (INIS)

    Lapa, Celso M. Franklin; Pereira, Claudio M.N.A.; Mol, Antonio C. de Abreu

    1999-01-01

    This paper presents a solution based on genetic algorithm and probabilistic safety analysis that can be applied in the optimization of the preventive maintenance politic of nuclear power plant safety systems. The goal of this approach is to improve the average availability of the system through the optimization of the preventive maintenance scheduling politic. The auxiliary feed water system of a two loops pressurized water reactor is used as a sample case, in order to demonstrate the effectiveness of the proposed method. The results, when compared to those obtained by some standard maintenance politics, reveal quantitative gains and operational safety levels. (author)

  17. Optimal scheduling of biocide dosing for seawater-cooled power and desalination plants

    KAUST Repository

    Mahfouz, Abdullah Bin

    2011-02-13

    Thermal desalination systems are typically integrated with power plants to exploit the excess heat resulting from the power-generation units. Using seawater in cooling the power plant and the desalination system is a common practice in many parts of the world where there is a shortage of freshwater. Biofouling is one of the major problems associated with the usage of seawater in cooling systems. Because of the dynamic variation in the power and water demands as well as the changes in the characteristics of seawater and the process, there is a need to develop an optimal policy for scheduling biocide usage and cleaning maintenance of the heat exchangers. The objective of this article is to introduce a systematic procedure for the optimization of scheduling the dosing of biocide and dechlorination chemicals as well as cleaning maintenance for a power production/thermal desalination plant. A multi-period optimization formulation is developed and solved to determine: the optimal levels of dosing and dechlorination chemicals; the timing of maintenance to clean the heat-exchange surfaces; and the dynamic dependence of the biofilm growth on the applied doses, the seawater-biocide chemistry, the process conditions, and seawater characteristics for each time period. The technical, economic, and environmental considerations of the system are accounted for. A case study is solved to elucidate the applicability of the developed optimization approach. © 2011 Springer-Verlag.

  18. Hybrid Symbiotic Organisms Search Optimization Algorithm for Scheduling of Tasks on Cloud Computing Environment.

    Science.gov (United States)

    Abdullahi, Mohammed; Ngadi, Md Asri

    2016-01-01

    Cloud computing has attracted significant attention from research community because of rapid migration rate of Information Technology services to its domain. Advances in virtualization technology has made cloud computing very popular as a result of easier deployment of application services. Tasks are submitted to cloud datacenters to be processed on pay as you go fashion. Task scheduling is one the significant research challenges in cloud computing environment. The current formulation of task scheduling problems has been shown to be NP-complete, hence finding the exact solution especially for large problem sizes is intractable. The heterogeneous and dynamic feature of cloud resources makes optimum task scheduling non-trivial. Therefore, efficient task scheduling algorithms are required for optimum resource utilization. Symbiotic Organisms Search (SOS) has been shown to perform competitively with Particle Swarm Optimization (PSO). The aim of this study is to optimize task scheduling in cloud computing environment based on a proposed Simulated Annealing (SA) based SOS (SASOS) in order to improve the convergence rate and quality of solution of SOS. The SOS algorithm has a strong global exploration capability and uses fewer parameters. The systematic reasoning ability of SA is employed to find better solutions on local solution regions, hence, adding exploration ability to SOS. Also, a fitness function is proposed which takes into account the utilization level of virtual machines (VMs) which reduced makespan and degree of imbalance among VMs. CloudSim toolkit was used to evaluate the efficiency of the proposed method using both synthetic and standard workload. Results of simulation showed that hybrid SOS performs better than SOS in terms of convergence speed, response time, degree of imbalance, and makespan.

  19. Hybrid Symbiotic Organisms Search Optimization Algorithm for Scheduling of Tasks on Cloud Computing Environment.

    Directory of Open Access Journals (Sweden)

    Mohammed Abdullahi

    Full Text Available Cloud computing has attracted significant attention from research community because of rapid migration rate of Information Technology services to its domain. Advances in virtualization technology has made cloud computing very popular as a result of easier deployment of application services. Tasks are submitted to cloud datacenters to be processed on pay as you go fashion. Task scheduling is one the significant research challenges in cloud computing environment. The current formulation of task scheduling problems has been shown to be NP-complete, hence finding the exact solution especially for large problem sizes is intractable. The heterogeneous and dynamic feature of cloud resources makes optimum task scheduling non-trivial. Therefore, efficient task scheduling algorithms are required for optimum resource utilization. Symbiotic Organisms Search (SOS has been shown to perform competitively with Particle Swarm Optimization (PSO. The aim of this study is to optimize task scheduling in cloud computing environment based on a proposed Simulated Annealing (SA based SOS (SASOS in order to improve the convergence rate and quality of solution of SOS. The SOS algorithm has a strong global exploration capability and uses fewer parameters. The systematic reasoning ability of SA is employed to find better solutions on local solution regions, hence, adding exploration ability to SOS. Also, a fitness function is proposed which takes into account the utilization level of virtual machines (VMs which reduced makespan and degree of imbalance among VMs. CloudSim toolkit was used to evaluate the efficiency of the proposed method using both synthetic and standard workload. Results of simulation showed that hybrid SOS performs better than SOS in terms of convergence speed, response time, degree of imbalance, and makespan.

  20. Effects of AV-delay optimization on hemodynamic parameters in patients with VDD pacemakers.

    Science.gov (United States)

    Krychtiuk, Konstantin A; Nürnberg, Michael; Volker, Romana; Pachinger, Linda; Jarai, Rudolf; Freynhofer, Matthias K; Wojta, Johann; Huber, Kurt; Weiss, Thomas W

    2014-05-01

    Atrioventricular (AV) delay optimization improves hemodynamics and clinical parameters in patients treated with cardiac resynchronization therapy and dual-chamber-pacemakers (PM). However, data on optimizing AV delay in patients treated with VDD-PMs are scarce. We, therefore, investigated the acute and chronic effects of AV delay optimization on hemodynamics in patients treated with VDD-PMs due to AV-conduction disturbances. In this prospective, single-center interventional trial, we included 64 patients (38 men, 26 women, median age: 77 (70-82) years) with implanted VDD-PM. AV-delay optimization was performed using a formula based on the surface electrocardiogram (ECG). Hemodynamic parameters (stroke volume (SV), cardiac output (CO), heart rate (HR), and blood pressure (BP)) were measured at baseline and follow-up after 3 months using impedance cardiography. Using an ECG formula for AV-delay optimization, the AV interval was decreased from 180 (180-180) to 75 (75-100) ms. At baseline, AV-delay optimization led to a significant increase of both SV (71.3 ± 15.8 vs. 55.3 ± 12.7 ml, p AV delay vs. nominal AV interval, respectively) and CO (5.1 ± 1.4 vs. 3.9 ± 1.0 l/min, p AV-delay optimization in patients treated with VDD-PMs exhibits immediate beneficial effects on hemodynamic parameters that are sustained for 3 months.

  1. Whether noninvasive optimization of AV and VV delays improves the response to cardiac resynchronization therapy.

    Science.gov (United States)

    Urbanek, Bożena; Chudzik, Michał; Klimczak, Artur; Rosiak, Marcin; Lewek, Joanna; Wranicz, Jerzy Krzysztof

    2013-01-01

    Device optimization is not routinely performed in patients who underwent cardiac resynchronization therapy (CRT) device implantation. Noninvasive optimization of CRT devices by measurement of cardiac output (CO) can be used as a simple method to assess ventricular systolic performance. The aim of this study was to assess whether optimization of atrioventricular (AV) and interventricular (VV) delay can improve hemodynamic response to CRT and whether this optimization should be performed for each patient individually. Twenty patients with advanced heart failure New York Heart Association (NYHA) class III/IV, left ventricular ejection fraction ≤ 35% and left bundle branch block (QRS ≥ 120 ms) in sinus rhythm were evaluated from 24 h to 48 h after implantation of a CRT device by means of impedance cardiography (ICG). CO was first measured at each patient's intrinsic rhythm. Patients then underwent adjustments of AV and VV delay from 80 ms to 140 ms and from -60 ms to +60 ms, respectively in 20 ms increment steps and CO at each setting was measured by ICG. Both AV and VV delays were programmed according to the greatest improvement in CO compared to intrinsic rhythm. There was a statistically signifi cant increase in CO measured at the intrinsic rhythm compared to different AV delay by mean of 21% (3.8 ± 1.0 vs. 4.6 ± 0.1 L/min, p AV/VV delays with left ventricle-preexcitation or simultaneous biventricular pacing caused additional increased CO from intrinsic rhythm by mean of 32.6% (3.8 ± 1.0 vs. 5.04 ± ± 1.0 L/min, p AV/VV setting delays also resulted in improved hemodynamic responses compared to VV factory setting delay. Both AV and VV delay optimization should be performed in clinical practice. Optimal AV delay improved outcome. However, combination of optimized AV/VV delays provided the best hemodynamic response. Optimized AV/VV delays with left ventricle-preexcitation or simultaneous biventricular pacing increased hemodynamic output compared to intrinsic

  2. Optimizing Hydropower Day-Ahead Scheduling for the Oroville-Thermalito Project

    Science.gov (United States)

    Veselka, T. D.; Mahalik, M.

    2012-12-01

    Under an award from the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Water Power Program, a team of national laboratories is developing and demonstrating a suite of advanced, integrated analytical tools to assist managers and planners increase hydropower resources while enhancing the environment. As part of the project, Argonne National Laboratory is developing the Conventional Hydropower Energy and Environmental Systems (CHEERS) model to optimize day-ahead scheduling and real-time operations. We will present the application of CHEERS to the Oroville-Thermalito Project located in Northern California. CHEERS will aid California Department of Water Resources (CDWR) schedulers in making decisions about unit commitments and turbine-level operating points using a system-wide approach to increase hydropower efficiency and the value of power generation and ancillary services. The model determines schedules and operations that are constrained by physical limitations, characteristics of plant components, operational preferences, reliability, and environmental considerations. The optimization considers forebay and afterbay implications, interactions between cascaded power plants, turbine efficiency curves and rough zones, and operator preferences. CHEERS simultaneously considers over time the interactions among all CDWR power and water resources, hydropower economics, reservoir storage limitations, and a set of complex environmental constraints for the Thermalito Afterbay and Feather River habitats. Power marketers, day-ahead schedulers, and plant operators provide system configuration and detailed operational data, along with feedback on model design and performance. CHEERS is integrated with CDWR data systems to obtain historic and initial conditions of the system as the basis from which future operations are then optimized. Model results suggest alternative operational regimes that improve the value of CDWR resources to the grid while

  3. Proposed algorithm to improve job shop production scheduling using ant colony optimization method

    Science.gov (United States)

    Pakpahan, Eka KA; Kristina, Sonna; Setiawan, Ari

    2017-12-01

    This paper deals with the determination of job shop production schedule on an automatic environment. On this particular environment, machines and material handling system are integrated and controlled by a computer center where schedule were created and then used to dictate the movement of parts and the operations at each machine. This setting is usually designed to have an unmanned production process for a specified interval time. We consider here parts with various operations requirement. Each operation requires specific cutting tools. These parts are to be scheduled on machines each having identical capability, meaning that each machine is equipped with a similar set of cutting tools therefore is capable of processing any operation. The availability of a particular machine to process a particular operation is determined by the remaining life time of its cutting tools. We proposed an algorithm based on the ant colony optimization method and embedded them on matlab software to generate production schedule which minimize the total processing time of the parts (makespan). We test the algorithm on data provided by real industry and the process shows a very short computation time. This contributes a lot to the flexibility and timelines targeted on an automatic environment.

  4. A fuzzy set approach to the flow computation in optimal power scheduling

    International Nuclear Information System (INIS)

    Wang, C.; Shahidehpour, S.M.

    1992-01-01

    The objective of multi-area power scheduling is to minimize the system operation cost while satisfying the system constraints, e.g., tie line capacity limits. This paper reports that there are two phases considered for the solution of this problem. One is the unit commitment which determines the operation states of generating units. The other is the economic dispatch which coordinates the generation among committed units. These two phases interact with each other as the area unit commitment may have to be rescheduled according to the economic dispatch results to m maintain a certain amount of area power generation and satisfy the operating constraints. In order to obtain an initial area unit commitment, previous algorithms assumed there would be no interchange transactions among areas(1-3). The principle idea for solving the multi-area generation scheduling problem was based on scheduling the unit commitment in each area and dispatching the total load economically among committed units such that the economical areas would generate excessive power and export the extra power to more expensive areas. However, tie flows reflect the power generation schedule in each area as the area unit commitment is adjusted to satisfy the security constraints. If the initial unit commitment in each area does not include any information regarding the interchange transactions, it will be computationally expensive to reach the optimal solution in large scale systems

  5. Optimal autaptic and synaptic delays enhanced synchronization transitions induced by each other in Newman–Watts neuronal networks

    International Nuclear Information System (INIS)

    Wang, Baoying; Gong, Yubing; Xie, Huijuan; Wang, Qi

    2016-01-01

    Highlights: • Optimal autaptic delay enhanced synchronization transitions induced by synaptic delay in neuronal networks. • Optimal synaptic delay enhanced synchronization transitions induced by autaptic delay. • Optimal coupling strength enhanced synchronization transitions induced by autaptic or synaptic delay. - Abstract: In this paper, we numerically study the effect of electrical autaptic and synaptic delays on synchronization transitions induced by each other in Newman–Watts Hodgkin–Huxley neuronal networks. It is found that the synchronization transitions induced by synaptic delay vary with varying autaptic delay and become strongest when autaptic delay is optimal. Similarly, the synchronization transitions induced by autaptic delay vary with varying synaptic delay and become strongest at optimal synaptic delay. Also, there is optimal coupling strength by which the synchronization transitions induced by either synaptic or autaptic delay become strongest. These results show that electrical autaptic and synaptic delays can enhance synchronization transitions induced by each other in the neuronal networks. This implies that electrical autaptic and synaptic delays can cooperate with each other and more efficiently regulate the synchrony state of the neuronal networks. These findings could find potential implications for the information transmission in neural systems.

  6. A modified generalized extremal optimization algorithm for the quay crane scheduling problem with interference constraints

    Science.gov (United States)

    Guo, Peng; Cheng, Wenming; Wang, Yi

    2014-10-01

    The quay crane scheduling problem (QCSP) determines the handling sequence of tasks at ship bays by a set of cranes assigned to a container vessel such that the vessel's service time is minimized. A number of heuristics or meta-heuristics have been proposed to obtain the near-optimal solutions to overcome the NP-hardness of the problem. In this article, the idea of generalized extremal optimization (GEO) is adapted to solve the QCSP with respect to various interference constraints. The resulting GEO is termed the modified GEO. A randomized searching method for neighbouring task-to-QC assignments to an incumbent task-to-QC assignment is developed in executing the modified GEO. In addition, a unidirectional search decoding scheme is employed to transform a task-to-QC assignment to an active quay crane schedule. The effectiveness of the developed GEO is tested on a suite of benchmark problems introduced by K.H. Kim and Y.M. Park in 2004 (European Journal of Operational Research, Vol. 156, No. 3). Compared with other well-known existing approaches, the experiment results show that the proposed modified GEO is capable of obtaining the optimal or near-optimal solution in a reasonable time, especially for large-sized problems.

  7. Towards Cost and Comfort Based Hybrid Optimization for Residential Load Scheduling in a Smart Grid

    Directory of Open Access Journals (Sweden)

    Nadeem Javaid

    2017-10-01

    Full Text Available In a smart grid, several optimization techniques have been developed to schedule load in the residential area. Most of these techniques aim at minimizing the energy consumption cost and the comfort of electricity consumer. Conversely, maintaining a balance between two conflicting objectives: energy consumption cost and user comfort is still a challenging task. Therefore, in this paper, we aim to minimize the electricity cost and user discomfort while taking into account the peak energy consumption. In this regard, we implement and analyse the performance of a traditional dynamic programming (DP technique and two heuristic optimization techniques: genetic algorithm (GA and binary particle swarm optimization (BPSO for residential load management. Based on these techniques, we propose a hybrid scheme named GAPSO for residential load scheduling, so as to optimize the desired objective function. In order to alleviate the complexity of the problem, the multi dimensional knapsack is used to ensure that the load of electricity consumer will not escalate during peak hours. The proposed model is evaluated based on two pricing schemes: day-ahead and critical peak pricing for single and multiple days. Furthermore, feasible regions are calculated and analysed to develop a relationship between power consumption, electricity cost, and user discomfort. The simulation results are compared with GA, BPSO and DP, and validate that the proposed hybrid scheme reflects substantial savings in electricity bills with minimum user discomfort. Moreover, results also show a phenomenal reduction in peak power consumption.

  8. Performance deterioration modeling and optimal preventive maintenance strategy under scheduled servicing subject to mission time

    Directory of Open Access Journals (Sweden)

    Li Dawei

    2014-08-01

    Full Text Available Servicing is applied periodically in practice with the aim of restoring the system state and prolonging the lifetime. It is generally seen as an imperfect maintenance action which has a chief influence on the maintenance strategy. In order to model the maintenance effect of servicing, this study analyzes the deterioration characteristics of system under scheduled servicing. And then the deterioration model is established from the failure mechanism by compound Poisson process. On the basis of the system damage value and failure mechanism, the failure rate refresh factor is proposed to describe the maintenance effect of servicing. A maintenance strategy is developed which combines the benefits of scheduled servicing and preventive maintenance. Then the optimization model is given to determine the optimal servicing period and preventive maintenance time, with an objective to minimize the system expected life-cycle cost per unit time and a constraint on system survival probability for the duration of mission time. Subject to mission time, it can control the ability of accomplishing the mission at any time so as to ensure the high dependability. An example of water pump rotor relating to scheduled servicing is introduced to illustrate the failure rate refresh factor and the proposed maintenance strategy. Compared with traditional methods, the numerical results show that the failure rate refresh factor can describe the maintenance effect of servicing more intuitively and objectively. It also demonstrates that this maintenance strategy can prolong the lifetime, reduce the total lifetime maintenance cost and guarantee the dependability of system.

  9. The Effect of a Reconstruction Technique and Heart Rate in the Evaluation of Optimal Trigger Delay Using Multiphase Reconstruction

    International Nuclear Information System (INIS)

    Cho, Young Jun

    2008-01-01

    To evaluate the mean optimal trigger delays and the difference between the absolute delay and the relative delay as a function of heart rate, using multiphase reconstruction. A total of 30 patients consecutively underwent a 64-slice MDCT examination. Optimal trigger delays at four planes (the bifurcation of the left main coronary artery, aortic valve, mitral valve and cardiac apex) were measured using multiphase reconstruction based on the absolute and relative delay. For this reason, patients were divided into three groups according to heart rate (group I, < 65 bpm; group II, 65-74 bpm; group III, ≥ 75 bpm), and the mean optimal trigger delays and the difference between the absolute delay and the relative delay were evaluated at the four planes for each group. The mean optimal trigger delay for the relative delay and absolute delay ranged from 46% to 66% and from 327 to 700 msec, respectively. The differences in the mean optimal trigger delay using the relative and the absolute delay at the four planes were 1% and 4 msec (group I), 3% and 27 msec (group II), and 14% and 46 msec (group III). In group III, the difference of the mean optimal trigger delay based on the relative delay, increased significantly compared to the absolute delay (p = 0.040). For the patients analyzed, the results suggest that as the heart rate increased, the mean optimal trigger delays shifted from the mid-diastolic phase to the end-systolic phase and the differences in the mean optimal trigger delay at the four planes were significantly greater for the relative delay

  10. Optimal Cluster Mill Pass Scheduling With an Accurate and Rapid New Strip Crown Model

    International Nuclear Information System (INIS)

    Malik, Arif S.; Grandhi, Ramana V.; Zipf, Mark E.

    2007-01-01

    Besides the requirement to roll coiled sheet at high levels of productivity, the optimal pass scheduling of cluster-type reversing cold mills presents the added challenge of assigning mill parameters that facilitate the best possible strip flatness. The pressures of intense global competition, and the requirements for increasingly thinner, higher quality specialty sheet products that are more difficult to roll, continue to force metal producers to commission innovative flatness-control technologies. This means that during the on-line computerized set-up of rolling mills, the mathematical model should not only determine the minimum total number of passes and maximum rolling speed, it should simultaneously optimize the pass-schedule so that desired flatness is assured, either by manual or automated means. In many cases today, however, on-line prediction of strip crown and corresponding flatness for the complex cluster-type rolling mills is typically addressed either by trial and error, by approximate deflection models for equivalent vertical roll-stacks, or by non-physical pattern recognition style models. The abundance of the aforementioned methods is largely due to the complexity of cluster-type mill configurations and the lack of deflection models with sufficient accuracy and speed for on-line use. Without adequate assignment of the pass-schedule set-up parameters, it may be difficult or impossible to achieve the required strip flatness. In this paper, we demonstrate optimization of cluster mill pass-schedules using a new accurate and rapid strip crown model. This pass-schedule optimization includes computations of the predicted strip thickness profile to validate mathematical constraints. In contrast to many of the existing methods for on-line prediction of strip crown and flatness on cluster mills, the demonstrated method requires minimal prior tuning and no extensive training with collected mill data. To rapidly and accurately solve the multi-contact problem

  11. Hybrid Particle Swarm Optimization based Day-Ahead Self-Scheduling for Thermal Generator in Competitive Electricity Market

    DEFF Research Database (Denmark)

    Pindoriya, Naran M.; Singh, S.N.; Østergaard, Jacob

    2009-01-01

    This paper presents a hybrid particle swarm optimization algorithm (HPSO) to solve the day-ahead self-scheduling for thermal power producer in competitive electricity market. The objective functions considered to model the self-scheduling problem are 1) to maximize the profit from selling energy...

  12. Optimization of Task Scheduling Algorithm through QoS Parameters for Cloud Computing

    Directory of Open Access Journals (Sweden)

    Monika

    2016-01-01

    Full Text Available Cloud computing is an incipient innovation which broadly spreads among analysts. It furnishes clients with foundation, stage and programming as enhancement which is easily available by means of web. A cloud is a sort of parallel and conveyed framework comprising of a gathering of virtualized PCs that are utilized to execute various tasks to accomplish good execution time, accomplish due date and usage of its assets. The scheduling issue can be seen as the finding an ideal task of assignments over the accessible arrangement of assets with the goal that we can accomplish the wanted objectives for tasks. This paper presents an optimal algorithm for scheduling tasks to get their waiting time as a QoS parameter. The algorithm is simulated using Cloudsim simulator and experiments are carried out to help clients to make sense of the bottleneck of utilizing no. of virtual machine parallely.

  13. Optimal scheduling for electric heat booster under day-ahead electricity and heat pricing

    DEFF Research Database (Denmark)

    Cai, Hanmin; You, Shi; Bindner, Henrik W.

    2017-01-01

    Multi-energy system (MES) operation calls for active management of flexible resources across energy sectors to improve efficiency and meet challenging environmental targets. Electric heat booster, a solution for Domestic Hot Water (DHW) preparation under Low-Temperature-District-Heating (LTDH......) context, is identified as one of aforementioned flexible resources for electricity and heat sectors. This paper extends the concept of optimal load scheduling under day-ahead pricing from electricity sector only to both electricity and heat sectors. A case study constructing day-ahead energy prices...... to shift energy consumption to low carbon content energy is provided. Results show that 0.5 DKK/kWhel add-ons on top of electricity spot price makes electricity and heat price not comparable such that electricity price variation will have no impact on load scheduling. This result suggests aforementioned...

  14. Schedule Optimization Study, Hanford RI/FS Program. Volume 2, Final report

    Energy Technology Data Exchange (ETDEWEB)

    1992-12-01

    A Schedule Optimization Study (SOS) of the US Department of Energy (DOE) Hanford Site Remedial Investigation/Feasibility Study (RI/FS) Program was conducted by an independent team of professionals from other federal agencies and the private sector experienced in environmental restoration. This team spent two weeks at Hanford in September 1992 examining the reasons for the lengthy RI/FS process at Hanford and developing recommendations to expedite the process. The need for the study arose out of a schedule dispute regarding the submission of the 1100-EM-1 Operable Unit RI/FS Work Plan. This report documents the study called for in the August 29, 1991, Dispute Resolution Committee Decision Statement. Battelle`s Environmental Management Operations (EMO) coordinated the effort for DOE`s Richland Field Office (RL).

  15. Comparison of optimal irrigation scheduling and groundwater recharge at representative sites in the North China Plain

    Science.gov (United States)

    Ma, Ying

    2014-05-01

    The North China Plain (NCP) is an important food production area in China, facing an increasing water shortage and overexploitation of groundwater. It is critical to optimize the irrigation scheduling and accurately estimate groundwater recharge for saving water and increasing crop water use efficiency. However, the water cycle and crop responses to irrigation are quite various in different areas, because of the spatial variation of climatic, soil, water table and other management practices in the NCP. In this study, three representative sites (LC site in the piedmont plain, TZ site in the northern alluvial and lacustrine plain, YC site in the southern alluvial and lacustrine plain) were selected to compare the optimal irrigation scheduling and corresponding groundwater recharge under different hydrological years for winter wheat-summer maize double cropping system. At each site, a physically based agro-hydrological model (SWAP) was calibrated using field data of soil moisture. Then, scenarios under different irrigation time and amount were simulated. Results showed that the optimal irrigation scheduling and corresponding groundwater recharge were significant different between the three representative sites. The mean water table depth at the LC (33.0 m), YC (10.3 m), and TZ site (2.5 m) caused great different time lags of infiltrated water and groundwater contribution to evapotranspiration. Then, the most irrigation amount was required for the TZ site but the least requirement for the YC site at each hydrologic year. As most clay contents in the deep soils at the LC site increased tortuosity and limited water movement, which resulted in lower rates of recharge compared to more sandy soils at the other two sites. Averagely, using the optimal irrigation scheduling could save 2.04×109 m3 irrigation water and reduce about 84.3% groundwater over-exploitation in winter wheat growth period in the NCP. Therefore, comparison of the simulation results among the three

  16. Metroplex Optimization Model Expansion and Analysis: The Airline Fleet, Route, and Schedule Optimization Model (AFRS-OM)

    Science.gov (United States)

    Sherry, Lance; Ferguson, John; Hoffman, Karla; Donohue, George; Beradino, Frank

    2012-01-01

    This report describes the Airline Fleet, Route, and Schedule Optimization Model (AFRS-OM) that is designed to provide insights into airline decision-making with regards to markets served, schedule of flights on these markets, the type of aircraft assigned to each scheduled flight, load factors, airfares, and airline profits. The main inputs to the model are hedged fuel prices, airport capacity limits, and candidate markets. Embedded in the model are aircraft performance and associated cost factors, and willingness-to-pay (i.e. demand vs. airfare curves). Case studies demonstrate the application of the model for analysis of the effects of increased capacity and changes in operating costs (e.g. fuel prices). Although there are differences between airports (due to differences in the magnitude of travel demand and sensitivity to airfare), the system is more sensitive to changes in fuel prices than capacity. Further, the benefits of modernization in the form of increased capacity could be undermined by increases in hedged fuel prices

  17. Improved teaching-learning-based and JAYA optimization algorithms for solving flexible flow shop scheduling problems

    Science.gov (United States)

    Buddala, Raviteja; Mahapatra, Siba Sankar

    2017-11-01

    Flexible flow shop (or a hybrid flow shop) scheduling problem is an extension of classical flow shop scheduling problem. In a simple flow shop configuration, a job having `g' operations is performed on `g' operation centres (stages) with each stage having only one machine. If any stage contains more than one machine for providing alternate processing facility, then the problem becomes a flexible flow shop problem (FFSP). FFSP which contains all the complexities involved in a simple flow shop and parallel machine scheduling problems is a well-known NP-hard (Non-deterministic polynomial time) problem. Owing to high computational complexity involved in solving these problems, it is not always possible to obtain an optimal solution in a reasonable computation time. To obtain near-optimal solutions in a reasonable computation time, a large variety of meta-heuristics have been proposed in the past. However, tuning algorithm-specific parameters for solving FFSP is rather tricky and time consuming. To address this limitation, teaching-learning-based optimization (TLBO) and JAYA algorithm are chosen for the study because these are not only recent meta-heuristics but they do not require tuning of algorithm-specific parameters. Although these algorithms seem to be elegant, they lose solution diversity after few iterations and get trapped at the local optima. To alleviate such drawback, a new local search procedure is proposed in this paper to improve the solution quality. Further, mutation strategy (inspired from genetic algorithm) is incorporated in the basic algorithm to maintain solution diversity in the population. Computational experiments have been conducted on standard benchmark problems to calculate makespan and computational time. It is found that the rate of convergence of TLBO is superior to JAYA. From the results, it is found that TLBO and JAYA outperform many algorithms reported in the literature and can be treated as efficient methods for solving the FFSP.

  18. Optimized Scheduling of Smart Meter Data Access for Real-time Voltage Quality Monitoring

    DEFF Research Database (Denmark)

    Kemal, Mohammed Seifu; Olsen, Rasmus Løvenstein; Schwefel, Hans-Peter

    2018-01-01

    Abstract—Active low-voltage distribution grids that support high integration of distributed generation such as photovoltaics and wind turbines require real-time voltage monitoring. At the same time, countries in Europe such as Denmark have close to 100% rollout of smart metering infrastructure....... The metering infrastructure has limitations to provide real-time measurements with small-time granularity. This paper presents an algorithm for optimized scheduling of smart meter data access to provide real-time voltage quality monitoring. The algorithm is analyzed using a real distribution grid in Denmark...

  19. Optimal Research and Numerical Simulation for Scheduling No-Wait Flow Shop in Steel Production

    Directory of Open Access Journals (Sweden)

    Huawei Yuan

    2013-01-01

    Full Text Available This paper considers the m-machine flow shop scheduling problem with the no-wait constraint to minimize total completion time which is the typical model in steel production. First, the asymptotic optimality of the Shortest Processing Time (SPT first rule is proven for this problem. To further evaluate the performance of the algorithm, a new lower bound with performance guarantee is designed. At the end of the paper, numerical simulations show the effectiveness of the proposed algorithm and lower bound.

  20. Lyapunov matrices approach to the parametric optimization of time-delay systems

    Directory of Open Access Journals (Sweden)

    Duda Józef

    2015-09-01

    Full Text Available In the paper a Lyapunov matrices approach to the parametric optimization problem of time-delay systems with a P-controller is presented. The value of integral quadratic performance index of quality is equal to the value of Lyapunov functional for the initial function of the time-delay system. The Lyapunov functional is determined by means of the Lyapunov matrix

  1. The short-run dynamics of optimal growyh models with delays

    OpenAIRE

    Collard, Fabrice; Licandro, Omar; Puch, Luis A.

    2003-01-01

    Differential equations with advanced and delayed time arguments may arise in the optimality conditions of simple growth models with delays. Models with investment gestation lags (time-to-build), consumption gestation lags (habit formation) or learning by using lie in this category. In this paper, we propose a shooting method to deal with leads and lags in the Euler system associated to dynamic general equilibrium models in continuous time. We introduce the discussion describing the dynamic...

  2. Optimization procedure for algorithms of task scheduling in high performance heterogeneous distributed computing systems

    Directory of Open Access Journals (Sweden)

    Nirmeen A. Bahnasawy

    2011-11-01

    Full Text Available In distributed computing, the schedule by which tasks are assigned to processors is critical to minimizing the execution time of the application. However, the problem of discovering the schedule that gives the minimum execution time is NP-complete. In this paper, a new task scheduling algorithm called Sorted Nodes in Leveled DAG Division (SNLDD is introduced and developed for HeDCSs with consider a bounded number of processors. The main principle of the developed algorithm is to divide the Directed Acyclic Graph (DAG into levels and sort the tasks in each level according to their computation size in descending order. To evaluate the performance of the developed SNLDD algorithm, a comparative study has been done between the developed SNLDD algorithm and the Longest Dynamic Critical Path (LDCP algorithm which is considered the most efficient existing algorithm. According to the comparative results, it is found that the performance of the developed algorithm provides better performance than the LDCP algorithm in terms of speedup, efficiency, complexity, and quality. Also, a new procedure called Superior Performance Optimization Procedure (SPOP has been introduced and implemented in the developed SNLDD algorithm and the LDCP algorithm to minimize the sleek time of the processors in the system. Again, the performance of the SNLDD algorithm outperforms the existing LDCP algorithm after adding the SPOP procedure.

  3. Optimized Charging Scheduling with Single Mobile Charger for Wireless Rechargeable Sensor Networks

    Directory of Open Access Journals (Sweden)

    Qihua Wang

    2017-11-01

    Full Text Available Due to the rapid development of wireless charging technology, the recharging issue in wireless rechargeable sensor network (WRSN has been a popular research problem in the past few years. The weakness of previous work is that charging route planning is not reasonable. In this work, a dynamic optimal scheduling scheme aiming to maximize the vacation time ratio of a single mobile changer for WRSN is proposed. In the proposed scheme, the wireless sensor network is divided into several sub-networks according to the initial topology of deployed sensor networks. After comprehensive analysis of energy states, working state and constraints for different sensor nodes in WRSN, we transform the optimized charging path problem of the whole network into the local optimization problem of the sub networks. The optimized charging path with respect to dynamic network topology in each sub-network is obtained by solving an optimization problem, and the lifetime of the deployed wireless sensor network can be prolonged. Simulation results show that the proposed scheme has good and reliable performance for a small wireless rechargeable sensor network.

  4. Scheduling structural health monitoring activities for optimizing life-cycle costs and reliability of wind turbines

    Science.gov (United States)

    Hanish Nithin, Anu; Omenzetter, Piotr

    2017-04-01

    Optimization of the life-cycle costs and reliability of offshore wind turbines (OWTs) is an area of immense interest due to the widespread increase in wind power generation across the world. Most of the existing studies have used structural reliability and the Bayesian pre-posterior analysis for optimization. This paper proposes an extension to the previous approaches in a framework for probabilistic optimization of the total life-cycle costs and reliability of OWTs by combining the elements of structural reliability/risk analysis (SRA), the Bayesian pre-posterior analysis with optimization through a genetic algorithm (GA). The SRA techniques are adopted to compute the probabilities of damage occurrence and failure associated with the deterioration model. The probabilities are used in the decision tree and are updated using the Bayesian analysis. The output of this framework would determine the optimal structural health monitoring and maintenance schedules to be implemented during the life span of OWTs while maintaining a trade-off between the life-cycle costs and risk of the structural failure. Numerical illustrations with a generic deterioration model for one monitoring exercise in the life cycle of a system are demonstrated. Two case scenarios, namely to build initially an expensive and robust or a cheaper but more quickly deteriorating structures and to adopt expensive monitoring system, are presented to aid in the decision-making process.

  5. Setting strategy of delay-optimization-oriented SMAC contention window size.

    Science.gov (United States)

    Rao, Yuan; Deng, Cheng; Su, Jun; Qiao, Yan; Zhu, Jun; Wang, Ru-Chuan

    2017-01-01

    Some frame components, such as SYNC (frame synchronization) and RTS/CTS (Ready to Send/Clear to Send), are not taken into consideration when the traditional setting strategies conduct the optimization of SMAC (Sensor MAC) contention window size. This paper proposes mathematical models that allow the analysis of data packets forwarding delay within one SMAC virtual cluster. Simulation results in OMNeT++ show good agreements with the proposed mathematical models, validating the models' correctness. The curve analyses of the models confirm the existence of delay-optimization-oriented contention window size that is closely related to the number of simultaneously contending nodes. Afterwards, it is shown that SYNC, RTS/CTS and EIFS (Extended InterFrame Space) have impacts on the optimal contention window size and expected delivery delay to various degrees, as well as throughput and energy efficiency. One ideal setting strategy of delay-optimization-oriented SMAC contention window size requires the combination of the network scale, SYNC, RTS/CTS and EIFS. Additionally, it is demonstrated that the proposed setting strategy makes contributions to the improvement in the existing SMAC extensions when they are integrated with each other, in terms of the end-to-end delay, throughput and energy consumption.

  6. Setting strategy of delay-optimization-oriented SMAC contention window size.

    Directory of Open Access Journals (Sweden)

    Yuan Rao

    Full Text Available Some frame components, such as SYNC (frame synchronization and RTS/CTS (Ready to Send/Clear to Send, are not taken into consideration when the traditional setting strategies conduct the optimization of SMAC (Sensor MAC contention window size. This paper proposes mathematical models that allow the analysis of data packets forwarding delay within one SMAC virtual cluster. Simulation results in OMNeT++ show good agreements with the proposed mathematical models, validating the models' correctness. The curve analyses of the models confirm the existence of delay-optimization-oriented contention window size that is closely related to the number of simultaneously contending nodes. Afterwards, it is shown that SYNC, RTS/CTS and EIFS (Extended InterFrame Space have impacts on the optimal contention window size and expected delivery delay to various degrees, as well as throughput and energy efficiency. One ideal setting strategy of delay-optimization-oriented SMAC contention window size requires the combination of the network scale, SYNC, RTS/CTS and EIFS. Additionally, it is demonstrated that the proposed setting strategy makes contributions to the improvement in the existing SMAC extensions when they are integrated with each other, in terms of the end-to-end delay, throughput and energy consumption.

  7. Setting strategy of delay-optimization-oriented SMAC contention window size

    Science.gov (United States)

    Deng, Cheng; Su, Jun; Qiao, Yan; Zhu, Jun; Wang, Ru-chuan

    2017-01-01

    Some frame components, such as SYNC (frame synchronization) and RTS/CTS (Ready to Send/Clear to Send), are not taken into consideration when the traditional setting strategies conduct the optimization of SMAC (Sensor MAC) contention window size. This paper proposes mathematical models that allow the analysis of data packets forwarding delay within one SMAC virtual cluster. Simulation results in OMNeT++ show good agreements with the proposed mathematical models, validating the models’ correctness. The curve analyses of the models confirm the existence of delay-optimization-oriented contention window size that is closely related to the number of simultaneously contending nodes. Afterwards, it is shown that SYNC, RTS/CTS and EIFS (Extended InterFrame Space) have impacts on the optimal contention window size and expected delivery delay to various degrees, as well as throughput and energy efficiency. One ideal setting strategy of delay-optimization-oriented SMAC contention window size requires the combination of the network scale, SYNC, RTS/CTS and EIFS. Additionally, it is demonstrated that the proposed setting strategy makes contributions to the improvement in the existing SMAC extensions when they are integrated with each other, in terms of the end-to-end delay, throughput and energy consumption. PMID:28732020

  8. An Ant Optimization Model for Unrelated Parallel Machine Scheduling with Energy Consumption and Total Tardiness

    Directory of Open Access Journals (Sweden)

    Peng Liang

    2015-01-01

    Full Text Available This research considers an unrelated parallel machine scheduling problem with energy consumption and total tardiness. This problem is compounded by two challenges: differences of unrelated parallel machines energy consumption and interaction between job assignments and machine state operations. To begin with, we establish a mathematical model for this problem. Then an ant optimization algorithm based on ATC heuristic rule (ATC-ACO is presented. Furthermore, optimal parameters of proposed algorithm are defined via Taguchi methods for generating test data. Finally, comparative experiments indicate the proposed ATC-ACO algorithm has better performance on minimizing energy consumption as well as total tardiness and the modified ATC heuristic rule is more effectively on reducing energy consumption.

  9. Delayed presentation of turner syndrome: Challenge to optimal management

    Directory of Open Access Journals (Sweden)

    Uma Kaimal Saikia

    2017-01-01

    Full Text Available Background: Turner syndrome (TS is a chromosomal disorder associated with dysmorphic features and comorbidities, with recent trends focusing on early diagnosis for adequate management. Aim: The aim is to study the age and mode of presentation of TS, associated comorbidities and look for any correlation with the genotype. Material and Methods: This was a retrospective analysis of girls with TS attending the endocrinology clinic of a tertiary care center. Their age, mode of presentation, and clinical features were noted. All participants underwent ear examination, echocardiography, and ultrasonography of the abdomen. Laboratory investigations included serum T4, thyroid-stimulating hormone, thyroid peroxidase antibodies, follicle-stimulating hormone, fasting, and 2-h plasma glucose after 75 g glucose load and a karyotype. Simple descriptive statistical methods were used. Results: Seventeen cases of TS were seen with a median age of presentation of 18 years (range 14–42 years. Primary amenorrhea was the most common reason for seeking medical attention (76.4% followed by short stature and diabetes mellitus (11.8% each. The mean height at presentation was 137.5 ± 5.4 cm. Monosomy of X chromosome (45,X was the most common karyotype obtained in 58.8% of the patients, followed by 45,X/46, XX in 17.6%, 45,X/46X,i(X(q10 in 11.8%, and 45,X/47,XXX and 46X,delXp11.2 in 5.9% patients each. Bicuspid aortic valve was seen in two patients having a 45,X/46,XX karyotype. Conclusion: Primary amenorrhea is the most common presenting feature in girls with TS leading to a delayed age of presentation. Short stature and dysmorphic features are often overlooked in infancy and childhood due to socioeconomic factors. This late age of presentation is a cause of concern as early detection and management is important for height outcomes, bone health, and psychosocial support. Assessment of comorbidities becomes important in this setting.

  10. Adaptive track scheduling to optimize concurrency and vectorization in GeantV

    International Nuclear Information System (INIS)

    Apostolakis, J; Brun, R; Carminati, F; Gheata, A; Novak, M; Wenzel, S; Bandieramonte, M; Bitzes, G; Canal, P; Elvira, V D; Jun, S Y; Lima, G; Licht, J C De Fine; Duhem, L; Sehgal, R; Shadura, O

    2015-01-01

    The GeantV project is focused on the R and D of new particle transport techniques to maximize parallelism on multiple levels, profiting from the use of both SIMD instructions and co-processors for the CPU-intensive calculations specific to this type of applications. In our approach, vectors of tracks belonging to multiple events and matching different locality criteria must be gathered and dispatched to algorithms having vector signatures. While the transport propagates tracks and changes their individual states, data locality becomes harder to maintain. The scheduling policy has to be changed to maintain efficient vectors while keeping an optimal level of concurrency. The model has complex dynamics requiring tuning the thresholds to switch between the normal regime and special modes, i.e. prioritizing events to allow flushing memory, adding new events in the transport pipeline to boost locality, dynamically adjusting the particle vector size or switching between vector to single track mode when vectorization causes only overhead. This work requires a comprehensive study for optimizing these parameters to make the behaviour of the scheduler self-adapting, presenting here its initial results. (paper)

  11. Robust Optimization of the Self- scheduling and Market Involvement for an Electricity Producer

    KAUST Repository

    Lima, Ricardo

    2015-01-07

    This work address the optimization under uncertainty of the self-scheduling, forward contracting, and pool involvement of an electricity producer operating a mixed power generation station, which combines thermal, hydro and wind sources, and uses a two-stage adaptive robust optimization approach. In this problem the wind power production and the electricity pool price are considered to be uncertain, and are described by uncertainty convex sets. Two variants of a constraint generation algorithm are proposed, namely a primal and dual version, and they are used to solve two case studies based on two different producers. Their market strategies are investigated for three different scenarios, corresponding to as many instances of electricity price forecasts. The effect of the producers’ approach, whether conservative or more risk prone, is also investigated by solving each instance for multiple values of the so-called budget parameter. It was possible to conclude that this parameter influences markedly the producers’ strategy, in terms of scheduling, profit, forward contracting, and pool involvement. Regarding the computational results, these show that for some instances, the two variants of the algorithms have a similar performance, while for a particular subset of them one variant has a clear superiority

  12. Fuzzy linear programming based optimal fuel scheduling incorporating blending/transloading facilities

    Energy Technology Data Exchange (ETDEWEB)

    Djukanovic, M.; Babic, B.; Milosevic, B. [Electrical Engineering Inst. Nikola Tesla, Belgrade (Yugoslavia); Sobajic, D.J. [EPRI, Palo Alto, CA (United States). Power System Control; Pao, Y.H. [Case Western Reserve Univ., Cleveland, OH (United States)]|[AI WARE, Inc., Cleveland, OH (United States)

    1996-05-01

    In this paper the blending/transloading facilities are modeled using an interactive fuzzy linear programming (FLP), in order to allow the decision-maker to solve the problem of uncertainty of input information within the fuel scheduling optimization. An interactive decision-making process is formulated in which decision-maker can learn to recognize good solutions by considering all possibilities of fuzziness. The application of the fuzzy formulation is accompanied by a careful examination of the definition of fuzziness, appropriateness of the membership function and interpretation of results. The proposed concept provides a decision support system with integration-oriented features, whereby the decision-maker can learn to recognize the relative importance of factors in the specific domain of optimal fuel scheduling (OFS) problem. The formulation of a fuzzy linear programming problem to obtain a reasonable nonfuzzy solution under consideration of the ambiguity of parameters, represented by fuzzy numbers, is introduced. An additional advantage of the FLP formulation is its ability to deal with multi-objective problems.

  13. A Chaotic Particle Swarm Optimization-Based Heuristic for Market-Oriented Task-Level Scheduling in Cloud Workflow Systems.

    Science.gov (United States)

    Li, Xuejun; Xu, Jia; Yang, Yun

    2015-01-01

    Cloud workflow system is a kind of platform service based on cloud computing. It facilitates the automation of workflow applications. Between cloud workflow system and its counterparts, market-oriented business model is one of the most prominent factors. The optimization of task-level scheduling in cloud workflow system is a hot topic. As the scheduling is a NP problem, Ant Colony Optimization (ACO) and Particle Swarm Optimization (PSO) have been proposed to optimize the cost. However, they have the characteristic of premature convergence in optimization process and therefore cannot effectively reduce the cost. To solve these problems, Chaotic Particle Swarm Optimization (CPSO) algorithm with chaotic sequence and adaptive inertia weight factor is applied to present the task-level scheduling. Chaotic sequence with high randomness improves the diversity of solutions, and its regularity assures a good global convergence. Adaptive inertia weight factor depends on the estimate value of cost. It makes the scheduling avoid premature convergence by properly balancing between global and local exploration. The experimental simulation shows that the cost obtained by our scheduling is always lower than the other two representative counterparts.

  14. A Chaotic Particle Swarm Optimization-Based Heuristic for Market-Oriented Task-Level Scheduling in Cloud Workflow Systems

    Directory of Open Access Journals (Sweden)

    Xuejun Li

    2015-01-01

    Full Text Available Cloud workflow system is a kind of platform service based on cloud computing. It facilitates the automation of workflow applications. Between cloud workflow system and its counterparts, market-oriented business model is one of the most prominent factors. The optimization of task-level scheduling in cloud workflow system is a hot topic. As the scheduling is a NP problem, Ant Colony Optimization (ACO and Particle Swarm Optimization (PSO have been proposed to optimize the cost. However, they have the characteristic of premature convergence in optimization process and therefore cannot effectively reduce the cost. To solve these problems, Chaotic Particle Swarm Optimization (CPSO algorithm with chaotic sequence and adaptive inertia weight factor is applied to present the task-level scheduling. Chaotic sequence with high randomness improves the diversity of solutions, and its regularity assures a good global convergence. Adaptive inertia weight factor depends on the estimate value of cost. It makes the scheduling avoid premature convergence by properly balancing between global and local exploration. The experimental simulation shows that the cost obtained by our scheduling is always lower than the other two representative counterparts.

  15. Maintenance of ovulation inhibition with a new progestogen-only pill containing drospirenone after scheduled 24-h delays in pill intake

    DEFF Research Database (Denmark)

    Duijkers, Ingrid J M; Heger-Mahn, Doris; Drouin, Dominique

    2016-01-01

    OBJECTIVES: Traditional progestogen-only pills (POPs) have stringent daily timing and missed pill rules that might affect contraceptive reliability. A new-generation oestrogen-free pill has been developed, containing 4-mg drospirenone with a unique regimen of 24 active treatment days followed...... of ovulation was maintained after four scheduled 24-h delays in tablet intake. STUDY DESIGN: One hundred thirty healthy women with proven ovulatory cycles were randomized, and 127 were treated with the drospirenone-only pill during two cycles. In treatment Group A (n=62), 24-h delays in tablet intake were...... inhibition by the new-generation oestrogen-free pill, containing 4-mg drospirenone for 24 days followed by a 4-day treatment-free period, was maintained despite four 24-h delays in tablet intake, so the impact of delayed intake on contraceptive reliability will be low....

  16. Spreadsheet modeling of optimal maintenance schedule for components in wear-out phase

    International Nuclear Information System (INIS)

    Artana, K.B.; Ishida, K.

    2002-01-01

    This paper addresses a method for determining the optimum maintenance schedule for components in the wear-out phase. The interval between maintenance for the components is optimized by minimizing the total cost. This consists of maintenance cost, operational cost, downtime cost and penalty cost. A decision to replace a component must also be taken when a component cannot attain the minimum reliability and availability index requirement. Premium solver platform, a spreadsheet-modeling tool, is utilized to model the optimization problem. Constraints, which are the considerations to be fulfilled, become the director of this process. A minimum and a maximum value are set on each constraint so as to give the working area of the optimization process. The optimization process investigates n-equally spaced maintenance at an interval of Tr. The increase in operational and maintenance costs due to the deterioration of the components is taken into account. This paper also performs a case study and sensitivity analysis on a liquid ring primer of a ship's bilge system

  17. Multiple time-scale optimization scheduling for islanded microgrids including PV, wind turbine, diesel generator and batteries

    DEFF Research Database (Denmark)

    Xiao, Zhao xia; Nan, Jiakai; Guerrero, Josep M.

    2017-01-01

    the adjustment of the day-ahead scheduling and giving priority to the use of renewable energy. According to the forecast of the critical and noncritical load, the wind speed, and the solar irradiation, mixed integer linear programming (MILP) optimization method is used to solve the multi-objective optimization......A multiple time-scale optimization scheduling including day ahead and short time for an islanded microgrid is presented. In this paper, the microgrid under study includes photovoltaics (PV), wind turbine (WT), diesel generator (DG), batteries, and shiftable loads. The study considers the maximum...... efficiency operation area for the diesel engine and the cost of the battery charge/discharge cycle losses. The day-ahead generation scheduling takes into account the minimum operational cost and the maximum load satisfaction as the objective function. Short-term optimal dispatch is based on minimizing...

  18. An Optimizing Space Data-Communications Scheduling Method and Algorithm with Interference Mitigation, Generalized for a Broad Class of Optimization Problems

    Science.gov (United States)

    Rash, James

    2014-01-01

    NASA's space data-communications infrastructure-the Space Network and the Ground Network-provide scheduled (as well as some limited types of unscheduled) data-communications services to user spacecraft. The Space Network operates several orbiting geostationary platforms (the Tracking and Data Relay Satellite System (TDRSS)), each with its own servicedelivery antennas onboard. The Ground Network operates service-delivery antennas at ground stations located around the world. Together, these networks enable data transfer between user spacecraft and their mission control centers on Earth. Scheduling data-communications events for spacecraft that use the NASA communications infrastructure-the relay satellites and the ground stations-can be accomplished today with software having an operational heritage dating from the 1980s or earlier. An implementation of the scheduling methods and algorithms disclosed and formally specified herein will produce globally optimized schedules with not only optimized service delivery by the space data-communications infrastructure but also optimized satisfaction of all user requirements and prescribed constraints, including radio frequency interference (RFI) constraints. Evolutionary algorithms, a class of probabilistic strategies for searching large solution spaces, is the essential technology invoked and exploited in this disclosure. Also disclosed are secondary methods and algorithms for optimizing the execution efficiency of the schedule-generation algorithms themselves. The scheduling methods and algorithms as presented are adaptable to accommodate the complexity of scheduling the civilian and/or military data-communications infrastructure within the expected range of future users and space- or ground-based service-delivery assets. Finally, the problem itself, and the methods and algorithms, are generalized and specified formally. The generalized methods and algorithms are applicable to a very broad class of combinatorial-optimization

  19. Optimal Control of a Delay-Varying Computer Virus Propagation Model

    OpenAIRE

    Ren, Jianguo; Xu, Yonghong; Zhang, Chunming

    2013-01-01

    By incorporating the objective of keeping a low number of infected nodes and a high number of recovered nodes at a lower cost into a known computer virus model (the delay-varying SIRC model) extended by introducing quarantine, a novel model is described by means of the optimal control strategy and theoretically analyzed. Through the comparison of simulation results, it is shown that the propagation of computer virus with varying latency period can be suppressed effectively by the optimal cont...

  20. Minimization of Load Variance in Power Grids—Investigation on Optimal Vehicle-to-Grid Scheduling

    Directory of Open Access Journals (Sweden)

    Kang Miao Tan

    2017-11-01

    Full Text Available The introduction of electric vehicles into the transportation sector helps reduce global warming and carbon emissions. The interaction between electric vehicles and the power grid has spurred the emergence of a smart grid technology, denoted as vehicle-to grid-technology. Vehicle-to-grid technology manages the energy exchange between a large fleet of electric vehicles and the power grid to accomplish shared advantages for the vehicle owners and the power utility. This paper presents an optimal scheduling of vehicle-to-grid using the genetic algorithm to minimize the power grid load variance. This is achieved by allowing electric vehicles charging (grid-to-vehicle whenever the actual power grid loading is lower than the target loading, while conducting electric vehicle discharging (vehicle-to-grid whenever the actual power grid loading is higher than the target loading. The vehicle-to-grid optimization algorithm is implemented and tested in MATLAB software (R2013a, MathWorks, Natick, MA, USA. The performance of the optimization algorithm depends heavily on the setting of the target load, power grid load and capability of the grid-connected electric vehicles. Hence, the performance of the proposed algorithm under various target load and electric vehicles’ state of charge selections were analysed. The effectiveness of the vehicle-to-grid scheduling to implement the appropriate peak load shaving and load levelling services for the grid load variance minimization is verified under various simulation investigations. This research proposal also recommends an appropriate setting for the power utility in terms of the selection of the target load based on the electric vehicle historical data.

  1. Delay-area trade-off for MPRM circuits based on hybrid discrete particle swarm optimization

    International Nuclear Information System (INIS)

    Jiang Zhidi; Wang Zhenhai; Wang Pengjun

    2013-01-01

    Polarity optimization for mixed polarity Reed—Muller (MPRM) circuits is a combinatorial issue. Based on the study on discrete particle swarm optimization (DPSO) and mixed polarity, the corresponding relation between particle and mixed polarity is established, and the delay-area trade-off of large-scale MPRM circuits is proposed. Firstly, mutation operation and elitist strategy in genetic algorithm are incorporated into DPSO to further develop a hybrid DPSO (HDPSO). Then the best polarity for delay and area trade-off is searched for large-scale MPRM circuits by combining the HDPSO and a delay estimation model. Finally, the proposed algorithm is testified by MCNC Benchmarks. Experimental results show that HDPSO achieves a better convergence than DPSO in terms of search capability for large-scale MPRM circuits. (semiconductor integrated circuits)

  2. LMI optimization approach to stabilization of time-delay chaotic systems

    International Nuclear Information System (INIS)

    Park, Ju H.; Kwon, O.M.

    2005-01-01

    Based on the Lyapunov stability theory and linear matrix inequality (LMI) technique, this paper proposes a novel control method for stabilization of a class of time-delay chaotic systems. A stabilization criterion is derived in terms of LMIs which can be easily solved by efficient convex optimization algorithms. A numerical example is included to show the advantage of the result derived

  3. AN OPTIMAL REPLENISHMENT POLICY FOR DETERIORATING ITEMS WITH RAMP TYPE DEMAND UNDER PERMISSIBLE DELAY IN PAYMENTS

    Directory of Open Access Journals (Sweden)

    Dr. Sanjay Jain

    2010-10-01

    Full Text Available The aim of this paper is to develop an optimal replenishment policy for inventory models of deteriorating items with ramp type demand under permissible delay in payments. Deterioration of items begins on their arrival in stock.  An example is also presented to illustrate the application of developed model.

  4. MDCT urography: retrospective determination of optimal delay time after intravenous contrast administration

    International Nuclear Information System (INIS)

    Meindl, Thomas; Coppenrath, Eva; Kahlil, Rami; Reiser, Maximilian F.; Mueller-Lisse, U.G.; Mueller-Lisse, Ulrike L.

    2006-01-01

    The optimal delay time after intravenous (i.v.) administration of contrast medium (CM) for opacifcation of the upper urinary tract (UUT) for multidetector computed tomography urography (MDCTU) was investigated. UUT opacification was retrospectively evaluated in 36 four-row MDCTU examinations. Single- (n=10) or dual-phase (n=26) MDCTU was performed with at least 5-min delay after i.v. CM. UUT was divided into four sections: intrarenal collecting system (IRCS), proximal, middle and distal ureter. Two independent readers rated UUT opacification: 1, none; 2, partial; 3, complete. Numbers and percentages of scores, and the 5%, 25%, 50%, 75% and 95% percentiles of delay time were calculated for each UUT section. After removing diseased segments, 344 segments were analysed. IRCS, proximal and middle ureter were completely opacified in 94% (81/86), 93% (80/86) and 77% (66/86) of cases, respectively. Median delay time was 15 min for complete opacification. The distal ureter was completely opacified in 37% (32/86) of cases and not opacified in 26% (22/86). Median delay time for complete opacification was 11 min with 25% and 75% percentiles of 10 and 16 min, respectively. At MDCTU, opacification of the IRCS, proximal and middle ureter was hardly sensitive to delay time. Delay times between 10 and 16 min were favourable in the distal ureter. (orig.)

  5. Modeling and optimization of tissue 10B concentration and dosimetry for arbitrary BPA-F infusion schedules in humans

    International Nuclear Information System (INIS)

    Kiger, W.S. III; Newton, T.H.; Palmer, M.R.

    2000-01-01

    Separate compartmental models have been derived for the concentration of 10 B resulting from BPA-F infusion in the central vascular space (i.e., blood or, more appropriately, plasma) and in glioblastoma multiforme and normal brain. By coupling the model for the temporal variation of 10 B concentration in the central vascular space with that for tissue, the dynamic behavior of the 10 B concentration and the resulting dosimetry in the relevant tissues and blood may be predicted for arbitrary infusion schedules. This coupled model may be used as a tool for identifying the optimal time for BNCT irradiation and optimal BPA-F infusion schedule (i.e., temporal targeting) in humans without the need for expensive and time-consuming pharmacokinetic studies for every infusion schedule considered. This model was used to analyze the concentration profiles resulting from a wide range of infusion schedules and their implications for dosimetry. (author)

  6. Optimal scheduling for enhanced coal bed methane production through CO2 injection

    International Nuclear Information System (INIS)

    Huang, Yuping; Zheng, Qipeng P.; Fan, Neng; Aminian, Kashy

    2014-01-01

    Highlights: • A novel deterministic optimization model for CO 2 -ECBM production scheduling. • Maximize the total profit from both sales of natural gas and CO 2 credits trading in the carbon market. • A stochastic model incorporating uncertainties and dynamics of NG price and CO 2 credit. - Abstract: Enhanced coal bed methane production with CO 2 injection (CO 2 -ECBM) is an effective technology for accessing the natural gas embedded in the traditionally unmineable coal seams. The revenue via this production process is generated not only by the sales of coal bed methane, but also by trading CO 2 credits in the carbon market. As the technology of CO 2 -ECBM becomes mature, its commercialization opportunities are also springing up. This paper proposes applicable mathematical models for CO 2 -ECBM production and compares the impacts of their production schedules on the total profit. A novel basic deterministic model for CO 2 -ECBM production including the technical and chemical details is proposed and then a multistage stochastic programming model is formulated in order to address uncertainties of natural gas price and CO 2 credit. Both models are nonlinear programming problems, which are solved by commercial nonlinear programming software BARON via GAMS. Numerical experiments show the benefits (e.g., expected profit gain) of using stochastic models versus deterministic models

  7. Optimal short-term operation schedule of a hydropower plant in a competitive electricity market

    International Nuclear Information System (INIS)

    Perez-Diaz, Juan I.; Wilhelmi, Jose R.; Arevalo, Luis A.

    2010-01-01

    This paper presents a dynamic programming model to solve the short-term scheduling problem of a hydropower plant that sells energy in a pool-based electricity market with the objective of maximizing the revenue. This is a nonlinear and non-concave problem subject to strong technical and strategic constraints, and in which discrete and continuous variables take part. The model described in this paper determines, in each hour of the planning horizon (typically from one day to one week), both the optimal number of units in operation (unit commitment) and the power to be generated by the committed units (generation dispatch). The power generated by each unit is considered as a nonlinear function of the actual water discharge and volume of the associated reservoir. The dependence of the units' efficiency and operating limits with the available gross head is also accounted for in this model. The application of this model to a real hydropower plant demonstrates its capabilities in providing the operation schedule that maximizes the revenue of the hydro plant while satisfying several constraints of different classes. In addition, the use of this model as a supporting tool to estimate the economic feasibility of a hydropower plant development project is also analyzed in the paper. (author)

  8. Optimal appointment scheduling with a stochastic server: Simulation based K-steps look-ahead selection method

    Directory of Open Access Journals (Sweden)

    Changchun Liu

    2018-10-01

    Full Text Available This paper studies the problem of scheduling a finite set of customers with stochastic service times for a single-server system. The objective is to minimize the waiting time of customers, the idle time of the server, and the lateness of the schedule. Because of the NP-hardness of the problem, the optimal schedule is notoriously hard to derive with reasonable computation times. Therefore, we develop a simulation based K-steps look-ahead selection method which can result in nearly optimal schedules within reasonable computation times. Furthermore, we study the different distributed service times, e.g., Exponential, Weibull and lognormal distribution and the results show that the proposed algorithm can obtain better results than the lag order approximation method proposed by Vink et al. (2015 [Vink, W., Kuiper, A., Kemper, B., & Bhulai, S. (2015. Optimal appointment scheduling in continuous time: The lag order approximation method. European Journal of Operational Research, 240(1, 213-219.]. Finally, a realistic appointment scheduling includes experiments to verify the good performance of the proposed method.

  9. Multiobjective Joint Optimization of Production Scheduling and Maintenance Planning in the Flexible Job-Shop Problem

    Directory of Open Access Journals (Sweden)

    Jianfei Ye

    2015-01-01

    Full Text Available In order to solve the joint optimization of production scheduling and maintenance planning problem in the flexible job-shop, a multiobjective joint optimization model considering the maximum completion time and maintenance costs per unit time is established based on the concept of flexible job-shop and preventive maintenance. A weighted sum method is adopted to eliminate the index dimension. In addition, a double-coded genetic algorithm is designed according to the problem characteristics. The best result under the circumstances of joint decision-making is obtained through multiple simulation experiments, which proves the validity of the algorithm. We can prove the superiority of joint optimization model by comparing the result of joint decision-making project with the result of independent decision-making project under fixed preventive maintenance period. This study will enrich and expand the theoretical framework and analytical methods of this problem; it provides a scientific decision analysis method for enterprise to make production plan and maintenance plan.

  10. Joint optimization of green vehicle scheduling and routing problem with time-varying speeds

    Science.gov (United States)

    Zhang, Dezhi; Wang, Xin; Ni, Nan; Zhang, Zhuo

    2018-01-01

    Based on an analysis of the congestion effect and changes in the speed of vehicle flow during morning and evening peaks in a large- or medium-sized city, the piecewise function is used to capture the rules of the time-varying speed of vehicles, which are very important in modelling their fuel consumption and CO2 emission. A joint optimization model of the green vehicle scheduling and routing problem with time-varying speeds is presented in this study. Extra wages during nonworking periods and soft time-window constraints are considered. A heuristic algorithm based on the adaptive large neighborhood search algorithm is also presented. Finally, a numerical simulation example is provided to illustrate the optimization model and its algorithm. Results show that, (1) the shortest route is not necessarily the route that consumes the least energy, (2) the departure time influences the vehicle fuel consumption and CO2 emissions and the optimal departure time saves on fuel consumption and reduces CO2 emissions by up to 5.4%, and (3) extra driver wages have significant effects on routing and departure time slot decisions. PMID:29466370

  11. Optimal harvesting of a stochastic delay logistic model with Lévy jumps

    International Nuclear Information System (INIS)

    Qiu, Hong; Deng, Wenmin

    2016-01-01

    The optimal harvesting problem of a stochastic time delay logistic model with Lévy jumps is considered in this article. We first show that the model has a unique global positive solution and discuss the uniform boundedness of its p th moment with harvesting. Then we prove that the system is globally attractive and asymptotically stable in distribution under our assumptions. Furthermore, we obtain the existence of the optimal harvesting effort by the ergodic method, and then we give the explicit expression of the optimal harvesting policy and maximum yield. (paper)

  12. Minimization of Load Variance in Power Grids—Investigation on Optimal Vehicle-to-Grid Scheduling

    DEFF Research Database (Denmark)

    Tan, Kang Miao; Ramachandaramurthy, Vigna K.; Yong, Jia Ying

    2017-01-01

    The introduction of electric vehicles into the transportation sector helps reduce global warming and carbon emissions. The interaction between electric vehicles and the power grid has spurred the emergence of a smart grid technology, denoted as vehicle-to grid-technology. Vehicle-to-grid technology...... manages the energy exchange between a large fleet of electric vehicles and the power grid to accomplish shared advantages for the vehicle owners and the power utility. This paper presents an optimal scheduling of vehicle-to-grid using the genetic algorithm to minimize the power grid load variance....... This is achieved by allowing electric vehicles charging (grid-to-vehicle) whenever the actual power grid loading is lower than the target loading, while conducting electric vehicle discharging (vehicle-to-grid) whenever the actual power grid loading is higher than the target loading. The vehicle...

  13. Hybrid Particle Swarm Optimization for Hybrid Flowshop Scheduling Problem with Maintenance Activities

    Science.gov (United States)

    Li, Jun-qing; Pan, Quan-ke; Mao, Kun

    2014-01-01

    A hybrid algorithm which combines particle swarm optimization (PSO) and iterated local search (ILS) is proposed for solving the hybrid flowshop scheduling (HFS) problem with preventive maintenance (PM) activities. In the proposed algorithm, different crossover operators and mutation operators are investigated. In addition, an efficient multiple insert mutation operator is developed for enhancing the searching ability of the algorithm. Furthermore, an ILS-based local search procedure is embedded in the algorithm to improve the exploitation ability of the proposed algorithm. The detailed experimental parameter for the canonical PSO is tuning. The proposed algorithm is tested on the variation of 77 Carlier and Néron's benchmark problems. Detailed comparisons with the present efficient algorithms, including hGA, ILS, PSO, and IG, verify the efficiency and effectiveness of the proposed algorithm. PMID:24883414

  14. Hybrid Particle Swarm Optimization for Hybrid Flowshop Scheduling Problem with Maintenance Activities

    Directory of Open Access Journals (Sweden)

    Jun-qing Li

    2014-01-01

    Full Text Available A hybrid algorithm which combines particle swarm optimization (PSO and iterated local search (ILS is proposed for solving the hybrid flowshop scheduling (HFS problem with preventive maintenance (PM activities. In the proposed algorithm, different crossover operators and mutation operators are investigated. In addition, an efficient multiple insert mutation operator is developed for enhancing the searching ability of the algorithm. Furthermore, an ILS-based local search procedure is embedded in the algorithm to improve the exploitation ability of the proposed algorithm. The detailed experimental parameter for the canonical PSO is tuning. The proposed algorithm is tested on the variation of 77 Carlier and Néron’s benchmark problems. Detailed comparisons with the present efficient algorithms, including hGA, ILS, PSO, and IG, verify the efficiency and effectiveness of the proposed algorithm.

  15. Hybrid particle swarm optimization for hybrid flowshop scheduling problem with maintenance activities.

    Science.gov (United States)

    Li, Jun-qing; Pan, Quan-ke; Mao, Kun

    2014-01-01

    A hybrid algorithm which combines particle swarm optimization (PSO) and iterated local search (ILS) is proposed for solving the hybrid flowshop scheduling (HFS) problem with preventive maintenance (PM) activities. In the proposed algorithm, different crossover operators and mutation operators are investigated. In addition, an efficient multiple insert mutation operator is developed for enhancing the searching ability of the algorithm. Furthermore, an ILS-based local search procedure is embedded in the algorithm to improve the exploitation ability of the proposed algorithm. The detailed experimental parameter for the canonical PSO is tuning. The proposed algorithm is tested on the variation of 77 Carlier and Néron's benchmark problems. Detailed comparisons with the present efficient algorithms, including hGA, ILS, PSO, and IG, verify the efficiency and effectiveness of the proposed algorithm.

  16. Energy-Aware Real-Time Task Scheduling for Heterogeneous Multiprocessors with Particle Swarm Optimization Algorithm

    Directory of Open Access Journals (Sweden)

    Weizhe Zhang

    2014-01-01

    Full Text Available Energy consumption in computer systems has become a more and more important issue. High energy consumption has already damaged the environment to some extent, especially in heterogeneous multiprocessors. In this paper, we first formulate and describe the energy-aware real-time task scheduling problem in heterogeneous multiprocessors. Then we propose a particle swarm optimization (PSO based algorithm, which can successfully reduce the energy cost and the time for searching feasible solutions. Experimental results show that the PSO-based energy-aware metaheuristic uses 40%–50% less energy than the GA-based and SFLA-based algorithms and spends 10% less time than the SFLA-based algorithm in finding the solutions. Besides, it can also find 19% more feasible solutions than the SFLA-based algorithm.

  17. Spectrum optimization-based chaotification using time-delay feedback control

    International Nuclear Information System (INIS)

    Zhou Jiaxi; Xu Daolin; Zhang Jing; Liu Chunrong

    2012-01-01

    Highlights: ► A time-delay feedback controller is designed for chaotification. ► A spectrum optimization method is proposed to determine chaotification parameters. ► Numerical examples verify the spectrum optimization- based chaotification method. ► Engineering application in line spectrum reconfiguration is demonstrated. - Abstract: In this paper, a spectrum optimization method is developed for chaotification in conjunction with an application in line spectrum reconfiguration. A key performance index (the objective function) based on Fourier spectrum is specially devised with the idea of suppressing spectrum spikes and broadening frequency band. Minimization of the index empowered by a genetic algorithm enables to locate favorable parameters of the time-delay feedback controller, by which a line spectrum of harmonic vibration can be transformed into a broad-band continuous spectrum of chaotic motion. Numerical simulations are carried out to verify the feasibility of the method and to demonstrate its effectiveness of chaotifying a 2-DOFs linear mechanical system.

  18. Model Predictive Optimal Control of a Time-Delay Distributed-Parameter Systems

    Science.gov (United States)

    Nguyen, Nhan

    2006-01-01

    This paper presents an optimal control method for a class of distributed-parameter systems governed by first order, quasilinear hyperbolic partial differential equations that arise in many physical systems. Such systems are characterized by time delays since information is transported from one state to another by wave propagation. A general closed-loop hyperbolic transport model is controlled by a boundary control embedded in a periodic boundary condition. The boundary control is subject to a nonlinear differential equation constraint that models actuator dynamics of the system. The hyperbolic equation is thus coupled with the ordinary differential equation via the boundary condition. Optimality of this coupled system is investigated using variational principles to seek an adjoint formulation of the optimal control problem. The results are then applied to implement a model predictive control design for a wind tunnel to eliminate a transport delay effect that causes a poor Mach number regulation.

  19. Short term hydroelectric power system scheduling with wind turbine generators using the multi-pass iteration particle swarm optimization approach

    International Nuclear Information System (INIS)

    Lee, T.-Y.

    2008-01-01

    This paper uses multi-pass iteration particle swarm optimization (MIPSO) to solve short term hydroelectric generation scheduling of a power system with wind turbine generators. MIPSO is a new algorithm for solving nonlinear optimal scheduling problems. A new index called iteration best (IB) is incorporated into particle swarm optimization (PSO) to improve solution quality. The concept of multi-pass dynamic programming is applied to modify PSO further and improve computation efficiency. The feasible operational regions of the hydro units and pumped storage plants over the whole scheduling time range must be determined before applying MIPSO to the problem. Wind turbine power generation then shaves the power system load curves. Next, MIPSO calculates hydroelectric generation scheduling. It begins with a coarse time stage and searching space and refines the time interval between two time stages and the search spacing pass by pass (iteration). With the cooperation of agents called particles, the near optimal solution of the scheduling problem can be effectively reached. The effects of wind speed uncertainty were also considered in this paper. The feasibility of the new algorithm is demonstrated by a numerical example, and MIPSO solution quality and computation efficiency are compared to those of other algorithms

  20. Optimizing Water Use and Hydropower Production in Operational Reservoir System Scheduling with RiverWare

    Science.gov (United States)

    Magee, T. M.; Zagona, E. A.

    2017-12-01

    Practical operational optimization of multipurpose reservoir systems is challenging for several reasons. Each purpose has its own constraints which may conflict with those of other purposes. While hydropower generation typically provides the bulk of the revenue, it is also among the lowest priority purposes. Each river system has important details that are specific to the location such as hydrology, reservoir storage capacity, physical limitations, bottlenecks, and the continuing evolution of operational policy. In addition, reservoir operations models include discrete, nonlinear, and nonconvex physical processes and if-then operating policies. Typically, the forecast horizon for scheduling needs to be extended far into the future to avoid near term (e.g., a few hours or a day) scheduling decisions that result in undesirable future states; this makes the computational effort much larger than may be expected. Put together, these challenges lead to large and customized mathematical optimization problems which must be solved efficiently to be of practical use. In addition, the solution process must be robust in an operational setting. We discuss a unique modeling approach in RiverWare that meets these challenges in an operational setting. The approach combines a Preemptive Linear Goal Programming optimization model to handle prioritized policies complimented by preprocessing and postprocessing with Rulebased Simulation to improve the solution with regard to nonlinearities, discrete issues, and if-then logic. An interactive policy language with a graphical user interface allows modelers to customize both the optimization and simulation based on the unique aspects of the policy for their system while the routine physical aspect of operations are modeled automatically. The modeler is aided by a set of compiled predefined functions and functions shared by other modelers. We illustrate the success of the approach with examples from daily use at the Tennessee Valley

  1. HYBRIDIZATION OF MODIFIED ANT COLONY OPTIMIZATION AND INTELLIGENT WATER DROPS ALGORITHM FOR JOB SCHEDULING IN COMPUTATIONAL GRID

    Directory of Open Access Journals (Sweden)

    P. Mathiyalagan

    2013-10-01

    Full Text Available As grid is a heterogeneous environment, finding an optimal schedule for the job is always a complex task. In this paper, a hybridization technique using intelligent water drops and Ant colony optimization which are nature-inspired swarm intelligence approaches are used to find the best resource for the job. Intelligent water drops involves in finding out all matching resources for the job requirements and the routing information (optimal path to reach those resources. Ant Colony optimization chooses the best resource among all matching resources for the job. The objective of this approach is to converge to the optimal schedule faster, minimize the make span of the job, improve load balancing of resources and efficient utilization of available resources.

  2. The Application of Time-Delay Dependent H∞ Control Model in Manufacturing Decision Optimization

    Directory of Open Access Journals (Sweden)

    Haifeng Guo

    2015-01-01

    Full Text Available This paper uses a time-delay dependent H∞ control model to analyze the effect of manufacturing decisions on the process of transmission from resources to capability. We establish a theoretical framework of manufacturing management process based on three terms: resource, manufacturing decision, and capability. Then we build a time-delay H∞ robust control model to analyze the robustness of manufacturing management. With the state feedback controller between manufacturing resources and decision, we find that there is an optimal decision to adjust the process of transmission from resources to capability under uncertain environment. Finally, we provide an example to prove the robustness of this model.

  3. Global stability, periodic solutions, and optimal control in a nonlinear differential delay model

    Directory of Open Access Journals (Sweden)

    Anatoli F. Ivanov

    2010-09-01

    Full Text Available A nonlinear differential equation with delay serving as a mathematical model of several applied problems is considered. Sufficient conditions for the global asymptotic stability and for the existence of periodic solutions are given. Two particular applications are treated in detail. The first one is a blood cell production model by Mackey, for which new periodicity criteria are derived. The second application is a modified economic model with delay due to Ramsey. An optimization problem for a maximal consumption is stated and solved for the latter.

  4. Optimism and positive and negative feelings in parents of young children with developmental delay.

    Science.gov (United States)

    Kurtz-Nelson, E; McIntyre, L L

    2017-07-01

    Parents' positive and negative feelings about their young children influence both parenting behaviour and child problem behaviour. Research has not previously examined factors that contribute to positive and negative feelings in parents of young children with developmental delay (DD). The present study sought to examine whether optimism, a known protective factor for parents of children with DD, was predictive of positive and negative feelings for these parents. Data were collected from 119 parents of preschool-aged children with developmental delay. Two separate hierarchical linear regression analyses were conducted to determine if optimism significantly predicted positive feelings and negative feelings and whether optimism moderated relations between parenting stress and parent feelings. Increased optimism was found to predict increased positive feelings and decreased negative feelings after controlling for child problem behaviour and parenting stress. In addition, optimism was found to moderate the relation between parenting stress and positive feelings. Results suggest that optimism may impact how parents perceive their children with DD. Future research should examine how positive and negative feelings impact positive parenting behaviour and the trajectory of problem behaviour specifically for children with DD. © 2017 MENCAP and International Association of the Scientific Study of Intellectual and Developmental Disabilities and John Wiley & Sons Ltd.

  5. Optimization of SFQ Logic Gate Considering Dependence of its Signal Propagation Delay on the Bias Voltage

    Science.gov (United States)

    Otsubo, Mikio; Yamanashi, Yuki; Yoshikawa, Nobuyuki

    Superconductive single flux quantum (SFQ) digital circuits can operate at a clock frequency of several tens of gigahertz. The operating margin of an SFQ logic circuit generally decreases with an increase in the operating frequency because of the timing error in the low-bias region caused by the difference in bias dependence of the signal-propagation delay between the data and clock lines. We proposed an improvement in the operating margin by controlling the dependence of the signal-propagation time on the bias voltage. In the present study, we investigated a new optimization method for an SFQ logic gate. We developed a new circuit parameter optimizer, which takes into account not only the bias margin but also the dependence of the signal-propagation delay on the bias voltage. We defined an appropriate evaluation function for the optimization. From the result of the optimization using the defined evaluation function, we designed and demonstrated an SFQ AND gate optimized using the new optimizer.

  6. Power Optimization of Multimode Mobile Embedded Systems with Workload-Delay Dependency

    Directory of Open Access Journals (Sweden)

    Hoeseok Yang

    2016-01-01

    Full Text Available This paper proposes to take the relationship between delay and workload into account in the power optimization of microprocessors in mobile embedded systems. Since the components outside a device continuously change their values or properties, the workload to be handled by the systems becomes dynamic and variable. This variable workload is formulated as a staircase function of the delay taken at the previous iteration in this paper and applied to the power optimization of DVFS (dynamic voltage-frequency scaling. In doing so, a graph representation of all possible workload/mode changes during the lifetime of a device, Workload Transition Graph (WTG, is proposed. Then, the power optimization problem is transformed into finding a cycle (closed walk in WTG which minimizes the average power consumption over it. Out of the obtained optimal cycle of WTG, one can derive the optimal power management policy of the target device. It is shown that the proposed policy is valid for both continuous and discrete DVFS models. The effectiveness of the proposed power optimization policy is demonstrated with the simulation results of synthetic and real-life examples.

  7. Optimal Charging Schedule Planning and Economic Analysis for Electric Bus Charging Stations

    Directory of Open Access Journals (Sweden)

    Rong-Ceng Leou

    2017-04-01

    Full Text Available The battery capacity of electric buses (EB used for public transportation is greater than that of electric cars, and the charging power is also several times greater than that used in electric cars; this can result in high energy consumption and negatively impact power distribution networks. This paper proposes a framework to determine the optimal contracted power capacity and charging schedule of an EB charging station in such a way that energy costs can be reduced. A mathematical model of controlled charging, which includes the capacity and energy charges of the station, was developed to minimize costs. The constraints of the model include the charging characteristics of an EB and the operational guidelines of the bus company. A practical EB charging station was used to verify the proposed model. The financial viability of this EB charging station is also studied in this paper. The economic analysis model for this charging station considers investment and operational costs, and the operational revenue. Sensitivity analyses with respect to some key parameters are also performed in this paper. Based on actual operational routes and EB charging schemes, test results indicate that the EB charging station investment is feasible, and the planning model proposed can be used to determine optimal station power capacity and minimize energy costs.

  8. Optimal Fair Scheduling in S-TDMA Sensor Networks for Monitoring River Plumes

    Directory of Open Access Journals (Sweden)

    Miguel-Angel Luque-Nieto

    2016-01-01

    Full Text Available Underwater wireless sensor networks (UWSNs are a promising technology to provide oceanographers with environmental data in real time. Suitable network topologies to monitor estuaries are formed by strings coming together to a sink node. This network may be understood as an oriented graph. A number of MAC techniques can be used in UWSNs, but Spatial-TDMA is preferred for fixed networks. In this paper, a scheduling procedure to obtain the optimal fair frame is presented, under ideal conditions of synchronization and transmission errors. The main objective is to find the theoretical maximum throughput by overlapping the transmissions of the nodes while keeping a balanced received data rate from each sensor, regardless of its location in the network. The procedure searches for all cliques of the compatibility matrix of the network graph and solves a Multiple-Vector Bin Packing (MVBP problem. This work addresses the optimization problem and provides analytical and numerical results for both the minimum frame length and the maximum achievable throughput.

  9. On the optimal scheduling of periodic tests and maintenance for reliable redundant components

    International Nuclear Information System (INIS)

    Courtois, Pierre-Jacques; Delsarte, Philippe

    2006-01-01

    Periodically, some m of the n redundant components of a dependable system may have to be taken out of service for inspection, testing or preventive maintenance. The system is then constrained to operate with lower (n-m) redundancy and thus with less reliability during these periods. However, more frequent periodic inspections decrease the probability that a component fail undetected in the time interval between successive inspections. An optimal time schedule of periodic preventive operations arises from these two conflicting factors, balancing the loss of redundancy during inspections against the reliability benefits of more frequent inspections. Considering no other factor than this decreased redundancy at inspection time, this paper demonstrates the existence of an optimal interval between inspections, which maximizes the mean time between system failures. By suitable transformations and variable identifications, an analytic closed form expression of the optimum is obtained for the general (m, n) case. The optimum is shown to be unique within the ranges of parameter values valid in practice; its expression is easy to evaluate and shown to be useful to analyze and understand the influence of these parameters. Inspections are assumed to be perfect, i.e. they cause no component failure by themselves and leave no failure undetected. In this sense, the optimum determines a lowest bound for the system failure rate that can be achieved by a system of n-redundant components, m of which require for inspection or maintenance recurrent periods of unavailability of length t. The model and its general closed form solution are believed to be new . Previous work had computed optimal values for an estimation of a time average of system unavailability, but by numerical procedures only and with different numerical approximations, other objectives and model assumptions (one component only inspected at a time), and taking into account failures caused by testing itself, repair and

  10. Discrete particle swarm optimization to solve multi-objective limited-wait hybrid flow shop scheduling problem

    Science.gov (United States)

    Santosa, B.; Siswanto, N.; Fiqihesa

    2018-04-01

    This paper proposes a discrete Particle Swam Optimization (PSO) to solve limited-wait hybrid flowshop scheduing problem with multi objectives. Flow shop schedulimg represents the condition when several machines are arranged in series and each job must be processed at each machine with same sequence. The objective functions are minimizing completion time (makespan), total tardiness time, and total machine idle time. Flow shop scheduling model always grows to cope with the real production system accurately. Since flow shop scheduling is a NP-Hard problem then the most suitable method to solve is metaheuristics. One of metaheuristics algorithm is Particle Swarm Optimization (PSO), an algorithm which is based on the behavior of a swarm. Originally, PSO was intended to solve continuous optimization problems. Since flow shop scheduling is a discrete optimization problem, then, we need to modify PSO to fit the problem. The modification is done by using probability transition matrix mechanism. While to handle multi objectives problem, we use Pareto Optimal (MPSO). The results of MPSO is better than the PSO because the MPSO solution set produced higher probability to find the optimal solution. Besides the MPSO solution set is closer to the optimal solution

  11. Optimal coordinated scheduling of combined heat and power fuel cell, wind, and photovoltaic units in micro grids considering uncertainties

    International Nuclear Information System (INIS)

    Bornapour, Mosayeb; Hooshmand, Rahmat-Allah; Khodabakhshian, Amin; Parastegari, Moein

    2016-01-01

    In this paper, a stochastic model is proposed for coordinated scheduling of combined heat and power units in micro grid considering wind turbine and photovoltaic units. Uncertainties of electrical market price; the speed of wind and solar radiation are considered using a scenario-based method. In the method, scenarios are generated using roulette wheel mechanism based on probability distribution functions of input random variables. Using this method, the probabilistic specifics of the problem are distributed and the problem is converted to a deterministic one. The type of the objective function, coordinated scheduling of combined heat and power, wind turbine, and photovoltaic units change this problem to a mixed integer nonlinear one. Therefore to solve this problem modified particle swarm optimization algorithm is employed. The mentioned uncertainties lead to an increase in profit. Moreover, the optimal coordinated scheduling of renewable energy resources and thermal units in micro grids increase the total profit. In order to evaluate the performance of the proposed method, its performance is executed on modified 33 bus distributed system as a micro grid. - Highlights: • Stochastic model is proposed for coordinated scheduling of renewable energy sources. • The effect of combined heat and power is considered. • Maximizing profits of micro grid is considered as objective function. • Considering the uncertainties of problem lead to profit increasing. • Optimal scheduling of renewable energy sources and thermal units increases profit.

  12. Optimal deployment schedule of an active twist rotor for performance enhancement and vibration reduction in high-speed flights

    Directory of Open Access Journals (Sweden)

    Young H. YOU

    2017-08-01

    Full Text Available The best active twist schedules exploiting various waveform types are sought taking advantage of the global search algorithm for the reduction of hub vibration and/or power required of a rotor in high-speed conditions. The active twist schedules include two non-harmonic inputs formed based on segmented step functions as well as the simple harmonic waveform input. An advanced Particle Swarm assisted Genetic Algorithm (PSGA is employed for the optimizer. A rotorcraft Computational Structural Dynamics (CSD code CAMRAD II is used to perform the rotor aeromechanics analysis. A Computation Fluid Dynamics (CFD code is coupled with CSD for verification and some physical insights. The PSGA optimization results are verified against the parameter sweep study performed using the harmonic actuation. The optimum twist schedules according to the performance and/or vibration reduction strategy are obtained and their optimization gains are compared between the actuation cases. A two-phase non-harmonic actuation schedule demonstrates the best outcome in decreasing the power required while a four-phase non-harmonic schedule results in the best vibration reduction as well as the simultaneous reductions in the power required and vibration. The mechanism of reduction to the performance gains is identified illustrating the section airloads, angle-of-attack distribution, and elastic twist deformation predicted by the present approaches.

  13. Meta-heuristic methods for optimization and application to material flow control and scheduling in manufacturing; Butsuryu scheduling no tame no system saitekika meta senryaku

    Energy Technology Data Exchange (ETDEWEB)

    Konishi, M. [Kobe Steel, Ltd., Kobe (Japan)

    1996-09-01

    This paper introduces meta-heuristic methods for system optimization for material flow scheduling as well as their applications. The systems are intended to optimize combinations which determine such variables as selection of transport routes in and out of a factory, ratio of transport vehicles, and ratio of product orders to facilities. The meta-heuristic methods include the simulated annealing (SA) algorithm and the genetic algorithm (GA). The SA method is a method to search an optimal solution by utilizing combination optimization and analogy in the statistical dynamics. Although the system has limitation in the scope of application, it is characterized in that the setting of vicinity structure utilizing experience is effective. The GA method is a collective search method which models after the evolution mechanism of living organisms, and is characterized by parallel search on a plurality of search points. The applications of the SA method include a system to optimize limits of receiving product orders (shipment plans) in an expanded copper plate manufacturing factory. The applications of the GA method include optimization of a problem to allot a plurality of orders to a plurality of slabs. A method that can be comparable to the GA and SA methods is the expert system. 11 refs., 8 figs., 1 tab.

  14. Residual Stress Developed During the Cure of Thermosetting Polymers: Optimizing Cure Schedule to Minimize Stress.

    Energy Technology Data Exchange (ETDEWEB)

    Kropka, Jamie Michael; Stavig, Mark E.; Jaramillo, Rex

    2016-06-01

    When thermosetting polymers are used to bond or encapsulate electrical, mechanical or optical assemblies, residual stress, which often affects the performance and/or reliability of these devices, develops within the structure. The Thin-Disk-on-Cylinder structural response test is demonstrated as a powerful tool to design epoxy encapsulant cure schedules to reduce residual stress, even when all the details of the material evolution during cure are not explicitly known. The test's ability to (1) distinguish between cohesive and adhesive failure modes and (2) demonstrate methodologies to eliminate failure and reduce residual stress, make choices of cure schedules that optimize stress in the encapsulant unambiguous. For the 828/DEA/GMB material in the Thin-Disk-on-Cylinder geometry, the stress associated with cure is significant and outweighs that associated with cool down from the final cure temperature to room temperature (for measured lid strain, Scure I > I I e+h erma * II) * The difference between the final cure temperature and 1 1 -- the temperature at which the material gels, Tf-T ge i, was demonstrated to be a primary factor in determining the residual stress associated with cure. Increasing T f -T ge i leads to a reduction in cure stress that is described as being associated with balancing some of the 828/DEA/GMB cure shrinkage with thermal expansion. The ability to tune residual stress associated with cure by controlling T f -T ge i would be anticipated to translate to other thermosetting encapsulation materials, but the times and temperatures appropriate for a given material may vary widely.

  15. Integrated Optimization of Service-Oriented Train Plan and Schedule on Intercity Rail Network with Varying Demand

    Directory of Open Access Journals (Sweden)

    Wenliang Zhou

    2015-01-01

    Full Text Available For a better service level of a train operating plan, we propose an integrated optimization method of train planning and train scheduling, which generally are optimized, respectively. Based on the cost analysis of both passengers travelling and enterprises operation, and the constraint analysis of trains operation, we construct a multiobjective function and build an integrated optimization model with the aim of reducing both passenger travel costs and enterprise operating costs. Then, a solving algorithm is established based on the simulated annealing algorithm. Finally, using as an example the Changzhutan intercity rail network, as an example we analyze the optimized results and the influence of the model parameters on the results.

  16. Optimal model-based deficit irrigation scheduling using AquaCrop: a simulation study with cotton, potato and tomato

    DEFF Research Database (Denmark)

    Linker, Raphael; Ioslovich, Ilya; Sylaios, Georgios

    2016-01-01

    variables are the irrigation amounts for each day of the season. The objective function is the expected yield calculated with the use of a model. In the present work we solved this optimization problem for three crops modeled by the model AquaCrop. This optimization problem is non-trivial due to the non......-smooth behavior of the objective function and the fact that it involves multiple integer variables. We developed an optimization scheme for generating sub-optimal irrigation schedules that take implicitly into account the response of the crop to water stress, and used these as initial guesses for a full...

  17. Design and implementation of a delay-optimized universal programmable routing circuit for FPGAs

    International Nuclear Information System (INIS)

    Wu Fang; Zhang Huowen; Lai Jinmei; Wang Yuan; Chen Liguang; Duan Lei; Tong Jiarong

    2009-01-01

    This paper presents a universal field programmable gate array (FPGA) programmable routing circuit, focusing primarily on a delay optimization. Under the precondition of the routing resource's flexibility and routability, the number of programmable interconnect points (PIP) is reduced, and a multiplexer (MUX) plus a BUFFER structure is adopted as the programmable switch. Also, the method of offset lines and the method of complementary hanged end-lines are applied to the TILE routing circuit and the I/O routing circuit, respectively. All of the above features ensure that the whole FPGA chip is highly repeatable, and the signal delay is uniform and predictable over the total chip. Meanwhile, the BUFFER driver is optimized to decrease the signal delay by up to 5%. The proposed routing circuit is applied to the Fudan programmable device (FDP) FPGA, which has been taped out with an SMIC 0.18-μm logic 1P6M process. The test result shows that the programmable routing resource works correctly, and the signal delay over the chip is highly uniform and predictable.

  18. Optimal Financing Order Decisions of a Supply Chain under the Retailer's Delayed Payment

    Directory of Open Access Journals (Sweden)

    Honglin Yang

    2014-01-01

    Full Text Available In real supply chain, a capital-constrained retailer has two typical payment choices: the up-front payment to receive a high discount price or the delayed payment to reduce capital pressure. We compare with the efficiency of optimal decisions of different participants, that is, supplier, retailer, and bank, under both types of payments based on a game equilibrium analysis. It shows that under the equilibrium, the delayed payment leads to a greater optimal order quantity from the retailer compared to the up-front payment and, thus, improves the whole benefit of the supply chain. The numerical simulation for the random demand following a uniform distribution further verifies our findings. This study provides novel evidence that a dominant supplier who actively offers trade credit helps enhance the whole efficiency of a supply chain.

  19. An Improved Particle Swarm Optimization for Selective Single Machine Scheduling with Sequence Dependent Setup Costs and Downstream Demands

    Directory of Open Access Journals (Sweden)

    Kun Li

    2015-01-01

    Full Text Available This paper investigates a special single machine scheduling problem derived from practical industries, namely, the selective single machine scheduling with sequence dependent setup costs and downstream demands. Different from traditional single machine scheduling, this problem further takes into account the selection of jobs and the demands of downstream lines. This problem is formulated as a mixed integer linear programming model and an improved particle swarm optimization (PSO is proposed to solve it. To enhance the exploitation ability of the PSO, an adaptive neighborhood search with different search depth is developed based on the decision characteristics of the problem. To improve the search diversity and make the proposed PSO algorithm capable of getting out of local optimum, an elite solution pool is introduced into the PSO. Computational results based on extensive test instances show that the proposed PSO can obtain optimal solutions for small size problems and outperform the CPLEX and some other powerful algorithms for large size problems.

  20. Optimal control strategy for an impulsive stochastic competition system with time delays and jumps

    Science.gov (United States)

    Liu, Lidan; Meng, Xinzhu; Zhang, Tonghua

    2017-07-01

    Driven by both white and jump noises, a stochastic delayed model with two competitive species in a polluted environment is proposed and investigated. By using the comparison theorem of stochastic differential equations and limit superior theory, sufficient conditions for persistence in mean and extinction of two species are established. In addition, we obtain that the system is asymptotically stable in distribution by using ergodic method. Furthermore, the optimal harvesting effort and the maximum of expectation of sustainable yield (ESY) are derived from Hessian matrix method and optimal harvesting theory of differential equations. Finally, some numerical simulations are provided to illustrate the theoretical results.

  1. Delay Specific Investigations on QoS Scheduling Schemes for Real-Time Traffic in Packet Switched Networks

    OpenAIRE

    P.S.Prakash; S.Selvan

    2008-01-01

    Packet switched data network like Internet, which has traditionally supported throughput sensitive applications such as email and file transfer, is increasingly supporting delay-sensitive multimedia applications such as interactive video. These delaysensitive applications would often rather sacrifice some throughput for better delay. Unfortunately, the current packet switched network does not offer choices, but instead provides monolithic best-effort service to all applic...

  2. Unified approach for the optimization of energy and water in multipurpose batch plants using a flexible scheduling framework

    CSIR Research Space (South Africa)

    Adekola, O

    2013-05-01

    Full Text Available & Engineering Chemistry Research Vol. 52(25)/ pp 8488-8506 Unified Approach for the Optimization of Energy and Water in Multipurpose Batch Plants Using a Flexible Scheduling Framework Omobolanle Adekola,† Jane D. Stamp,† Thokozani Majozi,*,†,‡ Anurag...

  3. Maintenance of ovulation inhibition with a new progestogen-only pill containing drospirenone after scheduled 24-h delays in pill intake.

    Science.gov (United States)

    Duijkers, Ingrid J M; Heger-Mahn, Doris; Drouin, Dominique; Colli, Enrico; Skouby, Sven

    2016-04-01

    Traditional progestogen-only pills (POPs) have stringent daily timing and missed pill rules that might affect contraceptive reliability. A new-generation oestrogen-free pill has been developed, containing 4-mg drospirenone with a unique regimen of 24 active treatment days followed by four placebo tablets. A previous study showed that this new drospirenone-only pill effectively inhibited ovulation. Clinical efficacy, however, can be affected by compliance, and delayed or forgotten pill intake often occurs in daily life. The aim of this study was to investigate if inhibition of ovulation was maintained after four scheduled 24-h delays in tablet intake. One hundred thirty healthy women with proven ovulatory cycles were randomized, and 127 were treated with the drospirenone-only pill during two cycles. In treatment Group A (n=62), 24-h delays in tablet intake were scheduled on days 3, 6, 11 and 22 during Cycle 2 and, in treatment Group B (n=65) during Cycle 1, respectively. Ovulation was defined as disappearance or persistence of a large follicle and progesterone levels higher than 5 ng/mL for at least 5 consecutive days. The overall ovulation rate was 0.8%; only one subject in Group A fulfilled the ovulation criteria in Cycle 2. Follicular diameters in the regular-intake and the delayed-intake cycles were similar. Despite the 4-day hormone-free period and multiple intentional 24-h delays in tablet intake, ovulation inhibition was maintained. This property distinguishes this new-generation oestrogen-free pill from traditional POPs by allowing the same "safety window" or flexibility in intake as combined oral contraceptives without compromising contraceptive reliability. Delayed or forgotten pill intake is very common. Ovulation inhibition by the new-generation oestrogen-free pill, containing 4-mg drospirenone for 24 days followed by a 4-day treatment-free period, was maintained despite four 24-h delays in tablet intake, so the impact of delayed intake on contraceptive

  4. Optimal stochastic reactive power scheduling in a microgrid considering voltage droop scheme of DGs and uncertainty of wind farms

    International Nuclear Information System (INIS)

    Khorramdel, Benyamin; Raoofat, Mahdi

    2012-01-01

    Distributed Generators (DGs) in a microgrid may operate in three different reactive power control strategies, including PV, PQ and voltage droop schemes. This paper proposes a new stochastic programming approach for reactive power scheduling of a microgrid, considering the uncertainty of wind farms. The proposed algorithm firstly finds the expected optimal operating point of each DG in V-Q plane while the wind speed is a probabilistic variable. A multi-objective function with goals of loss minimization, reactive power reserve maximization and voltage security margin maximization is optimized using a four-stage multi-objective nonlinear programming. Then, using Monte Carlo simulation enhanced by scenario reduction technique, the proposed algorithm simulates actual condition and finds optimal operating strategy of DGs. Also, if any DGs are scheduled to operate in voltage droop scheme, the optimum droop is determined. Also, in the second part of the research, to enhance the optimality of the results, PSO algorithm is used for the multi-objective optimization problem. Numerical examples on IEEE 34-bus test system including two wind turbines are studied. The results show the benefits of voltage droop scheme for mitigating the impacts of the uncertainty of wind. Also, the results show preference of PSO method in the proposed approach. -- Highlights: ► Reactive power scheduling in a microgrid considering loss and voltage security. ► Stochastic nature of wind farms affects reactive power scheduling and is considered. ► Advantages of using the voltage droop characteristics of DGs in voltage security are shown. ► Power loss, voltage security and VAR reserve are three goals of a multi-objective optimization. ► Monte Carlo method with scenario reduction is used to determine optimal control strategy of DGs.

  5. Scheduling Multilevel Deadline-Constrained Scientific Workflows on Clouds Based on Cost Optimization

    Directory of Open Access Journals (Sweden)

    Maciej Malawski

    2015-01-01

    Full Text Available This paper presents a cost optimization model for scheduling scientific workflows on IaaS clouds such as Amazon EC2 or RackSpace. We assume multiple IaaS clouds with heterogeneous virtual machine instances, with limited number of instances per cloud and hourly billing. Input and output data are stored on a cloud object store such as Amazon S3. Applications are scientific workflows modeled as DAGs as in the Pegasus Workflow Management System. We assume that tasks in the workflows are grouped into levels of identical tasks. Our model is specified using mathematical programming languages (AMPL and CMPL and allows us to minimize the cost of workflow execution under deadline constraints. We present results obtained using our model and the benchmark workflows representing real scientific applications in a variety of domains. The data used for evaluation come from the synthetic workflows and from general purpose cloud benchmarks, as well as from the data measured in our own experiments with Montage, an astronomical application, executed on Amazon EC2 cloud. We indicate how this model can be used for scenarios that require resource planning for scientific workflows and their ensembles.

  6. Adaptive Transmitter Optimization in Multiuser Multiantenna Systems: Theoretical Limits, Effect of Delays, and Performance Enhancements

    Directory of Open Access Journals (Sweden)

    Samardzija Dragan

    2005-01-01

    Full Text Available The advances in programmable and reconfigurable radios have rendered feasible transmitter optimization schemes that can greatly improve the performance of multiple-antenna multiuser systems. Reconfigurable radio platforms are particularly suitable for implementation of transmitter optimization at the base station. We consider the downlink of a wireless system with multiple transmit antennas at the base station and a number of mobile terminals (i.e., users each with a single receive antenna. Under an average transmit power constraint, we consider the maximum achievable sum data rates in the case of (1 zero-forcing (ZF spatial prefilter, (2 modified zero-forcing (MZF spatial prefilter, and (3 triangularization spatial prefilter coupled with dirty-paper coding (DPC transmission scheme. We show that the triangularization with DPC approaches the closed-loop MIMO rates (upper bound for higher SNRs. Further, the MZF solution performs very well for lower SNRs, while for higher SNRs, the rates for the ZF solution converge to the MZF rates. An important impediment that degrades the performance of such transmitter optimization schemes is the delay in channel state information (CSI. We characterize the fundamental limits of performance in the presence of delayed CSI and then propose performance enhancements using a linear MMSE predictor of the CSI that can be used in conjunction with transmitter optimization in multiple-antenna multiuser systems.

  7. A Three-Stage Optimization Algorithm for the Stochastic Parallel Machine Scheduling Problem with Adjustable Production Rates

    Directory of Open Access Journals (Sweden)

    Rui Zhang

    2013-01-01

    Full Text Available We consider a parallel machine scheduling problem with random processing/setup times and adjustable production rates. The objective functions to be minimized consist of two parts; the first part is related with the due date performance (i.e., the tardiness of the jobs, while the second part is related with the setting of machine speeds. Therefore, the decision variables include both the production schedule (sequences of jobs and the production rate of each machine. The optimization process, however, is significantly complicated by the stochastic factors in the manufacturing system. To address the difficulty, a simulation-based three-stage optimization framework is presented in this paper for high-quality robust solutions to the integrated scheduling problem. The first stage (crude optimization is featured by the ordinal optimization theory, the second stage (finer optimization is implemented with a metaheuristic called differential evolution, and the third stage (fine-tuning is characterized by a perturbation-based local search. Finally, computational experiments are conducted to verify the effectiveness of the proposed approach. Sensitivity analysis and practical implications are also discussed.

  8. Optimizing Fire Department Operations Through Work Schedule Analysis, Alternative Staffing, and Nonproductive Time Reduction

    Science.gov (United States)

    2014-09-01

    fatigue attributed to work-related stressors .19 On the other hand, research has shown that the 48/96 schedule exacerbates sleep deprivation issues...health and wellness initiatives, brown-out, fire department funding, peak-usage staffing, four-person staffing, schedule modification, sleep deprivation ...to a significant sleep deprivation risk that impacts the employee’s ability to function at peak levels.7 The 10/14-hour schedule produces better

  9. Solvability of some partial functional integrodifferential equations with finite delay and optimal controls in Banach spaces.

    Science.gov (United States)

    Ezzinbi, Khalil; Ndambomve, Patrice

    2016-01-01

    In this work, we consider the control system governed by some partial functional integrodifferential equations with finite delay in Banach spaces. We assume that the undelayed part admits a resolvent operator in the sense of Grimmer. Firstly, some suitable conditions are established to guarantee the existence and uniqueness of mild solutions for a broad class of partial functional integrodifferential infinite dimensional control systems. Secondly, it is proved that, under generally mild conditions of cost functional, the associated Lagrange problem has an optimal solution, and that for each optimal solution there is a minimizing sequence of the problem that converges to the optimal solution with respect to the trajectory, the control, and the functional in appropriate topologies. Our results extend and complement many other important results in the literature. Finally, a concrete example of application is given to illustrate the effectiveness of our main results.

  10. Capacitated vehicle-routing problem model for scheduled solid waste collection and route optimization using PSO algorithm.

    Science.gov (United States)

    Hannan, M A; Akhtar, Mahmuda; Begum, R A; Basri, H; Hussain, A; Scavino, Edgar

    2018-01-01

    Waste collection widely depends on the route optimization problem that involves a large amount of expenditure in terms of capital, labor, and variable operational costs. Thus, the more waste collection route is optimized, the more reduction in different costs and environmental effect will be. This study proposes a modified particle swarm optimization (PSO) algorithm in a capacitated vehicle-routing problem (CVRP) model to determine the best waste collection and route optimization solutions. In this study, threshold waste level (TWL) and scheduling concepts are applied in the PSO-based CVRP model under different datasets. The obtained results from different datasets show that the proposed algorithmic CVRP model provides the best waste collection and route optimization in terms of travel distance, total waste, waste collection efficiency, and tightness at 70-75% of TWL. The obtained results for 1 week scheduling show that 70% of TWL performs better than all node consideration in terms of collected waste, distance, tightness, efficiency, fuel consumption, and cost. The proposed optimized model can serve as a valuable tool for waste collection and route optimization toward reducing socioeconomic and environmental impacts. Copyright © 2017 Elsevier Ltd. All rights reserved.

  11. Constraint optimization model of a scheduling problem for a robotic arm in automatic systems

    DEFF Research Database (Denmark)

    Kristiansen, Ewa; Smith, Stephen F.; Kristiansen, Morten

    2014-01-01

    . The scheduling model is implemented as a stand-alone module using constraint programming, and integrated with a larger automatic system. The results of a number of simulation experiments with simple parts are reported, both to characterize the functionality of the scheduler and to illustrate the operation...

  12. Optimization of design and erection methods to minimize the construction time-schedule of EPR plants

    International Nuclear Information System (INIS)

    Pierrat, Michel; L'Huby, Yvan; Decelle, Alain

    1999-01-01

    This paper presents the results of the investigations made during the Basic Design of the EPR project (European Pressurized water Reactor) to shorten the construction schedule. A 57 months construction schedule can be reached for the first unit. The investigations concern both design and construction methods. (author)

  13. Solving the job-shop scheduling problem optimally by dynamic programming

    NARCIS (Netherlands)

    Gromicho Dos Santos, J.A.; van Hoorn, J.J.; Saldanha da Gama, F.; Timmer, G.T.

    2012-01-01

    Scheduling problems received substantial attention during the last decennia. The job-shop problem is a very important scheduling problem, which is NP-hard in the strong sense and with well-known benchmark instances of relatively small size which attest the practical difficulty in solving it. The

  14. Optimal Scheduling and Real-Time State-of-Charge Management of Energy Storage System for Frequency Regulation

    Directory of Open Access Journals (Sweden)

    Jin-Sun Yang

    2016-11-01

    Full Text Available An energy storage system (ESS in a power system facilitates tasks such as renewable integration, peak shaving, and the use of ancillary services. Among the various functions of an ESS, this study focused on frequency regulation (or secondary reserve. This paper presents an optimal scheduling algorithm for frequency regulation by an ESS. This algorithm determines the bidding capacity and base point of an ESS in each operational period to achieve the maximum profit within a stable state-of-charge (SOC range. However, the charging/discharging efficiency of an ESS causes SOC errors whenever the ESS performs frequency regulation. With an increase in SOC errors, the ESS cannot respond to an automatic generation control (AGC signal. This situation results in low ESS performance scores, and finally, the ESS is disqualified from performing frequency regulation. This paper also presents a real-time SOC management algorithm aimed at solving the SOC error problem in real-time operations. This algorithm compensates for SOC errors by changing the base point of the ESS. The optimal scheduling algorithm is implemented in MATLAB by using the particle swarm optimization (PSO method. In addition, changes in the SOC when the ESS performs frequency regulation in a real-time operation are confirmed using the PSCAD/EMTDC tool. The simulation results show that the optimal scheduling algorithm manages the SOC more efficiently than a commonly employed planning method. In addition, the proposed real-time SOC management algorithm is confirmed to be capable of performing SOC recovery.

  15. A framework for using ant colony optimization to schedule environmental flow management alternatives for rivers, wetlands, and floodplains

    Science.gov (United States)

    Szemis, J. M.; Maier, H. R.; Dandy, G. C.

    2012-08-01

    Rivers, wetlands, and floodplains are in need of management as they have been altered from natural conditions and are at risk of vanishing because of river development. One method to mitigate these impacts involves the scheduling of environmental flow management alternatives (EFMA); however, this is a complex task as there are generally a large number of ecological assets (e.g., wetlands) that need to be considered, each with species with competing flow requirements. Hence, this problem evolves into an optimization problem to maximize an ecological benefit within constraints imposed by human needs and the physical layout of the system. This paper presents a novel optimization framework which uses ant colony optimization to enable optimal scheduling of EFMAs, given constraints on the environmental water that is available. This optimization algorithm is selected because, unlike other currently popular algorithms, it is able to account for all aspects of the problem. The approach is validated by comparing it to a heuristic approach, and its utility is demonstrated using a case study based on the Murray River in South Australia to investigate (1) the trade-off between plant recruitment (i.e., promoting germination) and maintenance (i.e., maintaining habitat) flow requirements, (2) the trade-off between flora and fauna flow requirements, and (3) a hydrograph inversion case. The results demonstrate the usefulness and flexibility of the proposed framework as it is able to determine EFMA schedules that provide optimal or near-optimal trade-offs between the competing needs of species under a range of operating conditions and valuable insight for managers.

  16. MODELLING TEMPORAL SCHEDULE OF URBAN TRAINS USING AGENT-BASED SIMULATION AND NSGA2-BASED MULTIOBJECTIVE OPTIMIZATION APPROACHES

    Directory of Open Access Journals (Sweden)

    M. Sahelgozin

    2015-12-01

    Full Text Available Increasing distances between locations of residence and services leads to a large number of daily commutes in urban areas. Developing subway systems has been taken into consideration of transportation managers as a response to this huge amount of travel demands. In developments of subway infrastructures, representing a temporal schedule for trains is an important task; because an appropriately designed timetable decreases Total passenger travel times, Total Operation Costs and Energy Consumption of trains. Since these variables are not positively correlated, subway scheduling is considered as a multi-criteria optimization problem. Therefore, proposing a proper solution for subway scheduling has been always a controversial issue. On the other hand, research on a phenomenon requires a summarized representation of the real world that is known as Model. In this study, it is attempted to model temporal schedule of urban trains that can be applied in Multi-Criteria Subway Schedule Optimization (MCSSO problems. At first, a conceptual framework is represented for MCSSO. Then, an agent-based simulation environment is implemented to perform Sensitivity Analysis (SA that is used to extract the interrelations between the framework components. These interrelations is then taken into account in order to construct the proposed model. In order to evaluate performance of the model in MCSSO problems, Tehran subway line no. 1 is considered as the case study. Results of the study show that the model was able to generate an acceptable distribution of Pareto-optimal solutions which are applicable in the real situations while solving a MCSSO is the goal. Also, the accuracy of the model in representing the operation of subway systems was significant.

  17. Modelling Temporal Schedule of Urban Trains Using Agent-Based Simulation and NSGA2-BASED Multiobjective Optimization Approaches

    Science.gov (United States)

    Sahelgozin, M.; Alimohammadi, A.

    2015-12-01

    Increasing distances between locations of residence and services leads to a large number of daily commutes in urban areas. Developing subway systems has been taken into consideration of transportation managers as a response to this huge amount of travel demands. In developments of subway infrastructures, representing a temporal schedule for trains is an important task; because an appropriately designed timetable decreases Total passenger travel times, Total Operation Costs and Energy Consumption of trains. Since these variables are not positively correlated, subway scheduling is considered as a multi-criteria optimization problem. Therefore, proposing a proper solution for subway scheduling has been always a controversial issue. On the other hand, research on a phenomenon requires a summarized representation of the real world that is known as Model. In this study, it is attempted to model temporal schedule of urban trains that can be applied in Multi-Criteria Subway Schedule Optimization (MCSSO) problems. At first, a conceptual framework is represented for MCSSO. Then, an agent-based simulation environment is implemented to perform Sensitivity Analysis (SA) that is used to extract the interrelations between the framework components. These interrelations is then taken into account in order to construct the proposed model. In order to evaluate performance of the model in MCSSO problems, Tehran subway line no. 1 is considered as the case study. Results of the study show that the model was able to generate an acceptable distribution of Pareto-optimal solutions which are applicable in the real situations while solving a MCSSO is the goal. Also, the accuracy of the model in representing the operation of subway systems was significant.

  18. Effects of AV delay and VV delay on left atrial pressure and waveform in ambulant heart failure patients: insights into CRT optimization.

    Science.gov (United States)

    Chan, W Y Wandy; Blomqvist, Andreas; Melton, Iain C; Norén, Kjell; Crozier, Ian G; Benser, Michael E; Eigler, Neal L; Gutfinger, Dan; Troughton, Richard W

    2014-07-01

    We hypothesized that left atrial pressure (LAP) obtained by a permanent implantable sensor is sensitive to changes in cardiac resynchronization therapy (CRT) settings and could guide CRT optimization to improve the response rate. We investigated the effect of CRT optimization on LAP and its waveform parameters in ambulant heart failure (HF) patients. CRT optimization was performed in eight ambulant HF patients, using echocardiography as reference. LAP waveform was acquired at each of eight atrioventricular (AV) intervals and five inter-ventricular (VV) intervals. Selected waveform parameters were also evaluated for their sensitivity to CRT changes and agreement with echocardiography-guided optimal settings. Optimal AV and VV intervals varied considerably between patients. All patients exhibited significant changes in waveform morphology with AV optimization. Optimal AV delay determined from echocardiography ranged between 140 ms and 225 ms. Mean LAP tended to be lower at optimal setting 14 ± 3 mmHg compared to shorter (160 ms) AV settings (P = 0.16). There were clear trends to smaller peak a-wave (P = 0.11) and gentler positive a-slope (P = 0.15) and positive v-slope (P = 0.09) with longer AV delays. Mean LAP and negative v-wave slope correlated well with echo-guided optimal setting, r = 0.91 (P = 0.001) and 0.79 (P = 0.03), respectively. No significant effects on LAP or waveform were seen during VV optimization. LAP and its waveform changes considerably with AV optimization. There is good agreement between echo-guided optimal setting and LAP. LAP could provide an objective guide to CRT optimization. (Clinical Trial Registry information: URL: http://www.clinicaltrials.gov. Unique Identifier: NCT00632372). ©2014 Wiley Periodicals, Inc.

  19. Fixed priority scheduling with pre-emption thresholds and cache-related pre-emption delays: integrated analysis and evaluation

    NARCIS (Netherlands)

    Bril, R.J.; Altmeyer, S.; van den Heuvel, M.M.H.P.; Davis, R.I.; Behnam, M.

    Commercial off-the-shelf programmable platforms for real-time systems typically contain a cache to bridge the gap between the processor speed and main memory speed. Because cache-related pre-emption delays (CRPD) can have a significant influence on the computation times of tasks, CRPD have been

  20. Optimal nonlinear information processing capacity in delay-based reservoir computers

    Science.gov (United States)

    Grigoryeva, Lyudmila; Henriques, Julie; Larger, Laurent; Ortega, Juan-Pablo

    2015-09-01

    Reservoir computing is a recently introduced brain-inspired machine learning paradigm capable of excellent performances in the processing of empirical data. We focus in a particular kind of time-delay based reservoir computers that have been physically implemented using optical and electronic systems and have shown unprecedented data processing rates. Reservoir computing is well-known for the ease of the associated training scheme but also for the problematic sensitivity of its performance to architecture parameters. This article addresses the reservoir design problem, which remains the biggest challenge in the applicability of this information processing scheme. More specifically, we use the information available regarding the optimal reservoir working regimes to construct a functional link between the reservoir parameters and its performance. This function is used to explore various properties of the device and to choose the optimal reservoir architecture, thus replacing the tedious and time consuming parameter scannings used so far in the literature.

  1. Optimization of Resource Allocation in Multihop HARQ Relay Networks with a Delay Constraint

    Directory of Open Access Journals (Sweden)

    Han Jun-Mei

    2017-01-01

    Full Text Available By minimizing the outage probability, optimization is carried out in this paper to find joint optimal power allocation (OPA and relay placement (ORP for multihop relay networks adopting Hybrid Automatic Repeat reQuest (HARQ. Different from previous works, the joint OPA and ORP is analysed under generalized fading channels with the constraint on total transmit power, end-to-end relaying distance and maximum transmission number (delay. The simulation results demonstrate that for different fixed number of nodes and fading models, there are preferred deployments depending on path loss exponent and power retransmission strategy. By employing multiple retransmission round which can improve the reliability and energy efficiency without significant overhead, the end-to-end outage probability is no longer bounded by that of the weaker hop, i.e., the hop with a poor channel condition. The proposed strategy provides a dramatic improvement for the end-to-end outage probability by compensating the channel difference.

  2. Optimal Day-ahead Charging Scheduling of Electric Vehicles through an Aggregative Game Model

    DEFF Research Database (Denmark)

    Liu, Zhaoxi; Wu, Qiuwei; Huang, Shaojun

    2017-01-01

    The electric vehicle (EV) market has been growing rapidly around the world. With large scale deployment of EVs in power systems, both the grid and EV owners will benefit if the flexible demand of EV charging is properly managed through the electricity market. When EV charging demand is considerable...... in a grid, it will impact spot prices in the electricity market and consequently influence the charging scheduling itself. The interaction between the spot prices and the EV demand needs to be considered in the EV charging scheduling, otherwise it will lead to a higher charging cost. A day-ahead EV charging...... scheduling based on an aggregative game model is proposed in this paper. The impacts of the EV demand on the electricity prices are formulated with the game model in the scheduling considering possible actions of other EVs. The existence and uniqueness of the pure strategy Nash equilibrium are proved...

  3. THE DESIGN AND OPTIMIZATION OF AN INTEGRATED ARRIVAL/DEPARTURE SCHEDULER, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — Intelligent Automation, Inc. (IAI) proposes the design and validation of a dynamic integrated arrival/departure scheduler. In contrast to current approaches, we...

  4. Optimal Scheduling of a Battery Energy Storage System with Electric Vehicles’ Auxiliary for a Distribution Network with Renewable Energy Integration

    Directory of Open Access Journals (Sweden)

    Yuqing Yang

    2015-09-01

    Full Text Available With global conventional energy depletion, as well as environmental pollution, utilizing renewable energy for power supply is the only way for human beings to survive. Currently, distributed generation incorporated into a distribution network has become the new trend, with the advantages of controllability, flexibility and tremendous potential. However, the fluctuation of distributed energy resources (DERs is still the main concern for accurate deployment. Thus, a battery energy storage system (BESS has to be involved to mitigate the bad effects of DERs’ integration. In this paper, optimal scheduling strategies for BESS operation have been proposed, to assist with consuming the renewable energy, reduce the active power loss, alleviate the voltage fluctuation and minimize the electricity cost. Besides, the electric vehicles (EVs considered as the auxiliary technique are also introduced to attenuate the DERs’ influence. Moreover, both day-ahead and real-time operation scheduling strategies were presented under the consideration with the constraints of BESS and the EVs’ operation, and the optimization was tackled by a fuzzy mathematical method and an improved particle swarm optimization (IPSO algorithm. Furthermore, the test system for the proposed strategies is a real distribution network with renewable energy integration. After simulation, the proposed scheduling strategies have been verified to be extremely effective for the enhancement of the distribution network characteristics.

  5. An improved quantum-behaved particle swarm optimization method for short-term combined economic emission hydrothermal scheduling

    International Nuclear Information System (INIS)

    Lu Songfeng; Sun Chengfu; Lu Zhengding

    2010-01-01

    This paper presents a modified quantum-behaved particle swarm optimization (QPSO) for short-term combined economic emission scheduling (CEES) of hydrothermal power systems with several equality and inequality constraints. The hydrothermal scheduling is formulated as a bi-objective problem: (i) minimizing fuel cost and (ii) minimizing pollutant emission. The bi-objective problem is converted into a single objective one by price penalty factor. The proposed method, denoted as QPSO-DM, combines the QPSO algorithm with differential mutation operation to enhance the global search ability. In this study, heuristic strategies are proposed to handle the equality constraints especially water dynamic balance constraints and active power balance constraints. A feasibility-based selection technique is also employed to meet the reservoir storage volumes constraints. To show the efficiency of the proposed method, different case studies are carried out and QPSO-DM is compared with the differential evolution (DE), the particle swarm optimization (PSO) with same heuristic strategies in terms of the solution quality, robustness and convergence property. The simulation results show that the proposed method is capable of yielding higher-quality solutions stably and efficiently in the short-term hydrothermal scheduling than any other tested optimization algorithms.

  6. Optimizing Music Learning: Exploring How Blocked and Interleaved Practice Schedules Affect Advanced Performance.

    Science.gov (United States)

    Carter, Christine E; Grahn, Jessica A

    2016-01-01

    Repetition is the most commonly used practice strategy by musicians. Although blocks of repetition continue to be suggested in the pedagogical literature, work in the field of cognitive psychology suggests that repeated events receive less processing, thereby reducing the potential for long-term learning. Motor skill learning and sport psychology research offer an alternative. Instead of using a blocked practice schedule, with practice completed on one task before moving on to the next task, an interleaved schedule can be used, in which practice is frequently alternated between tasks. This frequent alternation involves more effortful processing, resulting in increased long-term learning. The finding that practicing in an interleaved schedule leads to better retention than practicing in a blocked schedule has been labeled the "contextual interference effect." While the effect has been observed across a wide variety of fields, few studies have researched this phenomenon in a music-learning context, despite the broad potential for application to music practice. This study compared the effects of blocked and interleaved practice schedules on advanced clarinet performance in an ecologically valid context. Ten clarinetists were given one concerto exposition and one technical excerpt to practice in a blocked schedule (12 min per piece) and a second concerto exposition and technical excerpt to practice in an interleaved schedule (3 min per piece, alternating until a total of 12 min of practice were completed on each piece). Participants sight-read the four pieces prior to practice and performed them at the end of practice and again one day later. The sight-reading and two performance run-throughs of each piece were recorded and given to three professional clarinetists to rate using a percentage scale. Overall, whenever there was a ratings difference between the conditions, pieces practiced in the interleaved schedule were rated better than those in the blocked schedule

  7. Optimizing music learning: Exploring how blocked and interleaved practice schedules affect advanced performance

    Directory of Open Access Journals (Sweden)

    Christine E Carter

    2016-08-01

    Full Text Available Repetition is the most commonly used practice strategy by musicians. Although blocks of repetition continue to be suggested in the pedagogical literature, work in the field of cognitive psychology suggests that repeated events receive less processing, thereby reducing the potential for long-term learning. Motor skill learning and sport psychology research offer an alternative. Instead of using a blocked practice schedule, with practice completed on one task before moving on to the next task, an interleaved schedule can be used, in which practice is frequently alternated between tasks. This frequent alternation involves more effortful processing, resulting in increased long-term learning. The finding that practicing in an interleaved schedule leads to better retention than practicing in a blocked schedule has been labeled the contextual interference effect. While the effect has been observed across a wide variety of fields, few studies have researched this phenomenon in a music-learning context, despite the broad potential for application to music practice. This study compared the effects of blocked and interleaved practice schedules on advanced clarinet performance in an ecologically valid context. Ten clarinetists were given one concerto exposition and one technical excerpt to practice in a blocked schedule (twelve minutes per piece and a second concerto exposition and technical excerpt to practice in an interleaved schedule (three minutes per piece, alternating until a total of twelve minutes of practice were completed on each piece. Participants sight-read the four pieces prior to practice and performed them at the end of practice and again one day later. The sight-reading and two performance run-throughs of each piece were recorded and given to three professional clarinetists to rate using a percentage scale. Overall, whenever there was a ratings difference between the conditions, pieces practiced in the interleaved schedule were rated

  8. Optimizing Music Learning: Exploring How Blocked and Interleaved Practice Schedules Affect Advanced Performance

    Science.gov (United States)

    Carter, Christine E.; Grahn, Jessica A.

    2016-01-01

    Repetition is the most commonly used practice strategy by musicians. Although blocks of repetition continue to be suggested in the pedagogical literature, work in the field of cognitive psychology suggests that repeated events receive less processing, thereby reducing the potential for long-term learning. Motor skill learning and sport psychology research offer an alternative. Instead of using a blocked practice schedule, with practice completed on one task before moving on to the next task, an interleaved schedule can be used, in which practice is frequently alternated between tasks. This frequent alternation involves more effortful processing, resulting in increased long-term learning. The finding that practicing in an interleaved schedule leads to better retention than practicing in a blocked schedule has been labeled the “contextual interference effect.” While the effect has been observed across a wide variety of fields, few studies have researched this phenomenon in a music-learning context, despite the broad potential for application to music practice. This study compared the effects of blocked and interleaved practice schedules on advanced clarinet performance in an ecologically valid context. Ten clarinetists were given one concerto exposition and one technical excerpt to practice in a blocked schedule (12 min per piece) and a second concerto exposition and technical excerpt to practice in an interleaved schedule (3 min per piece, alternating until a total of 12 min of practice were completed on each piece). Participants sight-read the four pieces prior to practice and performed them at the end of practice and again one day later. The sight-reading and two performance run-throughs of each piece were recorded and given to three professional clarinetists to rate using a percentage scale. Overall, whenever there was a ratings difference between the conditions, pieces practiced in the interleaved schedule were rated better than those in the blocked schedule

  9. Multi-Objective Task Scheduling in the Cloud Computing based on the Patrice Swarm Optimization

    OpenAIRE

    Farnaz Sharifi Milani; Ahmad Habibizad Navin

    2015-01-01

    Cloud computing is the latest emerging trend in distributed computing, where shared resources are provided to end-users in an on demand fashion that brings many advantages, including data ubiquity, flexibility of access, high availability of resources, and flexibility. In this type of systems many challenges are existed that the task scheduling problem is one of them. The task scheduling problem in Cloud computing is an NP-hard problem. Therefore, many heuristics have bee...

  10. Dynamical Behavior of a Malaria Model with Discrete Delay and Optimal Insecticide Control

    Science.gov (United States)

    Kar, Tuhin Kumar; Jana, Soovoojeet

    In this paper we have proposed and analyzed a simple three-dimensional mathematical model related to malaria disease. We consider three state variables associated with susceptible human population, infected human population and infected mosquitoes, respectively. A discrete delay parameter has been incorporated to take account of the time of incubation period with infected mosquitoes. We consider the effect of insecticide control, which is applied to the mosquitoes. Basic reproduction number is figured out for the proposed model and it is shown that when this threshold is less than unity then the system moves to the disease-free state whereas for higher values other than unity, the system would tend to an endemic state. On the other hand if we consider the system with delay, then there may exist some cases where the endemic equilibrium would be unstable although the numerical value of basic reproduction number may be greater than one. We formulate and solve the optimal control problem by considering insecticide as the control variable. Optimal control problem assures to obtain better result than the noncontrol situation. Numerical illustrations are provided in support of the theoretical results.

  11. Dual chamber pacing with optimal AV delay in congestive heart failure: a randomized study.

    Science.gov (United States)

    Capucci, A; Romano, S; Puglisi, A; Santini, M; Pagani, M; Cazzin, R; Zanuttini, D; Mangiameli, S; Moracchini, P V; Neri, R; De Ciuceis, P; Circo, A; Cavaglià, S; De Seta, F

    1999-07-01

    A prospective randomized trial was set up to evaluate contractile parameters and quality of life in patients with congestive heart failure. We describe the results from 38 patients in sinus rhythm and with chronic heart failure due to congestive cardiomyopathy, prospectively randomized to optimal medical therapy (Group 1, 19 patients) or optimal medical therapy plus dual chamber pacemaker programmed to optimal AV delay (Group 2, 19 patients). At a 6 month follow-up, 7/19 patients in Group 1 had died compared with 5/19 patients in Group 2. During follow-up, there were few significant changes in evaluated parameters except for mitral regurgitation time, which was prolonged in Group 1 and shortened in Group 2. The systolic left ventricular diameter shortened significantly only in Group 2. An energy and activity questionnaire showed that the effect of DDD pacing in the latter patient population was beneficial. From these results we may conclude that at the 6 month follow-up DDD pacing with echo-optimized AV interval programming can improve quality of life without affecting survival.

  12. SU-F-19A-08: Optimal Time Release Schedule of In-Situ Drug Release During Permanent Prostate Brachytherapy

    International Nuclear Information System (INIS)

    Cormack, R; Ngwa, W; Makrigiorgos, G; Tangutoori, S; Rajiv, K; Sridhar, S

    2014-01-01

    Purpose: Permanent prostate brachytherapy spacers can be used to deliver sustained doses of radiosentitizing drug directly to the target, in order to enhance the radiation effect. Implantable nanoplatforms for chemo-radiation therapy (INCeRTs) have a maximum drug capacity and can be engineered to control the drug release schedule. The optimal schedule for sensitization during continuous low dose rate irradiation is unknown. This work studies the optimal release schedule of drug for both traditional sensitizers, and those that work by suppressing DNA repair processes. Methods: Six brachytherapy treatment plans were used to model the anatomy, implant geometry and calculate the spatial distribution of radiation dose and drug concentrations for a range of drug diffusion parameters. Three state partial differential equations (cells healthy, damaged or dead) modeled the effect of continuous radiation (radiosensitivities α,β) and cellular repair (time tr) on a cell population. Radiosensitization was modeled as concentration dependent change in α,β or tr which with variable duration under the constraint of fixed total drug release. Average cell kill was used to measure effectiveness. Sensitization by means of both enhanced damage and reduced repair were studied. Results: Optimal release duration is dependent on the concentration of radiosensitizer compared to the saturation concentration (csat) above which additional sensitization does not occur. Long duration drug release when enhancing α or β maximizes cell death when drug concentrations are generally over csat. Short term release is optimal for concentrations below saturation. Sensitization by suppressing repair has a similar though less distinct trend that is more affected by the radiation dose distribution. Conclusion: Models of sustained local radiosensitization show potential to increase the effectiveness of radiation in permanent prostate brachytherapy. INCeRTs with high drug capacity produce the greatest

  13. SU-F-19A-08: Optimal Time Release Schedule of In-Situ Drug Release During Permanent Prostate Brachytherapy

    Energy Technology Data Exchange (ETDEWEB)

    Cormack, R; Ngwa, W; Makrigiorgos, G [Dana-Farber Cancer Institute, Brigham and Women' s Hospital and Harvard Medical School, Boston, MA (United States); Tangutoori, S; Rajiv, K; Sridhar, S [Northeastern University, Boston, MA (United States)

    2014-06-15

    Purpose: Permanent prostate brachytherapy spacers can be used to deliver sustained doses of radiosentitizing drug directly to the target, in order to enhance the radiation effect. Implantable nanoplatforms for chemo-radiation therapy (INCeRTs) have a maximum drug capacity and can be engineered to control the drug release schedule. The optimal schedule for sensitization during continuous low dose rate irradiation is unknown. This work studies the optimal release schedule of drug for both traditional sensitizers, and those that work by suppressing DNA repair processes. Methods: Six brachytherapy treatment plans were used to model the anatomy, implant geometry and calculate the spatial distribution of radiation dose and drug concentrations for a range of drug diffusion parameters. Three state partial differential equations (cells healthy, damaged or dead) modeled the effect of continuous radiation (radiosensitivities α,β) and cellular repair (time tr) on a cell population. Radiosensitization was modeled as concentration dependent change in α,β or tr which with variable duration under the constraint of fixed total drug release. Average cell kill was used to measure effectiveness. Sensitization by means of both enhanced damage and reduced repair were studied. Results: Optimal release duration is dependent on the concentration of radiosensitizer compared to the saturation concentration (csat) above which additional sensitization does not occur. Long duration drug release when enhancing α or β maximizes cell death when drug concentrations are generally over csat. Short term release is optimal for concentrations below saturation. Sensitization by suppressing repair has a similar though less distinct trend that is more affected by the radiation dose distribution. Conclusion: Models of sustained local radiosensitization show potential to increase the effectiveness of radiation in permanent prostate brachytherapy. INCeRTs with high drug capacity produce the greatest

  14. Optimization of irrigation scheduling for spring wheat with mulching and limited irrigation water in an arid climate

    Science.gov (United States)

    Wen, Y.

    2017-12-01

    Combining mulch and irrigation scheduling may lead to an increase of crop yield and water use efficiency (WUE = crop yield/evapotranspiration) with limited irrigation water, especially in arid regions. Based on 2 years' field experiments with ten irrigation-mulching treatments of spring wheat (Triticum aestivum L.) in the Shiyang River Basin Experiment Station in Gansu Province of Northwest China, a simulation-based optimization model for deficit irrigation scheduling of plastic mulching spring wheat was used to analyze an optimal irrigation scheduling for different deficit irrigation scenarios. Results revealed that mulching may increase maximum grain yield without water stress by 0.4-0.6 t ha-1 in different years and WUE by 0.2-0.3 kg m-3 for different irrigation amounts compared with no mulching. Yield of plastic mulching spring wheat was more sensitive to water stress in the early and development growth stages with an increase of cumulative crop water sensitive index (CCWSI) by 42%, and less sensitive to water stress in the mid and late growth stages with a reduction of CCWSI by 24%. For a relative wet year, when irrigation water is only applied once it should be at the mid to end of booting growth stage. Two irrigations should be applied at the beginning of booting and heading growth stages. The irrigation date can be extended to the beginning of jointing and grain formation growth stages with more water available for irrigation. For a normal or a dry year, the first irrigation should be applied 5-8 days earlier than the wet year. The highest WUE of 3.6 kg m-3 was achieved with 180 mm of irrigation applied twice for mulching in a wet year. Combining mulch and an optimal deficit irrigation scheduling is an effective way to increase crop yield and WUE in arid regions.

  15. Tuning of an optimal fuzzy PID controller with stochastic algorithms for networked control systems with random time delay.

    Science.gov (United States)

    Pan, Indranil; Das, Saptarshi; Gupta, Amitava

    2011-01-01

    An optimal PID and an optimal fuzzy PID have been tuned by minimizing the Integral of Time multiplied Absolute Error (ITAE) and squared controller output for a networked control system (NCS). The tuning is attempted for a higher order and a time delay system using two stochastic algorithms viz. the Genetic Algorithm (GA) and two variants of Particle Swarm Optimization (PSO) and the closed loop performances are compared. The paper shows that random variation in network delay can be handled efficiently with fuzzy logic based PID controllers over conventional PID controllers. Copyright © 2010 ISA. Published by Elsevier Ltd. All rights reserved.

  16. A PMBGA to Optimize the Selection of Rules for Job Shop Scheduling Based on the Giffler-Thompson Algorithm

    Directory of Open Access Journals (Sweden)

    Rui Zhang

    2012-01-01

    Full Text Available Most existing research on the job shop scheduling problem has been focused on the minimization of makespan (i.e., the completion time of the last job. However, in the fiercely competitive market nowadays, delivery punctuality is more important for maintaining a high service reputation. So in this paper, we aim at solving job shop scheduling problems with the total weighted tardiness objective. Several dispatching rules are adopted in the Giffler-Thompson algorithm for constructing active schedules. It is noticeable that the rule selections for scheduling consecutive operations are not mutually independent but actually interrelated. Under such circumstances, a probabilistic model-building genetic algorithm (PMBGA is proposed to optimize the sequence of selected rules. First, we use Bayesian networks to model the distribution characteristics of high-quality solutions in the population. Then, the new generation of individuals is produced by sampling the established Bayesian network. Finally, some elitist individuals are further improved by a special local search module based on parameter perturbation. The superiority of the proposed approach is verified by extensive computational experiments and comparisons.

  17. A Reconfigured Whale Optimization Technique (RWOT for Renewable Electrical Energy Optimal Scheduling Impact on Sustainable Development Applied to Damietta Seaport, Egypt

    Directory of Open Access Journals (Sweden)

    Noha H. El-Amary

    2018-03-01

    Full Text Available This paper studies the effect on the rate of growth of carbon dioxide emission in seaports’ atmosphere of replacing a part of the fossil fuel electrical power generation by clean renewable electrical energies, through two different scheduling strategies. The increased rate of harmful greenhouse gas emissions due to conventional electrical power generation severely affects the whole global atmosphere. Carbon dioxide and other greenhouse gases emissions are responsible for a significant share of global warming. Developing countries participate in this environmental distortion to a great percentage. Two different suggested strategies for renewable electrical energy scheduling are discussed in this paper, to attain a sustainable green port by the utilization of two mutual sequential clean renewable energies, which are biomass and photovoltaic (PV energy. The first strategy, which is called the eco-availability mode, is a simple method. It is based on operating the renewable electrical energy sources during the available time of operation, taking into consideration the simple and basic technical issues only, without considering the sophisticated technical and economical models. The available operation time is determined by the environmental condition. This strategy is addressed to result on the maximum available Biomass and PV energy generation based on the least environmental and technical conditions (panel efficiency, minimum average daily sunshine hours per month, minimum average solar insolation per month. The second strategy, which is called the Intelligent Scheduling (IS mode, relies on an intelligent Reconfigured Whale Optimization Technique (RWOT based-model. In this strategy, some additional technical and economical issues are considered. The studied renewable electrical energy generation system is considered in two scenarios, which are with and without storage units. The objective (cost function of the scheduling optimization problem, for

  18. Optimization of workflow scheduling in Utility Management System with hierarchical neural network

    Directory of Open Access Journals (Sweden)

    Srdjan Vukmirovic

    2011-08-01

    Full Text Available Grid computing could be the future computing paradigm for enterprise applications, one of its benefits being that it can be used for executing large scale applications. Utility Management Systems execute very large numbers of workflows with very high resource requirements. This paper proposes architecture for a new scheduling mechanism that dynamically executes a scheduling algorithm using feedback about the current status Grid nodes. Two Artificial Neural Networks were created in order to solve the scheduling problem. A case study is created for the Meter Data Management system with measurements from the Smart Metering system for the city of Novi Sad, Serbia. Performance tests show that significant improvement of overall execution time can be achieved by Hierarchical Artificial Neural Networks.

  19. Joint optimization of CQI calculation and interference mitigation for user scheduling in MIMO-OFDM systems

    KAUST Repository

    Sadek, Mirette

    2011-05-01

    In MIMO-OFDM multiuser systems, user scheduling is employed as a means of multiple access. In a downlink scenario, users that share the same subcarriers of an OFDM symbol are separated through precoding in order to achieve space division multiple access (SDMA). User scheduling techniques rely on channel knowledge at the transmitter, namely, the so-called channel quality indicator (CQI). In this paper, we implement a leakage-based precoding algorithm whose purpose is twofold. First, it is used to compute a reliable CQI based on a group of precoding vectors that are adapted to the channel. Then, it implements user scheduling through using the optimum vectors for precoding, thus minimizing interference among users. We also introduce the concept of resource block size adaptivity. The resource block (RB) is defined as the least unit in an OFDM symbol that a user can be assigned to. We propose a variable RB size that adapts to the channel conditions. © 2011 IEEE.

  20. An optimization based on simulation approach to the patient admission scheduling problem using a linear programing algorithm.

    Science.gov (United States)

    Granja, C; Almada-Lobo, B; Janela, F; Seabra, J; Mendes, A

    2014-12-01

    As patient's length of stay in waiting lists increases, governments are looking for strategies to control the problem. Agreements were created with private providers to diminish the workload in the public sector. However, the growth of the private sector is not following the demand for care. Given this context, new management strategies have to be considered in order to minimize patient length of stay in waiting lists while reducing the costs and increasing (or at least maintaining) the quality of care. Appointment scheduling systems are today known to be proficient in the optimization of health care services. Their utilization is focused on increasing the usage of human resources, medical equipment and reducing the patient waiting times. In this paper, a simulation-based optimization approach to the Patient Admission Scheduling Problem is presented. Modeling tools and simulation techniques are used in the optimization of a diagnostic imaging department. The proposed techniques have demonstrated to be effective in the evaluation of diagnostic imaging workflows. A simulated annealing algorithm was used to optimize the patient admission sequence towards minimizing the total completion and total waiting of patients. The obtained results showed average reductions of 5% on the total completion and 38% on the patients' total waiting time. Copyright © 2014 Elsevier Inc. All rights reserved.

  1. Dynamic contrast-enhanced MR imaging of endometrial cancer. Optimizing the imaging delay for tumour-myometrium contrast

    Energy Technology Data Exchange (ETDEWEB)

    Park, Sung Bin [Chung-Ang University Hospital, Chung-Ang University College of Medicine, Department of Radiology, Seoul (Korea, Republic of); Moon, Min Hoan; Sung, Chang Kyu [Seoul National University College of Medicine, 41, Department of Radiology, SMG-SNU Boramae Medical Center, Seoul (Korea, Republic of); Oh, Sohee [Seoul National University College of Medicine, 41, Department of Biostatistics, SMG-SNU Boramae Medical Center, Seoul (Korea, Republic of); Lee, Young Ho [Kwandong University College of Medicine, Department of Radiology, Cheil General Hospital and Women' s Healthcare Center, Seoul (Korea, Republic of)

    2014-11-15

    To investigate the optimal imaging delay time of dynamic contrast-enhanced magnetic resonance (MR) imaging in women with endometrial cancer. This prospective single-institution study was approved by the institutional review board, and informed consent was obtained from the participants. Thirty-five women (mean age, 54 years; age range, 29-66 years) underwent dynamic contrast-enhanced MR imaging with a temporal resolution of 25-40 seconds. The signal intensity difference ratios between the myometrium and endometrial cancer were analyzed to investigate the optimal imaging delay time using single change-point analysis. The optimal imaging delay time for appropriate tumour-myometrium contrast ranged from 31.7 to 268.1 seconds. The median optimal imaging delay time was 91.3 seconds, with an interquartile range of 46.2 to 119.5 seconds. The median signal intensity difference ratios between the myometrium and endometrial cancer were 0.03, with an interquartile range of -0.01 to 0.06, on the pre-contrast MR imaging and 0.20, with an interquartile range of 0.15 to 0.25, on the post-contrast MR imaging. An imaging delay of approximately 90 seconds after initiating contrast material injection may be optimal for obtaining appropriate tumour-myometrium contrast in women with endometrial cancer. (orig.)

  2. Dynamic contrast-enhanced MR imaging of endometrial cancer. Optimizing the imaging delay for tumour-myometrium contrast

    International Nuclear Information System (INIS)

    Park, Sung Bin; Moon, Min Hoan; Sung, Chang Kyu; Oh, Sohee; Lee, Young Ho

    2014-01-01

    To investigate the optimal imaging delay time of dynamic contrast-enhanced magnetic resonance (MR) imaging in women with endometrial cancer. This prospective single-institution study was approved by the institutional review board, and informed consent was obtained from the participants. Thirty-five women (mean age, 54 years; age range, 29-66 years) underwent dynamic contrast-enhanced MR imaging with a temporal resolution of 25-40 seconds. The signal intensity difference ratios between the myometrium and endometrial cancer were analyzed to investigate the optimal imaging delay time using single change-point analysis. The optimal imaging delay time for appropriate tumour-myometrium contrast ranged from 31.7 to 268.1 seconds. The median optimal imaging delay time was 91.3 seconds, with an interquartile range of 46.2 to 119.5 seconds. The median signal intensity difference ratios between the myometrium and endometrial cancer were 0.03, with an interquartile range of -0.01 to 0.06, on the pre-contrast MR imaging and 0.20, with an interquartile range of 0.15 to 0.25, on the post-contrast MR imaging. An imaging delay of approximately 90 seconds after initiating contrast material injection may be optimal for obtaining appropriate tumour-myometrium contrast in women with endometrial cancer. (orig.)

  3. Inter-terminal transfer between port terminals. A continuous mathematical programming model to optimize scheduling and deployment of transport units

    Energy Technology Data Exchange (ETDEWEB)

    Morales Fusco, P.; Pedrielli, G.; Zhou, C.; Hay Lee, L.; Peng Chew, E.

    2016-07-01

    In most large port cities, the challenge of inter-terminal transfers (ITT) prevails due to the long distance between multiple terminals. The quantity of containers requiring movement between terminals as they connect from pre-carrier to on-carrier is increasing with the formation of the mega-alliances. The paper proposes a continuous time mathematical programming model to optimize the deployment and schedule of trucks and barges to minimize the number of operating transporters, their makespan, costs and the distance travelled by the containers by choosing the right combination of transporters and container movements while fulfilling time window restrictions imposed on reception of the containers. A multi-step routing problem is developed where transporters can travel from one terminal to another and/or load or unload containers from a specific batch at each step. The model proves successful in identifying the costless schedule and means of transportation. And a sensibility analysis over the parameters used is provided. (Author)

  4. Scheduling and Optimization of Fault-Tolerant Embedded Systems with Transparency/Performance Trade-Offs

    DEFF Research Database (Denmark)

    Izosimov, Viacheslav; Pop, Paul; Eles, Petru

    2012-01-01

    In this article, we propose a strategy for the synthesis of fault-tolerant schedules and for the mapping of fault-tolerant applications. Our techniques handle transparency/performance trade-offs and use the faultoccurrence information to reduce the overhead due to fault tolerance. Processes and m...

  5. Resource-constrained optimal scheduling of SDF graphs via timed automata (extended version)

    NARCIS (Netherlands)

    Ahmad, W.; de Groote, Robert; Holzenspies, P.K.F.; Stoelinga, Mariëlle Ida Antoinette; van de Pol, Jan Cornelis

    2014-01-01

    Synchronous dataflow (SDF) graphs are a widely used formalism for modelling, analysing and realising streaming applications, both on a single processor and in a multiprocessing context. Efficient schedules are essential to obtain maximal throughput under the constraint of available number of

  6. Optimal Usage of Multiple Energy Carriers in Residential Systems : Unit Scheduling and Power Control

    NARCIS (Netherlands)

    Ramirez-Elizondo, L.M.

    2013-01-01

    The world’s increasing energy demand and growing environmental concerns have motivated scientists to develop new technologies and methods to make better use of the remaining resources of our planet. The main objective of this dissertation is to develop a scheduling and control tool at the district

  7. Multi-objective parallel particle swarm optimization for day-ahead Vehicle-to-Grid scheduling

    DEFF Research Database (Denmark)

    Soares, Joao; Vale, Zita; Canizes, Bruno

    2013-01-01

    This paper presents a methodology for multi-objective day-ahead energy resource scheduling for smart grids considering intensive use of distributed generation and Vehicle-To-Grid (V2G). The main focus is the application of weighted Pareto to a multi-objective parallel particle swarm approach aiming...

  8. Resource-Constrained Optimal Scheduling of Synchronous Dataflow Graphs via Timed Automata

    NARCIS (Netherlands)

    Ahmad, W.; de Groote, Robert; Holzenspies, P.K.F.; Stoelinga, Mariëlle Ida Antoinette; van de Pol, Jan Cornelis

    Synchronous dataflow (SDF) graphs are a widely used formalism for modelling, analysing and realising streaming applications, both on a single processor and in a multiprocessing context. Efficient schedules are essential to obtain maximal throughput under the constraint of available resources. This

  9. Optimal Real-Time Scheduling for Hybrid Energy Storage Systems and Wind Farms Based on Model Predictive Control

    Directory of Open Access Journals (Sweden)

    Meng Xiong

    2015-08-01

    Full Text Available Energy storage devices are expected to be more frequently implemented in wind farms in near future. In this paper, both pumped hydro and fly wheel storage systems are used to assist a wind farm to smooth the power fluctuations. Due to the significant difference in the response speeds of the two storages types, the wind farm coordination with two types of energy storage is a problem. This paper presents two methods for the coordination problem: a two-level hierarchical model predictive control (MPC method and a single-level MPC method. In the single-level MPC method, only one MPC controller coordinates the wind farm and the two storage systems to follow the grid scheduling. Alternatively, in the two-level MPC method, two MPC controllers are used to coordinate the wind farm and the two storage systems. The structure of two level MPC consists of outer level and inner level MPC. They run alternatively to perform real-time scheduling and then stop, thus obtaining long-term scheduling results and sending some results to the inner level as input. The single-level MPC method performs both long- and short-term scheduling tasks in each interval. The simulation results show that the methods proposed can improve the utilization of wind power and reduce wind power spillage. In addition, the single-level MPC and the two-level MPC are not interchangeable. The single-level MPC has the advantage of following the grid schedule while the two-level MPC can reduce the optimization time by 60%.

  10. Optimized energy-delay sub-network routing protocol development and implementation for wireless sensor networks

    International Nuclear Information System (INIS)

    Fonda, James W; Zawodniok, Maciej; Jagannathan, S; Watkins, Steve E

    2008-01-01

    The development and the implementation issues of a reactive optimized energy-delay sub-network routing (OEDSR) protocol for wireless sensor networks (WSN) are introduced and its performance is contrasted with the popular ad hoc on-demand distance vector (AODV) routing protocol. Analytical results illustrate the performance of the proposed OEDSR protocol, while experimental results utilizing a hardware testbed under various scenarios demonstrate improvements in energy efficiency of the OEDSR protocol. A hardware platform constructed at the University of Missouri-Rolla (UMR), now the Missouri University of Science and Technology (MST), based on the Generation 4 Smart Sensor Node (G4-SSN) prototyping platform is also described. Performance improvements are shown in terms of end-to-end (E2E) delay, throughput, route-set-up time and drop rates and energy usage is given for three topologies, including a mobile topology. Additionally, results from the hardware testbed provide valuable lessons for network deployments. Under testing OEDSR provides a factor of ten improvement in the energy used in the routing session and extends network lifetime compared to AODV. Depletion experiments show that the time until the first node failure is extended by a factor of three with the network depleting and network lifetime is extended by 6.7%

  11. Optimal design of PID controller for second order plus time delay systems

    International Nuclear Information System (INIS)

    Srivastava, S.; Misra, A.; Kumar, Y.; Thakur, S.K.

    2015-01-01

    It is well known that the effect of time delay in the forward path of control loop deteriorates the system performance and at the same time makes it difficult to compute the optimum PID controller parameters of the feedback control systems. PI/PID controller is most popular and used more than 80% in industries as well as in accelerators lab due to its simple structure and appropriate robustness. At VECC we have planned to use a PID controller for the speed control of DC motor which will be used to adjust the solenoid coil position of the 2.45 GHz microwave ion source for optimum performance during the online operation. In this paper we present a comparison of the two methods which have been used to design the optimum PID controller parameters: one by optimizing different time domain performance indices such as lAE, ITSE etc. and other using analytical formulation based on Linear Quadratic Regulator (LQR). We have performed numerical simulations using MATLAB and compare the closed loop time response performance measures using the PID parameters obtained from above mentioned two methods on a second order transfer function of a DC motor with time delay. (author)

  12. Towards an atrio-ventricular delay optimization assessed by a computer model for cardiac resynchronization therapy

    Science.gov (United States)

    Ojeda, David; Le Rolle, Virginie; Tse Ve Koon, Kevin; Thebault, Christophe; Donal, Erwan; Hernández, Alfredo I.

    2013-11-01

    In this paper, lumped-parameter models of the cardiovascular system, the cardiac electrical conduction system and a pacemaker are coupled to generate mitral ow pro les for di erent atrio-ventricular delay (AVD) con gurations, in the context of cardiac resynchronization therapy (CRT). First, we perform a local sensitivity analysis of left ventricular and left atrial parameters on mitral ow characteristics, namely E and A wave amplitude, mitral ow duration, and mitral ow time integral. Additionally, a global sensitivity analysis over all model parameters is presented to screen for the most relevant parameters that a ect the same mitral ow characteristics. Results provide insight on the in uence of left ventricle and atrium in uence on mitral ow pro les. This information will be useful for future parameter estimation of the model that could reproduce the mitral ow pro les and cardiovascular hemodynamics of patients undergoing AVD optimization during CRT.

  13. Factorization and the synthesis of optimal feedback kernels for differential-delay systems

    Science.gov (United States)

    Milman, Mark M.; Scheid, Robert E.

    1987-01-01

    A combination of ideas from the theories of operator Riccati equations and Volterra factorizations leads to the derivation of a novel, relatively simple set of hyperbolic equations which characterize the optimal feedback kernel for the finite-time regulator problem for autonomous differential-delay systems. Analysis of these equations elucidates the underlying structure of the feedback kernel and leads to the development of fast and accurate numerical methods for its computation. Unlike traditional formulations based on the operator Riccati equation, the gain is characterized by means of classical solutions of the derived set of equations. This leads to the development of approximation schemes which are analogous to what has been accomplished for systems of ordinary differential equations with given initial conditions.

  14. Optimal robust stabilizer design based on UPFC for interconnected power systems considering time delay

    Directory of Open Access Journals (Sweden)

    Koofigar Hamid Reza

    2017-09-01

    Full Text Available A robust auxiliary wide area damping controller is proposed for a unified power flow controller (UPFC. The mixed H2 / H∞ problem with regional pole placement, resolved by linear matrix inequality (LMI, is applied for controller design. Based on modal analysis, the optimal wide area input signals for the controller are selected. The time delay of input signals, due to electrical distance from the UPFC location is taken into account in the design procedure. The proposed controller is applied to a multi-machine interconnected power system from the IRAN power grid. It is shown that the both transient and dynamic stability are significantly improved despite different disturbances and loading conditions.

  15. Energy and delay trade-offs in arithmetic circuits: Methodologies and optimizations

    Science.gov (United States)

    Baran, Dursun

    Technology scaling cannot provide sufficient amount of energy reduction to keep control of the energy consumption of the current VLSI systems. In order to solve the problem of the high power dissipation of current processors, a complete optimization framework is developed. The system architecture, circuit topology, gate sizes and the technology related parameters are optimized jointly. For this purpose, circuit design methodologies are developed for demanded applications. The developed circuit design techniques target two objectives namely critical path complexity reduction of the circuit and the equalization of the signal path complexities. The generated circuit topologies are candidates for the energy efficient design. The final determination of the best circuit topology is made after optimizing the gate sizes and the voltage supply of the design. For this purpose, a quick circuit sizing algorithm (Constant Stage Effort Ratio) is developed. The algorithm redistributes the effort delay through the circuit to reduce the energy consumption at the same performance. The run-time of the developed algorithm linearly depends on the number of the logic gates in the circuit. By using the developed algorithm, a considerable amount of the run-time improvement is obtained. The developed optimization framework is applied to the parallel prefix adders and parallel multipliers. Up to 4.5X energy saving is obtained by the use of the design methodologies in 64-bit parallel adders over existing designs. Energy-efficient parallel adder structures are developed for static, domino and compound domino logic families. The suitability of the developed design techniques are explored in future technology nodes as well. Similar analysis is performed to the parallel multipliers. 16x16-bit serial, single-cycle parallel and two-cycle parallel multiplier structures are optimized using the developed optimization flow. Up to 20% energy reduction is obtained in static single-cycle 16x16-bit

  16. Environment-Aware Production Scheduling for Paint Shops in Automobile Manufacturing: A Multi-Objective Optimization Approach

    Directory of Open Access Journals (Sweden)

    Rui Zhang

    2017-12-01

    Full Text Available The traditional way of scheduling production processes often focuses on profit-driven goals (such as cycle time or material cost while tending to overlook the negative impacts of manufacturing activities on the environment in the form of carbon emissions and other undesirable by-products. To bridge the gap, this paper investigates an environment-aware production scheduling problem that arises from a typical paint shop in the automobile manufacturing industry. In the studied problem, an objective function is defined to minimize the emission of chemical pollutants caused by the cleaning of painting devices which must be performed each time before a color change occurs. Meanwhile, minimization of due date violations in the downstream assembly shop is also considered because the two shops are interrelated and connected by a limited-capacity buffer. First, we have developed a mixed-integer programming formulation to describe this bi-objective optimization problem. Then, to solve problems of practical size, we have proposed a novel multi-objective particle swarm optimization (MOPSO algorithm characterized by problem-specific improvement strategies. A branch-and-bound algorithm is designed for accurately assessing the most promising solutions. Finally, extensive computational experiments have shown that the proposed MOPSO is able to match the solution quality of an exact solver on small instances and outperform two state-of-the-art multi-objective optimizers in literature on large instances with up to 200 cars.

  17. Numerical solution of the state-delayed optimal control problems by a fast and accurate finite difference θ-method

    Science.gov (United States)

    Hajipour, Mojtaba; Jajarmi, Amin

    2018-02-01

    Using the Pontryagin's maximum principle for a time-delayed optimal control problem results in a system of coupled two-point boundary-value problems (BVPs) involving both time-advance and time-delay arguments. The analytical solution of this advance-delay two-point BVP is extremely difficult, if not impossible. This paper provides a discrete general form of the numerical solution for the derived advance-delay system by applying a finite difference θ-method. This method is also implemented for the infinite-time horizon time-delayed optimal control problems by using a piecewise version of the θ-method. A matrix formulation and the error analysis of the suggested technique are provided. The new scheme is accurate, fast and very effective for the optimal control of linear and nonlinear time-delay systems. Various types of finite- and infinite-time horizon problems are included to demonstrate the accuracy, validity and applicability of the new technique.

  18. Chronic cocaine exposure in adolescence: Effects on spatial discrimination reversal, delay discounting, and performance on fixed-ratio schedules in mice.

    Science.gov (United States)

    Pope, Derek A; Boomhower, Steven R; Hutsell, Blake A; Teixeira, Kathryn M; Newland, M Christopher

    2016-04-01

    Adolescence is marked by the continued development of the neural pathways that support choice and decision-making, particularly those involving dopamine signaling. Cocaine exposure during adolescence may interfere with this development and manifest as increased perseveration and delay discounting in adulthood, behavioral processes that are related to drug addiction. Adolescent mice were exposed to 30mg/kg/day of cocaine (n=11) or saline vehicle (n=10) for 14days and behavior was assessed in adulthood. In Experiment 1, performance on a spatial-discrimination-reversal procedure was evaluated. In the first two sessions following the first reversal, cocaine-exposed mice produced more preservative errors relative to controls. In Experiment 2, cocaine-exposed mice displayed steeper delay discounting than saline-exposed mice, effects that were reversed by acute cocaine administration. Experiment 3 examined responding maintained by a range of fixed-ratio schedules of reinforcement. An analysis based on a theoretical framework called Mathematical Principles of Reinforcement (MPR) was applied to response-rate functions of individual mice. According to MPR, differences in response-rate functions in adulthood were due to a steepening of the delay-of-reinforcement gradient, disrupted motoric capacity (lower maximum response rates), and enhanced reinforcer efficacy for the adolescent cocaine- compared with saline-exposed mice. Overall, these experiments suggest that chronic exposure to cocaine during adolescence may impair different features of 'executive functions' in adulthood, and these may be related to distortions in the impact of reinforcing events. Copyright © 2016 Elsevier Inc. All rights reserved.

  19. A Multi-Verse Optimizer with Levy Flights for Numerical Optimization and Its Application in Test Scheduling for Network-on-Chip.

    Directory of Open Access Journals (Sweden)

    Cong Hu

    Full Text Available We propose a new meta-heuristic algorithm named Levy flights multi-verse optimizer (LFMVO, which incorporates Levy flights into multi-verse optimizer (MVO algorithm to solve numerical and engineering optimization problems. The Original MVO easily falls into stagnation when wormholes stochastically re-span a number of universes (solutions around the best universe achieved over the course of iterations. Since Levy flights are superior in exploring unknown, large-scale search space, they are integrated into the previous best universe to force MVO out of stagnation. We test this method on three sets of 23 well-known benchmark test functions and an NP complete problem of test scheduling for Network-on-Chip (NoC. Experimental results prove that the proposed LFMVO is more competitive than its peers in both the quality of the resulting solutions and convergence speed.

  20. A Multi-Verse Optimizer with Levy Flights for Numerical Optimization and Its Application in Test Scheduling for Network-on-Chip.

    Science.gov (United States)

    Hu, Cong; Li, Zhi; Zhou, Tian; Zhu, Aijun; Xu, Chuanpei

    2016-01-01

    We propose a new meta-heuristic algorithm named Levy flights multi-verse optimizer (LFMVO), which incorporates Levy flights into multi-verse optimizer (MVO) algorithm to solve numerical and engineering optimization problems. The Original MVO easily falls into stagnation when wormholes stochastically re-span a number of universes (solutions) around the best universe achieved over the course of iterations. Since Levy flights are superior in exploring unknown, large-scale search space, they are integrated into the previous best universe to force MVO out of stagnation. We test this method on three sets of 23 well-known benchmark test functions and an NP complete problem of test scheduling for Network-on-Chip (NoC). Experimental results prove that the proposed LFMVO is more competitive than its peers in both the quality of the resulting solutions and convergence speed.

  1. Decoupling algorithms from schedules for easy optimization of image processing pipelines

    OpenAIRE

    Adams, Andrew; Paris, Sylvain; Levoy, Marc; Ragan-Kelley, Jonathan Millar; Amarasinghe, Saman P.; Durand, Fredo

    2012-01-01

    Using existing programming tools, writing high-performance image processing code requires sacrificing readability, portability, and modularity. We argue that this is a consequence of conflating what computations define the algorithm, with decisions about storage and the order of computation. We refer to these latter two concerns as the schedule, including choices of tiling, fusion, recomputation vs. storage, vectorization, and parallelism. We propose a representation for feed-forward imagi...

  2. Managing daily surgery schedules in a teaching hospital: a mixed-integer optimization approach

    OpenAIRE

    Pulido Martínez, Raúl; Aguirre, Adrián M.; Ortega Mier, Miguel Ángel; García Sánchez, Álvaro; Méndez, Carlos A.

    2014-01-01

    Background This study examined the daily surgical scheduling problem in a teaching hospital. This problem relates to the use of multiple operating rooms and different types of surgeons in a typical surgical day with deterministic operation durations (preincision, incision, and postincision times). Teaching hospitals play a key role in the health-care system; however, existing models assume that the duration of surgery is independent of the surgeon?s skills. This problem has not been properly ...

  3. Distortion Optimized Packet Scheduling and Prioritization of Multiple Video Streams over 802.11e Networks

    Directory of Open Access Journals (Sweden)

    Ilias Politis

    2007-01-01

    Full Text Available This paper presents a generic framework solution for minimizing video distortion of all multiple video streams transmitted over 802.11e wireless networks, including intelligent packet scheduling and channel access differentiation mechanisms. A distortion prediction model designed to capture the multireferenced frame coding characteristic of H.264/AVC encoded videos is used to predetermine the distortion importance of each video packet in all streams. Two intelligent scheduling algorithms are proposed: the “even-loss distribution,” where each video sender is experiencing the same loss and the “greedy-loss distribution” packet scheduling, where selected packets are dropped over all streams, ensuring that the most significant video stream in terms of picture context and quality characteristics will experience minimum losses. The proposed model has been verified with actual distortion measurements and has been found more accurate than the “additive distortion” model that omits the correlation among lost frames. The paper includes analytical and simulation results from the comparison of both schemes and from their comparison to the simplified additive model, for different video sequences and channel conditions.

  4. Pilot signal design via constrained optimization with application to delay-Doppler shift estimation in OFDM systems

    DEFF Research Database (Denmark)

    Jing, Lishuai; Pedersen, Troels; Fleury, Bernard Henri

    2013-01-01

    We address the problem of searching for the optimal pilot signal, i.e. pattern and signature, of an orthogonal frequency-division multiplexing (OFDM) system when the purpose is to estimate the delay and Doppler shift under the assumption of a single-path propagation channel. This problem is relev......We address the problem of searching for the optimal pilot signal, i.e. pattern and signature, of an orthogonal frequency-division multiplexing (OFDM) system when the purpose is to estimate the delay and Doppler shift under the assumption of a single-path propagation channel. This problem...

  5. Comparison of echocardiography and device based algorithm for atrio-ventricular delay optimization in heart block patients.

    Science.gov (United States)

    Vijayvergiya, Rajesh; Gupta, Ankur

    2015-11-26

    To compare the atrio-ventricular (AV/PV) delay optimization by echocardiography and intra-cardiac electrocardiogram (IEGM) based QuickOpt algorithm in complete heart block (CHB) patients, implanted with a dual chamber pacemaker. We prospectively enrolled 20 patients (age 59.45 ± 18.1 years; male: 65%) with CHB, who were implanted with a dual chamber pacemaker. The left ventricular outflow tract velocity time-integral was measured after AV/PV delay optimization by both echocardiography and QuickOpt algorithm method. Bland-Altman analysis was used for agreement between the two techniques. The optimal AV and PV delay determined by echocardiography was 155.5 ± 14.68 ms and 122.5 ± 17.73 ms (P < 0.0001), respectively and by QuickOpt method was 167.5 ± 16.73 and 117.5 ms ± 9.10 ms (P < 0.0001), respectively. A good agreement was observed between optimal AV and PV delay as measured by two methods. However, the correlation of the optimal AV (r = 0.0689, P = 0.77) and PV (r = 0.2689, P = 0.25) intervals measured by the two techniques was poor. The time required for AV/PV optimization was 45.26 ± 1.73 min by echocardiography and 0.44 ± 0.08 min by QuickOpt method (P < 0.0001). The programmer based IEGM method is an automated, quick, easier and reliable alternative to echocardiography for the optimization of AV/PV delay in CHB patients, implanted with a dual chamber pacemaker.

  6. Short-term cascaded hydroelectric system scheduling based on chaotic particle swarm optimization using improved logistic map

    Science.gov (United States)

    He, Yaoyao; Yang, Shanlin; Xu, Qifa

    2013-07-01

    In order to solve the model of short-term cascaded hydroelectric system scheduling, a novel chaotic particle swarm optimization (CPSO) algorithm using improved logistic map is introduced, which uses the water discharge as the decision variables combined with the death penalty function. According to the principle of maximum power generation, the proposed approach makes use of the ergodicity, symmetry and stochastic property of improved logistic chaotic map for enhancing the performance of particle swarm optimization (PSO) algorithm. The new hybrid method has been examined and tested on two test functions and a practical cascaded hydroelectric system. The experimental results show that the effectiveness and robustness of the proposed CPSO algorithm in comparison with other traditional algorithms.

  7. Optimization of the heat treatment schedule for next european dipole (NED) powder in tube $Nb_{3}Sn$ strand

    CERN Document Server

    Boutboul, T; den Ouden, A; Pedrini, D; Volpini, G

    2009-01-01

    A Nb3Sn strand was successfully developed by the company SMI for Next European Dipole (NED) activity and on the basis of Powder-In-Tube (PIT) method. This strand, after the standard reaction recommended by the firm (84 h @ 675 oC), presents attractive performances as a critical current density in the non-copper part of ~ 2500 A/mm2 for 4.2 K and 12 T applied field, an effective filament diameter of ~ 50 μm and limited flux jumps at low magnetic fields. Heat treatment optimization studies are currently performed at CERN to try to optimize the strand electric abilities. For this purpose, various heat treatment schedules were already investigated with a plateau temperature as low as 625 oC. The preliminary results of these studies are summarized here.

  8. An Optimization Scheduling Model for Wind Power and Thermal Power with Energy Storage System considering Carbon Emission Trading

    Directory of Open Access Journals (Sweden)

    Huan-huan Li

    2015-01-01

    Full Text Available Wind power has the characteristics of randomness and intermittence, which influences power system safety and stable operation. To alleviate the effect of wind power grid connection and improve power system’s wind power consumptive capability, this paper took emission trading and energy storage system into consideration and built an optimization model for thermal-wind power system and energy storage systems collaborative scheduling. A simulation based on 10 thermal units and wind farms with 2800 MW installed capacity verified the correctness of the models put forward by this paper. According to the simulation results, the introduction of carbon emission trading can improve wind power consumptive capability and cut down the average coal consumption per unit of power. The introduction of energy storage system can smooth wind power output curve and suppress power fluctuations. The optimization effects achieve the best when both of carbon emission trading and energy storage system work at the same time.

  9. Message Scheduling and Forwarding in Congested DTNs

    KAUST Repository

    Elwhishi, Ahmed

    2012-08-19

    Multi-copy utility-based routing has been considered as one of the most applicable approaches to effective message delivery in Delay Tolerant Networks (DTNs). By allowing multiple message replicas launched, the ratio of message delivery or delay can be significantly reduced compared with other counterparts. Such an advantage, nonetheless, is at the expense of taking more buffer space at each node and higher complexity in message forwarding decisions. This paper investigates an efficient message scheduling and dropping policy via analytical modeling approach, aiming to achieve optimal performance in terms of message delivery delay. Extensive simulation results, based on a synthetic mobility model and real mobility traces, show that the proposed scheduling framework can achieve superb performance against its counterparts in terms of delivery delay.

  10. Radiation therapy for painful bone metastases. Aiming at optimal treatment schedules

    International Nuclear Information System (INIS)

    Murakami, Ryuji; Saito, Ryuichi; Miyazaki, Toshiyuki; Takahashi, Mutsumasa

    2001-01-01

    The purpose of this study is to evaluate the pain relief obtained by radiation therapy for painful bone metastases, with a special regard to general condition. Between June 1998 and May 2000, 54 patients with 86 painful bone metastases were treated with radiation therapy whose effects could be evaluated for a minimum period of 6 months or until death. Treatment schedules were 3 Gy/fraction/day (30-36 Gy/10-12 fractions) in usual cases (61 lesions), 4-8 Gy/fraction/day (8-20 Gy/1-5 fractions) in patients with a poor general condition (9 lesions), and 2 Gy/fraction/day (40-50 Gy/20-25 fractions) in lesions with a large radiation field (16 lesions). Complete pain relief without medication (CR) was achieved in 40 lesions (47%). Significant predictors for CR were primary site (p=0.0003), performance status (p=0.0060), pain score (p=00190), narcotic score (p<0.0001), and prognosis (p<0.0001), but no difference was found in CR among treatment schedules. No evidence of severe radiation-induced complication was seen. General condition (performance status and prognosis) has an influence on pain relief. Compared with the daily 2 Gy protocol, the daily 3 Gy protocol has the advantage of shorter treatment time. The treatment schedule should be assessed in patients with a large radiation field and/or poor general condition. Especially for the patients with poor general condition, combined pain medication should be considered. (author)

  11. Depositional features of the Middle Jurassic formation of Field N and their influence on optimal drilling schedule

    Science.gov (United States)

    Mishina, D.; Rukavishnikov, V.; Belozerov, B.; Bochkov, A.

    2015-02-01

    The Middle Jurassic formation of Field N represented by 4 hydrodynamically connected layers (J5-6, J4, J3 and J2) contains 42% of the field STOIIP. The J2-6 formation is characterized as a gas-oil-condensate massive lithologically and tectonically screened accumulation with a gas cap (J2, J3 layers) and bottom water (J5-6 layer). Oil is predominantly in the J3 and J4 layers. There is a high risk of early gas coning from gas-bearing layers to oil producing wells determined on the basis of production test results, which can significantly decrease the life of the well. To select a more optimal drilling schedule, it is necessary to take the risk of early gas coning into account and determine distinctive features within the gas- saturated zone that can reduce it. The presence of a thick shale barrier between the J2 and J3 layers with thicknesses varying from 0 to 30 m is recognized as the beginning of a transgression cycle, and if the gas cap is only in the J2 layer, this barrier with the thickness of more than 5 m can extensively prevent early gas coning into oil producing wells. The integration of geological information represented by the probability map constructed and petrophysical information represented by the kh map provide the more precise determination of an optimal drilling schedule.

  12. Optimal Scheduling of Railway Track Possessions in Large-Scale Projects with Multiple Construction Works

    DEFF Research Database (Denmark)

    Li, Rui; Roberti, Roberto

    2017-01-01

    This paper addresses the railway track possession scheduling problem (RTPSP), where a large-scale railway infrastructure project consisting of multiple construction works is to be planned. The RTPSP is to determine when to perform the construction works and in which track possessions while...... by solving a mixed-integer linear-programming model for the given track blocking proposal. The proposed approach is tested on a real-life case study from the Danish railway infrastructure manager. The results show that, in 2 h of computing time, the approach is able to provide solutions that are within 0...

  13. An Optimization of Manufacturing Systems using a Feedback Control Scheduling Model

    Science.gov (United States)

    Ikome, John M.; Kanakana, Grace M.

    2018-03-01

    In complex production system that involves multiple process, unplanned disruption often turn to make the entire production system vulnerable to a number of problems which leads to customer’s dissatisfaction. However, this problem has been an ongoing problem that requires a research and methods to streamline the entire process or develop a model that will address it, in contrast to this, we have developed a feedback scheduling model that can minimize some of this problem and after a number of experiment, it shows that some of this problems can be eliminated if the correct remedial actions are implemented on time.

  14. Optimal control of an electric vehicle’s charging schedule under electricity markets

    DEFF Research Database (Denmark)

    Lan, Tian; Hu, Junjie; Kang, Qi

    2013-01-01

    ), since the hourly electricity prices are different in the market. In this paper, the problem is formulated into an optimal control one and solved by dynamic programming. Optimization aims to find the economically optimal charging solution for each vehicle. In this paper, a nonlinear battery model......As increasing numbers of electric vehicles (EVs) enter into the society, the charging behavior of EVs has got lots of attention due to its economical difference within the electricity market. The charging cost for EVs generally differ from each other in choosing the charging time interval (hourly...

  15. Ant colony optimization and event-based dynamic task scheduling and staffing for software projects

    Science.gov (United States)

    Ellappan, Vijayan; Ashwini, J.

    2017-11-01

    In programming change organizations from medium to inconceivable scale broadens, the issue of wander orchestrating is amazingly unusual and testing undertaking despite considering it a manual system. Programming wander-organizing requirements to deal with the issue of undertaking arranging and in addition the issue of human resource portion (also called staffing) in light of the way that most of the advantages in programming ventures are individuals. We propose a machine learning approach with finds respond in due order regarding booking by taking in the present arranging courses of action and an event based scheduler revives the endeavour arranging system moulded by the learning computation in perspective of the conformity in event like the begin with the Ander, the instant at what time possessions be free starting to ended errands, and the time when delegates stick together otherwise depart the wander inside the item change plan. The route toward invigorating the timetable structure by the even based scheduler makes the arranging method dynamic. It uses structure components to exhibit the interrelated surges of endeavours, slip-ups and singular all through different progression organizes and is adjusted to mechanical data. It increases past programming wander movement ask about by taking a gander at a survey based process with a one of a kind model, organizing it with the data based system for peril assessment and cost estimation, and using a choice showing stage.

  16. Simulated Annealing-Based Ant Colony Algorithm for Tugboat Scheduling Optimization

    Directory of Open Access Journals (Sweden)

    Qi Xu

    2012-01-01

    Full Text Available As the “first service station” for ships in the whole port logistics system, the tugboat operation system is one of the most important systems in port logistics. This paper formulated the tugboat scheduling problem as a multiprocessor task scheduling problem (MTSP after analyzing the characteristics of tugboat operation. The model considers factors of multianchorage bases, different operation modes, and three stages of operations (berthing/shifting-berth/unberthing. The objective is to minimize the total operation times for all tugboats in a port. A hybrid simulated annealing-based ant colony algorithm is proposed to solve the addressed problem. By the numerical experiments without the shifting-berth operation, the effectiveness was verified, and the fact that more effective sailing may be possible if tugboats return to the anchorage base timely was pointed out; by the experiments with the shifting-berth operation, one can see that the objective is most sensitive to the proportion of the shifting-berth operation, influenced slightly by the tugboat deployment scheme, and not sensitive to the handling operation times.

  17. Optimally Scheduling Distribution of the MH-60S Helicopter and Pilots to Combat Support (HC) Squadrons

    National Research Council Canada - National Science Library

    Culver, Cory

    2002-01-01

    ... (Optimal Transition HC Allocation Model) that minimizes lost flying days. OTHCAM takes into account variable training durations, travel times and tour lengths as well as manpower and aircraft constraints...

  18. A TOTP-Based Enhanced Route Optimization Procedure for Mobile IPv6 to Reduce Handover Delay and Signalling Overhead

    Science.gov (United States)

    Shah, Peer Azmat; Hasbullah, Halabi B.; Lawal, Ibrahim A.; Aminu Mu'azu, Abubakar; Tang Jung, Low

    2014-01-01

    Due to the proliferation of handheld mobile devices, multimedia applications like Voice over IP (VoIP), video conferencing, network music, and online gaming are gaining popularity in recent years. These applications are well known to be delay sensitive and resource demanding. The mobility of mobile devices, running these applications, across different networks causes delay and service disruption. Mobile IPv6 was proposed to provide mobility support to IPv6-based mobile nodes for continuous communication when they roam across different networks. However, the Route Optimization procedure in Mobile IPv6 involves the verification of mobile node's reachability at the home address and at the care-of address (home test and care-of test) that results in higher handover delays and signalling overhead. This paper presents an enhanced procedure, time-based one-time password Route Optimization (TOTP-RO), for Mobile IPv6 Route Optimization that uses the concepts of shared secret Token, time based one-time password (TOTP) along with verification of the mobile node via direct communication and maintaining the status of correspondent node's compatibility. The TOTP-RO was implemented in network simulator (NS-2) and an analytical analysis was also made. Analysis showed that TOTP-RO has lower handover delays, packet loss, and signalling overhead with an increased level of security as compared to the standard Mobile IPv6's Return-Routability-based Route Optimization (RR-RO). PMID:24688398

  19. A TOTP-Based Enhanced Route Optimization Procedure for Mobile IPv6 to Reduce Handover Delay and Signalling Overhead

    Directory of Open Access Journals (Sweden)

    Peer Azmat Shah

    2014-01-01

    Full Text Available Due to the proliferation of handheld mobile devices, multimedia applications like Voice over IP (VoIP, video conferencing, network music, and online gaming are gaining popularity in recent years. These applications are well known to be delay sensitive and resource demanding. The mobility of mobile devices, running these applications, across different networks causes delay and service disruption. Mobile IPv6 was proposed to provide mobility support to IPv6-based mobile nodes for continuous communication when they roam across different networks. However, the Route Optimization procedure in Mobile IPv6 involves the verification of mobile node’s reachability at the home address and at the care-of address (home test and care-of test that results in higher handover delays and signalling overhead. This paper presents an enhanced procedure, time-based one-time password Route Optimization (TOTP-RO, for Mobile IPv6 Route Optimization that uses the concepts of shared secret Token, time based one-time password (TOTP along with verification of the mobile node via direct communication and maintaining the status of correspondent node’s compatibility. The TOTP-RO was implemented in network simulator (NS-2 and an analytical analysis was also made. Analysis showed that TOTP-RO has lower handover delays, packet loss, and signalling overhead with an increased level of security as compared to the standard Mobile IPv6’s Return-Routability-based Route Optimization (RR-RO.

  20. A TOTP-based enhanced route optimization procedure for mobile IPv6 to reduce handover delay and signalling overhead.

    Science.gov (United States)

    Shah, Peer Azmat; Hasbullah, Halabi B; Lawal, Ibrahim A; Aminu Mu'azu, Abubakar; Tang Jung, Low

    2014-01-01

    Due to the proliferation of handheld mobile devices, multimedia applications like Voice over IP (VoIP), video conferencing, network music, and online gaming are gaining popularity in recent years. These applications are well known to be delay sensitive and resource demanding. The mobility of mobile devices, running these applications, across different networks causes delay and service disruption. Mobile IPv6 was proposed to provide mobility support to IPv6-based mobile nodes for continuous communication when they roam across different networks. However, the Route Optimization procedure in Mobile IPv6 involves the verification of mobile node's reachability at the home address and at the care-of address (home test and care-of test) that results in higher handover delays and signalling overhead. This paper presents an enhanced procedure, time-based one-time password Route Optimization (TOTP-RO), for Mobile IPv6 Route Optimization that uses the concepts of shared secret Token, time based one-time password (TOTP) along with verification of the mobile node via direct communication and maintaining the status of correspondent node's compatibility. The TOTP-RO was implemented in network simulator (NS-2) and an analytical analysis was also made. Analysis showed that TOTP-RO has lower handover delays, packet loss, and signalling overhead with an increased level of security as compared to the standard Mobile IPv6's Return-Routability-based Route Optimization (RR-RO).

  1. A Jackson network model and threshold policy for joint optimization of energy and delay in multi-hop wireless networks

    KAUST Repository

    Xia, Li

    2014-11-20

    This paper studies the joint optimization problem of energy and delay in a multi-hop wireless network. The optimization variables are the transmission rates, which are adjustable according to the packet queueing length in the buffer. The optimization goal is to minimize the energy consumption of energy-critical nodes and the packet transmission delay throughout the network. In this paper, we aim at understanding the well-known decentralized algorithms which are threshold based from a different research angle. By using a simplified network model, we show that we can adopt the semi-open Jackson network model and study this optimization problem in closed form. This simplified network model further allows us to establish some significant optimality properties. We prove that the system performance is monotonic with respect to (w.r.t.) the transmission rate. We also prove that the threshold-type policy is optimal, i.e., when the number of packets in the buffer is larger than a threshold, transmit with the maximal rate (power); otherwise, no transmission. With these optimality properties, we develop a heuristic algorithm to iteratively find the optimal threshold. Finally, we conduct some simulation experiments to demonstrate the main idea of this paper.

  2. Temporally Dependent Rate-Distortion Optimization for Low-Delay Hierarchical Video Coding.

    Science.gov (United States)

    Gao, Yanbo; Zhu, Ce; Li, Shuai; Yang, Tianwu

    2017-09-01

    Low-delay hierarchical coding structure (LD-HCS), as one of the most important components in the latest High Efficiency Video Coding (HEVC) standard, greatly improves coding performance. It groups consecutive P/B frames into different layers and encodes them with different quantization parameters (QPs) and reference mechanisms in such a way that temporal dependency among frames can be exploited. However, due to varying characteristics of video contents, temporal dependency among coding units differs significantly from each other in the same or different layers, while a fixed LD-HCS scheme cannot take full advantage of the dependency, leading to a substantial loss in coding performance. This paper addresses the temporally dependent rate distortion optimization (RDO) problem by attempting to exploit varying temporal dependency of different units. First, the temporal relationship of different frames under the LD-HCS is examined, and hierarchical temporal propagation chains are constructed to represent the temporal dependency among coding units in different frames. Then, a hierarchical temporally dependent RDO scheme is developed specifically for the LD-HCS based on a source distortion propagation model. Experimental results show that our proposed scheme can achieve 2.5% and 2.3% BD-rate gain in average compared with the HEVC codec under the same configuration of P and B frames, respectively, with a negligible increase in encoding time. Furthermore, coupled with QP adaption, our proposed method can achieve higher coding gains, e.g., with multi-QP optimization, about 5.4% and 5.0% BD-rate saving in average over the HEVC codec under the same setting of P and B frames, respectively.

  3. Capacity optimization and scheduling of a multiproduct manufacturing facility for biotech products.

    Science.gov (United States)

    Shaik, Munawar A; Dhakre, Ankita; Rathore, Anurag S; Patil, Nitin

    2014-01-01

    A general mathematical framework has been proposed in this work for scheduling of a multiproduct and multipurpose facility involving manufacturing of biotech products. The specific problem involves several batch operations occurring in multiple units involving fixed processing time, unlimited storage policy, transition times, shared units, and deterministic and fixed data in the given time horizon. The different batch operations are modeled using state-task network representation. Two different mathematical formulations are proposed based on discrete- and continuous-time representations leading to a mixed-integer linear programming model which is solved using General Algebraic Modeling System software. A case study based on a real facility is presented to illustrate the potential and applicability of the proposed models. The continuous-time model required less number of events and has a smaller problem size compared to the discrete-time model. © 2014 American Institute of Chemical Engineers.

  4. Optimal Day-Ahead Scheduling of a Hybrid Electric Grid Using Weather Forecasts

    Science.gov (United States)

    2013-12-01

    energy marketing, electrical and power engineering . We focus in this literature review on the optimization of the HEG in terms of design and operating...nacelle to rotate into the wind with an optimal angle β. The yawing mechanism can be passive, like a tail vane on smaller wind turbines, or active with...gCONTRIB ON g k k k warmup k k       (Eq. 13) , , : gg k gCON InitialCTRIB g k

  5. Optimally Scheduled Deployments of Miniature Trailing-Edge Effectors for Rotorcraft Power Reduction

    OpenAIRE

    Bae, Eui Sung; Gandhi, Farhan; Maughmer, Mark

    2017-01-01

    Spanwise-segmented Miniature Trailing-Edge Effectors (MiTEs), essentially deployable Gurney flaps, were examined for rotorcraft power reduction. Four MiTEs, extending from 50-60%, 60-70%, 70-80% and 80-90% span, were considered and actuated at frequencies of 1/rev and 2/rev. A gradient-based optimization scheme was used to determine the optimal deployment of the MiTEs, while satisfying vehicle trim. Studies were based on a UH-60 type aircraft and the effect of the MiTEs was examined at modera...

  6. Optimal filtering for systems with finite-step autocorrelated process noises, random one-step sensor delay and missing measurements

    Science.gov (United States)

    Chen, Dongyan; Xu, Long; Du, Junhua

    2016-03-01

    The optimal filtering problem is investigated for a class of discrete stochastic systems with finite-step autocorrelated process noises, random one-step sensor delay and missing measurements. The random disturbances existing in the system are characterized by the multiplicative noises and the phenomena of sensor delay and missing measurements occur in a random way. The random sensor delay and missing measurements are described by two Bernoulli distributed random variables with known conditional probabilities. By using the state augmentation approach, the original system is converted into a new discrete system where the random one-step sensor delay and missing measurements exist in the sensor output. The new process noises and observation noises consist of the original stochastic terms, and the process noises are still autocorrelated. Then, based on the minimum mean square error (MMSE) principle, a new linear optimal filter is designed such that, for the finite-step autocorrelated process noises, random one-step sensor delay and missing measurements, the estimation error is minimized. By solving the recursive matrix equation, the filter gain is designed. Finally, a simulation example is given to illustrate the feasibility and effectiveness of the proposed filtering scheme.

  7. Nucleus accumbens core lesions induce sub-optimal choice and reduce sensitivity to magnitude and delay in impulsive choice tasks

    Science.gov (United States)

    Steele, Catherine C.; Peterson, Jennifer R.; Marshall, Andrew T.; Stuebing, Sarah L.; Kirkpatrick, Kimberly

    2017-01-01

    The nucleus accumbens core (NAc) has long been recognized as an important contributor to the computation of reward value that is critical for impulsive choice behavior. Impulsive choice refers to choosing a smaller-sooner (SS) over a larger-later (LL) reward when the LL is more optimal in terms of the rate of reward delivery. Two experiments examined the role of the NAc in impulsive choice and its component processes of delay and magnitude processing. Experiment 1 delivered an impulsive choice task with manipulations of LL reward magnitude, followed by a reward magnitude discrimination task. Experiment 2 tested impulsive choice under manipulations of LL delay, followed by temporal bisection and progressive interval tasks. NAc lesions, in comparison to sham control lesions, produced suboptimal preferences that resulted in lower reward earning rates, and led to reduced sensitivity to magnitude and delay within the impulsive choice task. The secondary tasks revealed intact reward magnitude and delay discrimination abilities, but the lesion rats persisted in responding more as the progressive interval increased during the session. The results suggest that the NAc is most critical for demonstrating good sensitivity to magnitude and delay, and adjusting behavior accordingly. Ultimately, the NAc lesions induced suboptimal choice behavior rather than simply promoting impulsive choice, suggesting that an intact NAc is necessary for optimal decision making. PMID:29146281

  8. Portfolio optimization using Mixture Design of Experiments. Scheduling trades within electricity markets

    International Nuclear Information System (INIS)

    Oliveira, Francisco Alexandre de; Paiva, Anderson Paulo de; Lima, Jose Wanderley Marangon; Balestrassi, Pedro Paulo; Mendes, Rona Rinston Amaury

    2011-01-01

    Deregulation of the electricity sector has given rise to several approaches to defining optimal portfolios of energy contracts. Financial tools - requiring substantial adjustments - are usually used to determine risk and return. This article presents a novel approach to adjusting the conditional value at risk (CVaR) metric to the mix of contracts on the energy markets; the approach uses Mixture Design of Experiments (MDE). In this kind of experimental strategy, the design factors are treated as proportions in a mixture system considered quite adequate for treating portfolios in general. Instead of using traditional linear programming, the concept of desirability function is here used to combine the multi-response, nonlinear objective functions for mean with the variance of a specific portfolio obtained through MDE. The maximization of the desirability function is implied in the portfolio optimization, generating an efficient recruitment frontier. This approach offers three main contributions: it includes risk aversion in the optimization routine, it assesses interaction between contracts, and it lessens the computational effort required to solve the constrained nonlinear optimization problem. A case study based on the Brazilian energy market is used to illustrate the proposal. The numerical results verify the proposal's adequacy. (author)

  9. Portfolio optimization using Mixture Design of Experiments. Scheduling trades within electricity markets

    Energy Technology Data Exchange (ETDEWEB)

    Oliveira, Francisco Alexandre de; Paiva, Anderson Paulo de; Lima, Jose Wanderley Marangon; Balestrassi, Pedro Paulo; Mendes, Rona Rinston Amaury [Federal Univ. of Itajuba, Minas Gerais (Brazil)

    2011-01-15

    Deregulation of the electricity sector has given rise to several approaches to defining optimal portfolios of energy contracts. Financial tools - requiring substantial adjustments - are usually used to determine risk and return. This article presents a novel approach to adjusting the conditional value at risk (CVaR) metric to the mix of contracts on the energy markets; the approach uses Mixture Design of Experiments (MDE). In this kind of experimental strategy, the design factors are treated as proportions in a mixture system considered quite adequate for treating portfolios in general. Instead of using traditional linear programming, the concept of desirability function is here used to combine the multi-response, nonlinear objective functions for mean with the variance of a specific portfolio obtained through MDE. The maximization of the desirability function is implied in the portfolio optimization, generating an efficient recruitment frontier. This approach offers three main contributions: it includes risk aversion in the optimization routine, it assesses interaction between contracts, and it lessens the computational effort required to solve the constrained nonlinear optimization problem. A case study based on the Brazilian energy market is used to illustrate the proposal. The numerical results verify the proposal's adequacy. (author)

  10. Energy Optimization for Distributed Energy Resources Scheduling with Enhancements in Voltage Stability Margin

    DEFF Research Database (Denmark)

    Morais, Hugo; Sousa, Tiago; Perez, Angel

    2016-01-01

    to evaluate the resulting multiobjective optimization problem: the sum-weighted Pareto front and an adapted goal programming methodology. With this new methodology, the system operators can consider both the costs and voltage stability. Priority can be assigned to one objective function according...

  11. Move-optimal schedules for parallel machines to minimize total weighted completion time

    NARCIS (Netherlands)

    Brueggemann, T.; Hurink, Johann L.; Kern, Walter

    2005-01-01

    We study the minimum total weighted completion time problem on identical machines, which is known to be strongly $\\mathcal{NP}$-hard. We analyze a simple local search heuristic, moving jobs from one machine to another. The local optima can be shown to be approximately optimal with approximation

  12. Optimal resource allocation and load scheduling for a multi-commodity smart energy system

    NARCIS (Netherlands)

    Blaauwbroek, N.; Nguyen, P.H.; Shi, H.; Kamphuis, I.G.; Kling, W.L.; Konsman, M.J.

    2015-01-01

    The increasing introduction of district heating systems together with hybrid energy appliances as heat pumps and micro-combined heat and power installations, results in new opportunities for optimizing the available resources in multi-commodity smart energy systems, including electricity, heat and

  13. Quality of Move-Optimal Schedules for Minimizing the Vector Norm of the Workloads

    NARCIS (Netherlands)

    Brueggemann, T.; Hurink, Johann L.

    2006-01-01

    We study the problem of minimizing the vector norm $||\\cdot||_p$ of the workloads. We examine move-optimal assignments and prove a performance guarantee of $\\frac{2^p-1}{p} \\cdot \\left(\\frac{p-1}{2^p-2}\\right)^{\\frac{p-1}{p}},$ for any integer $p>1$ and moreover, we show that this guarantee is

  14. Optimal Scheduling Using Branch and Bound with SPIN 4.0

    NARCIS (Netherlands)

    Ruys, T.C.; Ball, T.; Rajamani, S.K.

    2003-01-01

    The use of model checkers to solve discrete optimisation problems is appealing. A model checker can first be used to verify that the model of the problem is correct. Subsequently, the same model can be used to find an optimal solution for the problem. This paper describes how to apply the new

  15. Trade-off between learning and exploitation: the Pareto-optimal versus evolutionarily stable learning schedule in cumulative cultural evolution.

    Science.gov (United States)

    Wakano, Joe Yuichiro; Miura, Chiaki

    2014-02-01

    Inheritance of culture is achieved by social learning and improvement is achieved by individual learning. To realize cumulative cultural evolution, social and individual learning should be performed in this order in one's life. However, it is not clear whether such a learning schedule can evolve by the maximization of individual fitness. Here we study optimal allocation of lifetime to learning and exploitation in a two-stage life history model under a constant environment. We show that the learning schedule by which high cultural level is achieved through cumulative cultural evolution is unlikely to evolve as a result of the maximization of individual fitness, if there exists a trade-off between the time spent in learning and the time spent in exploiting the knowledge that has been learned in earlier stages of one's life. Collapse of a fully developed culture is predicted by a game-theoretical analysis where individuals behave selfishly, e.g., less learning and more exploiting. The present study suggests that such factors as group selection, the ability of learning-while-working ("on the job training"), or environmental fluctuation might be important in the realization of rapid and cumulative cultural evolution that is observed in humans. Copyright © 2013 Elsevier Inc. All rights reserved.

  16. A Scheduling Model for the Re-entrant Manufacturing System and Its Optimization by NSGA-II

    Directory of Open Access Journals (Sweden)

    Masoud Rabbani

    2016-11-01

    Full Text Available In this study, a two-objective mixed-integer linear programming model (MILP for multi-product re-entrant flow shop scheduling problem has been designed. As a result, two objectives are considered. One of them is maximization of the production rate and the other is the minimization of processing time. The system has m stations and can process several products in a moment. The re-entrant flow shop scheduling problem is well known as NP-hard problem and its complexity has been discussed by several researchers. Given that NSGA-II algorithm is one of the strongest and most applicable algorithm in solving multi-objective optimization problems, it is used to solve this problem. To increase algorithm performance, Taguchi technique is used to design experiments for algorithm’s parameters. Numerical experiments are proposed to show the efficiency and effectiveness of the model. Finally, the results of NSGA-II are compared with SPEA2 algorithm (Strength Pareto Evolutionary Algorithm 2. The experimental results show that the proposed algorithm performs significantly better than the SPEA2.

  17. An Integrated and Optimal Joint Scheduling of Energy Resources to Feed Electrical, Thermal and Potable Water Demands in Remote Area

    Directory of Open Access Journals (Sweden)

    R. Ghaffarpour

    2016-12-01

    Full Text Available The continuous spread of distributed energy resources (DERs such as combined heating and power (CHP, diesel generators, boilers and renewable energy sources provide an effective solution to energy related problems to serve the power and heat demands with minimum cost. Moreover, the DERs may play a significant role for supplying power and heat in rural areas, where grid electricity is not available. Also, some dry areas may face water scarcity and salinity problems. So, one important solution is the use of DERs to drive desalination units in order to solve water scarcity and salinity problems. In this study, the optimal scheduling of DERs and reverse osmosis (RO desalination unit that feed the required electric, thermal and potable water demands are determined. The present paper describes the operation constraints and cost function of components of the system in detail. Operation constraints of generation units as well as feasible region of operation CHP in dual dependency characteristic are taken into account. To confirm the performance of the proposed model the approach is tested on a realistic remote area over a 24-h period. The results show that the economical scheduling of DERs and desalination units can be obtained using proposed methodology by implementing the proposed formulation.

  18. Utility-Optimal Dynamic Rate Allocation under Average End-to-End Delay Requirements

    OpenAIRE

    Hajiesmaili, Mohammad H.; Talebi, Mohammad Sadegh; Khonsari, Ahmad

    2015-01-01

    QoS-aware networking applications such as real-time streaming and video surveillance systems require nearly fixed average end-to-end delay over long periods to communicate efficiently, although may tolerate some delay variations in short periods. This variability exhibits complex dynamics that makes rate control of such applications a formidable task. This paper addresses rate allocation for heterogeneous QoS-aware applications that preserves the long-term end-to-end delay constraint while, s...

  19. Modeling Optimal Scheduling for Pumping System to Minimize Operation Cost and Enhance Operation Reliability

    Directory of Open Access Journals (Sweden)

    Yin Luo

    2012-01-01

    Full Text Available Traditional pump scheduling models neglect the operation reliability which directly relates with the unscheduled maintenance cost and the wear cost during the operation. Just for this, based on the assumption that the vibration directly relates with the operation reliability and the degree of wear, it could express the operation reliability as the normalization of the vibration level. The characteristic of the vibration with the operation point was studied, it could be concluded that idealized flow versus vibration plot should be a distinct bathtub shape. There is a narrow sweet spot (80 to 100 percent BEP to obtain low vibration levels in this shape, and the vibration also follows similar law with the square of the rotation speed without resonance phenomena. Then, the operation reliability could be modeled as the function of the capacity and rotation speed of the pump and add this function to the traditional model to form the new. And contrast with the tradition method, the result shown that the new model could fix the result produced by the traditional, make the pump operate in low vibration, then the operation reliability could increase and the maintenance cost could decrease.

  20. Optimal Routing and Scheduling of Charge for Electric Vehicles: A Case Study

    Directory of Open Access Journals (Sweden)

    J. Barco

    2017-01-01

    Full Text Available There are increasing interests in improving public transportation systems. One of the proposed strategies for this improvement is the use of Battery Electric Vehicles (BEVs. This approach leads to a new challenge as the BEVs’ routing is exposed to the traditional routing problems of conventional vehicles, as well as the particular requirements of the electrical technologies of BEVs. Examples of BEVs’ routing problems include the autonomy, battery degradation, and charge process. This work presents a differential evolution algorithm for solving an electric vehicle routing problem (EVRP. The formulation of the EVRP to be solved is based on a scheme to coordinate the BEVs’ routing and recharge scheduling, considering operation and battery degradation costs. A model based on the longitudinal dynamics equation of motion estimates the energy consumption of each BEV. A case study, consisting of an airport shuttle service scenario, is used to illustrate the proposed methodology. For this transport service, the BEV energy consumption is estimated based on experimentally measured driving patterns.

  1. Optimal Day-ahead Scheduling for Microgrid Participation in Frequency Regulation Markets

    Energy Technology Data Exchange (ETDEWEB)

    Baone, Chaitanya [General Electric; Acharya, Naresh [General Electric; Wiegman, Herman [General Electric

    2016-09-09

    As microgrid installations are steadily growing in the United States and around the world, widespread adoption of commercial microgrids would rely upon the economic benefit to the owners and operators. With the introduction of new market mechanisms and growing penetration of non-traditional generation assets, there is an increasing need and interest in allowing distributed assets to participate in traditional grid services such as frequency regulation. This paper considers the problem of determining the optimal balance of energy and ancillary services for individual microgrid generation assets to participate in such markets. An optimization framework that maximizes the predicted performance of the microgrid over a day-ahead time horizon while accounting for individual asset constraints is proposed. Simulation results on a realistic test system with practical considerations are presented.

  2. A short-term scheduling for the optimal operation of biorefineries

    International Nuclear Information System (INIS)

    Grisi, E.F.; Yusta, J.M.; Khodr, H.M.

    2011-01-01

    This work presents an analysis of the inherent potentialities and characteristics of the sugarcane industries that produce sugar, bioethanol, biogas and bioelectricity and that are being described as 'Biorefineries'. These Biorefineries are capable of producing bio-energy under diverse forms, intended for their own internal consumption and for external sales and marketing. A complex model and simulation are carried out of the processes of a sugarcane industry, with the data characteristic as well as the production costs, prices of products and considerations on the energy demand by basic processes. A Mixed-Integer Linear Programming (MILP) optimization problem formulation and an analysis of optimal solutions in short-term operation are described, taking into account the production cost functions of each commodity and the incomes obtained from selling electricity and other products. The objective is to maximize the hourly plant economic profit in the different scenarios considered in a real case study.

  3. Optimization of nas lemoore scheduling to support a growing aircraft population

    Science.gov (United States)

    2017-03-01

    38 Figure 13. Frequency of Solution Times Used by MSISCHE over All Scenarios with 0% and 5% Optimality Gaps ...the VBA and GAMS code remain invisible to the user. A. INTERFACE Figure 3 through 5 present a few snapshots of the interface. Figure 3 shows the...AC AC wait Total Wait Max AC Wait Total AC AC wait Total Wait Max AC Wait Status Status Possible Solution Gap Time 1 86 86 83 210 210 204 61 0 0 0

  4. Optimal vaccine schedules to maintain measles elimination with a two-dose routine policy.

    Science.gov (United States)

    McKEE, A; Shea, K; Ferrari, M J

    2017-01-01

    Measles was eliminated in the Americas in 2002 by a combination of routine immunizations and supplementary immunization activities. Recent outbreaks underscore the importance of reconsidering vaccine policy in order to maintain elimination. We constructed an age-structured dynamical model for the distribution of immunity in a population with routine immunization and without disease, and analysed the steady state for an idealized age structure and for real age structures of countries in the Americas. We compared the level of immunity maintained by current policy in these countries to the level maintainable by an optimal policy. The optimal age target for the first routine dose of measles vaccine depends on the timing and coverage of both doses. Similarly, the optimal age target for the second dose of measles vaccine depends on the timing and coverage of the first dose. The age targets for the first and second doses of measles vaccine should be adjusted for the post-elimination era, by specifically accounting for current context, including realized coverage of both doses, and altered maternal immunity. Doing so can greatly improve the proportion immune within a population, and therefore the chances of maintaining measles elimination, without changing coverage.

  5. Fuzzy mixed assembly line sequencing and scheduling optimization model using multiobjective dynamic fuzzy GA.

    Science.gov (United States)

    Tahriri, Farzad; Dawal, Siti Zawiah Md; Taha, Zahari

    2014-01-01

    A new multiobjective dynamic fuzzy genetic algorithm is applied to solve a fuzzy mixed-model assembly line sequencing problem in which the primary goals are to minimize the total make-span and minimize the setup number simultaneously. Trapezoidal fuzzy numbers are implemented for variables such as operation and travelling time in order to generate results with higher accuracy and representative of real-case data. An improved genetic algorithm called fuzzy adaptive genetic algorithm (FAGA) is proposed in order to solve this optimization model. In establishing the FAGA, five dynamic fuzzy parameter controllers are devised in which fuzzy expert experience controller (FEEC) is integrated with automatic learning dynamic fuzzy controller (ALDFC) technique. The enhanced algorithm dynamically adjusts the population size, number of generations, tournament candidate, crossover rate, and mutation rate compared with using fixed control parameters. The main idea is to improve the performance and effectiveness of existing GAs by dynamic adjustment and control of the five parameters. Verification and validation of the dynamic fuzzy GA are carried out by developing test-beds and testing using a multiobjective fuzzy mixed production assembly line sequencing optimization problem. The simulation results highlight that the performance and efficacy of the proposed novel optimization algorithm are more efficient than the performance of the standard genetic algorithm in mixed assembly line sequencing model.

  6. Fuzzy Mixed Assembly Line Sequencing and Scheduling Optimization Model Using Multiobjective Dynamic Fuzzy GA

    Directory of Open Access Journals (Sweden)

    Farzad Tahriri

    2014-01-01

    Full Text Available A new multiobjective dynamic fuzzy genetic algorithm is applied to solve a fuzzy mixed-model assembly line sequencing problem in which the primary goals are to minimize the total make-span and minimize the setup number simultaneously. Trapezoidal fuzzy numbers are implemented for variables such as operation and travelling time in order to generate results with higher accuracy and representative of real-case data. An improved genetic algorithm called fuzzy adaptive genetic algorithm (FAGA is proposed in order to solve this optimization model. In establishing the FAGA, five dynamic fuzzy parameter controllers are devised in which fuzzy expert experience controller (FEEC is integrated with automatic learning dynamic fuzzy controller (ALDFC technique. The enhanced algorithm dynamically adjusts the population size, number of generations, tournament candidate, crossover rate, and mutation rate compared with using fixed control parameters. The main idea is to improve the performance and effectiveness of existing GAs by dynamic adjustment and control of the five parameters. Verification and validation of the dynamic fuzzy GA are carried out by developing test-beds and testing using a multiobjective fuzzy mixed production assembly line sequencing optimization problem. The simulation results highlight that the performance and efficacy of the proposed novel optimization algorithm are more efficient than the performance of the standard genetic algorithm in mixed assembly line sequencing model.

  7. Fuzzy Mixed Assembly Line Sequencing and Scheduling Optimization Model Using Multiobjective Dynamic Fuzzy GA

    Science.gov (United States)

    Tahriri, Farzad; Dawal, Siti Zawiah Md; Taha, Zahari

    2014-01-01

    A new multiobjective dynamic fuzzy genetic algorithm is applied to solve a fuzzy mixed-model assembly line sequencing problem in which the primary goals are to minimize the total make-span and minimize the setup number simultaneously. Trapezoidal fuzzy numbers are implemented for variables such as operation and travelling time in order to generate results with higher accuracy and representative of real-case data. An improved genetic algorithm called fuzzy adaptive genetic algorithm (FAGA) is proposed in order to solve this optimization model. In establishing the FAGA, five dynamic fuzzy parameter controllers are devised in which fuzzy expert experience controller (FEEC) is integrated with automatic learning dynamic fuzzy controller (ALDFC) technique. The enhanced algorithm dynamically adjusts the population size, number of generations, tournament candidate, crossover rate, and mutation rate compared with using fixed control parameters. The main idea is to improve the performance and effectiveness of existing GAs by dynamic adjustment and control of the five parameters. Verification and validation of the dynamic fuzzy GA are carried out by developing test-beds and testing using a multiobjective fuzzy mixed production assembly line sequencing optimization problem. The simulation results highlight that the performance and efficacy of the proposed novel optimization algorithm are more efficient than the performance of the standard genetic algorithm in mixed assembly line sequencing model. PMID:24982962

  8. Does Operation Scheduling Make a Difference: Tapping the Potential of Optimized Design for Skipping-Stop Strategy in Reducing Bus Emissions

    Directory of Open Access Journals (Sweden)

    Xumei Chen

    2017-09-01

    Full Text Available The idea of corporate social responsibility has promoted bus operation agencies to rethink how to provide not only efficient but also environmentally friendly services for residents. A study on the potential of using an optimized design of skip-stop services, one of the essential operational strategies in practice, to reduce emissions is conducted in this paper. The underlying scheduling problem is formulated as a nonlinear programming problem with the primary objective of optimizing the total costs for both passengers and operating agencies, as well as with the secondary objective of minimizing bus emissions. A solution method is developed to solve the problem. A real-world case of Route 16 in Beijing is studied, in which the optimal scheduling strategy that maximizes the cost savings and environmental benefits is determined. The costs and emissions of the proposed scheduling strategy are compared with the optimal scheduling with skip-stop services without considering bus emissions. The results show that the proposed scheduling strategy outperforms the other operating strategy with respect to operational costs and bus emissions. A sensitivity study is then conducted to investigate the impact of the fleet size in operations and passenger demand on the effectiveness of the proposed stop-skipping strategy considering bus emissions.

  9. Optimal harvesting of a stochastic delay tri-trophic food-chain model with Lévy jumps

    Science.gov (United States)

    Qiu, Hong; Deng, Wenmin

    2018-02-01

    In this paper, the optimal harvesting of a stochastic delay tri-trophic food-chain model with Lévy jumps is considered. We introduce two kinds of environmental perturbations in this model. One is called white noise which is continuous and is described by a stochastic integral with respect to the standard Brownian motion. And the other one is jumping noise which is modeled by a Lévy process. Under some mild assumptions, the critical values between extinction and persistent in the mean of each species are established. The sufficient and necessary criteria for the existence of optimal harvesting policy are established and the optimal harvesting effort and the maximum of sustainable yield are also obtained. We utilize the ergodic method to discuss the optimal harvesting problem. The results show that white noises and Lévy noises significantly affect the optimal harvesting policy while time delays is harmless for the optimal harvesting strategy in some cases. At last, some numerical examples are introduced to show the validity of our results.

  10. Two-Stage Optimal Scheduling of Electric Vehicle Charging based on Transactive Control

    DEFF Research Database (Denmark)

    Liu, Zhaoxi; Wu, Qiuwei; Ma, Kang

    2018-01-01

    In this paper, a two-stage optimal charging scheme based on transactive control is proposed for the aggregator to manage day-ahead electricity procurement and real-time EV charging management in order to minimize its total operating cost. The day-ahead electricity procurement considers both the day...... predictive control (MPC) based method is proposed for the aggregator to clear the transactive market. The realtime charging decisions of the EVs are determined by the clearing of the proposed transactive market according to the realtime requests and preferences of the EV owners. As such, the aggregators...

  11. Sleep and cognitive performance of African-Americans and European-Americans before and during circadian misalignment produced by an abrupt 9-h delay in the sleep/wake schedule.

    Directory of Open Access Journals (Sweden)

    Gemma M Paech

    Full Text Available We conducted two studies of circadian misalignment in non-Hispanic African and European-Americans. In the first, the sleep/wake (light/dark schedule was advanced 9 h, similar to flying east, and in the second these schedules were delayed 9 h, similar to flying west or sleeping during the day after night work. We confirmed that the free-running circadian period is shorter in African-Americans compared to European-Americans, and found differences in the magnitude and direction of circadian rhythm phase shifts which were related to the circadian period. The sleep and cognitive performance data from the first study (published in this journal documented the impairment in both ancestry groups due to this extreme circadian misalignment. African-Americans slept less and performed slightly worse during advanced/misaligned days than European-Americans. The current analysis is of sleep and cognitive performance from the second study. Participants were 23 African-Americans and 22 European-Americans (aged 18-44 years. Following four baseline days (8 h time in bed, based on habitual sleep, the sleep/wake schedule was delayed by 9 h for three days. Sleep was monitored using actigraphy. During the last two baseline/aligned days and the first two delayed/misaligned days, beginning 2 h after waking, cognitive performance was assessed every 3 h using the Automated Neuropsychological Assessment Metrics (ANAM battery. Mixed model ANOVAs assessed the effects of ancestry (African-American or European-American and condition (baseline/aligned or delayed/misaligned on sleep and performance. There was decreased sleep and impaired cognitive performance in both ancestry groups during the two delayed/misaligned days relative to baseline/aligned days. Sleep and cognitive performance did not differ between African-Americans and European-Americans during either baseline/aligned or delayed/misaligned days. While our previous work showed that an advance in the sleep/wake schedule

  12. Optimized Scheduling Technique of Null Subcarriers for Peak Power Control in 3GPP LTE Downlink

    Science.gov (United States)

    Park, Sang Kyu

    2014-01-01

    Orthogonal frequency division multiple access (OFDMA) is a key multiple access technique for the long term evolution (LTE) downlink. However, high peak-to-average power ratio (PAPR) can cause the degradation of power efficiency. The well-known PAPR reduction technique, dummy sequence insertion (DSI), can be a realistic solution because of its structural simplicity. However, the large usage of subcarriers for the dummy sequences may decrease the transmitted data rate in the DSI scheme. In this paper, a novel DSI scheme is applied to the LTE system. Firstly, we obtain the null subcarriers in single-input single-output (SISO) and multiple-input multiple-output (MIMO) systems, respectively; then, optimized dummy sequences are inserted into the obtained null subcarrier. Simulation results show that Walsh-Hadamard transform (WHT) sequence is the best for the dummy sequence and the ratio of 16 to 20 for the WHT and randomly generated sequences has the maximum PAPR reduction performance. The number of near optimal iteration is derived to prevent exhausted iterations. It is also shown that there is no bit error rate (BER) degradation with the proposed technique in LTE downlink system. PMID:24883376

  13. Optimal Scheduling of an Regional Integrated Energy System with Energy Storage Systems for Service Regulation

    Directory of Open Access Journals (Sweden)

    Hengrui Ma

    2018-01-01

    Full Text Available Ancillary services are critical to maintaining the safe and stable operation of power systems that contain a high penetration level of renewable energy resources. As a high-quality regulation resource, the regional integrated energy system (RIES with energy storage system (ESS can effectively adjust the non-negligible frequency offset caused by the renewable energy integration into the power system, and help solve the problem of power system frequency stability. In this paper, the optimization model aiming at regional integrated energy system as a participant in the regulation market based on pay-for-performance is established. Meanwhile YALMIP + CPLEX is used to simulate and analyze the total operating cost under different dispatch modes. This paper uses the actual operation model of the PJM regulation market to guide the optimal allocation of regulation resource in the regional integrated energy system, and provides a balance between the power trading revenue and regulation market revenue in order to achieve the maximum profit.

  14. Optimized scheduling technique of null subcarriers for peak power control in 3GPP LTE downlink.

    Science.gov (United States)

    Cho, Soobum; Park, Sang Kyu

    2014-01-01

    Orthogonal frequency division multiple access (OFDMA) is a key multiple access technique for the long term evolution (LTE) downlink. However, high peak-to-average power ratio (PAPR) can cause the degradation of power efficiency. The well-known PAPR reduction technique, dummy sequence insertion (DSI), can be a realistic solution because of its structural simplicity. However, the large usage of subcarriers for the dummy sequences may decrease the transmitted data rate in the DSI scheme. In this paper, a novel DSI scheme is applied to the LTE system. Firstly, we obtain the null subcarriers in single-input single-output (SISO) and multiple-input multiple-output (MIMO) systems, respectively; then, optimized dummy sequences are inserted into the obtained null subcarrier. Simulation results show that Walsh-Hadamard transform (WHT) sequence is the best for the dummy sequence and the ratio of 16 to 20 for the WHT and randomly generated sequences has the maximum PAPR reduction performance. The number of near optimal iteration is derived to prevent exhausted iterations. It is also shown that there is no bit error rate (BER) degradation with the proposed technique in LTE downlink system.

  15. Optimizing Instruction Scheduling and Register Allocation for Register-File-Connected Clustered VLIW Architectures

    Directory of Open Access Journals (Sweden)

    Haijing Tang

    2013-01-01

    Full Text Available Clustering has become a common trend in very long instruction words (VLIW architecture to solve the problem of area, energy consumption, and design complexity. Register-file-connected clustered (RFCC VLIW architecture uses the mechanism of global register file to accomplish the inter-cluster data communications, thus eliminating the performance and energy consumption penalty caused by explicit inter-cluster data move operations in traditional bus-connected clustered (BCC VLIW architecture. However, the limit number of access ports to the global register file has become an issue which must be well addressed; otherwise the performance and energy consumption would be harmed. In this paper, we presented compiler optimization techniques for an RFCC VLIW architecture called Lily, which is designed for encryption systems. These techniques aim at optimizing performance and energy consumption for Lily architecture, through appropriate manipulation of the code generation process to maintain a better management of the accesses to the global register file. All the techniques have been implemented and evaluated. The result shows that our techniques can significantly reduce the penalty of performance and energy consumption due to access port limitation of global register file.

  16. Current status of high dose rate brachytherapy in cervical cancer in Korea and optimal treatment schedule

    Energy Technology Data Exchange (ETDEWEB)

    Huh, Seung Jae [College of Medicine, Sungkyunkwan Univ., Seoul (Korea, Republic of)

    1998-12-01

    Brachytherapy is an essential part of radiotherapy for uterine cervical cancer. The low dose rate (LDR) regimen has been the major technique of intracavitary therapy for cervical cancer. However, there has been an expansion in the last 20 years of high dose rate (HDR) machines using Ir-192 sources. Since 1979, HDR brachytherapy has been used for the treatment of uterine cervical cancer in Korea. The number of institutions employing HDR has been increasing, while the number of low dose rate system has been constant. In 1995, there was a total 27 HDR brachytherapy units installed and 1258 cases of patients with cervical cancer were treated with HDR. Most common regimens of HDR brachytherapy are total dose of 30-39 Gy at point A with 10-13 fractions in three fractions per week, 24-32 Gy with 6-8 fractions in two fractions per week, and 30-35 Gy with 6-7 fractions in two fractions per week. The average fractionation regimen of HDR brachytherapy is about 8 fractions of 4. 1 Gy each to point A. In Korea, treatment results for HDR brachytherapy are comparable with the LDR series and appears to be a safe and effective alternative to LDR therapy for the treatment of cervical carcinoma. Studies from the major centers report the five-year survival rate of cervical cancer as, 78-86% for Stage I, 68-85% for stage II, and 38-56% for Stage III. World-wide questionnaire study and Japanese questionnaire survey of multiple institutions showed no survival difference in any stages and dose-rate effect ratio (HDR/LDR) was calculated to be 0.54 to 0.58. However, the optimum treatment doses and fractionation schemes appropriate to generate clinical results comparable to conventional LDR schemes have yet to be standardized. In conclusion, HDR intracavitary radiotherapy is increasingly practiced in Korea and an effective treatment modality for cervical cancer. To determine the optimum radiotherapy dose and fractionation schedule, a nation-wide prospective study is necessary in Korea. In

  17. Optimization Scheduling Model for Wind-thermal Power System Considering the Dynamic penalty factor

    Science.gov (United States)

    PENG, Siyu; LUO, Jianchun; WANG, Yunyu; YANG, Jun; RAN, Hong; PENG, Xiaodong; HUANG, Ming; LIU, Wanyu

    2018-03-01

    In this paper, a new dynamic economic dispatch model for power system is presented.Objective function of the proposed model presents a major novelty in the dynamic economic dispatch including wind farm: introduced the “Dynamic penalty factor”, This factor could be computed by using fuzzy logic considering both the variable nature of active wind power and power demand, and it could change the wind curtailment cost according to the different state of the power system. Case studies were carried out on the IEEE30 system. Results show that the proposed optimization model could mitigate the wind curtailment and the total cost effectively, demonstrate the validity and effectiveness of the proposed model.

  18. Low Emissions and Delay Optimization for an Isolated Signalized Intersection Based on Vehicular Trajectories.

    Directory of Open Access Journals (Sweden)

    Ciyun Lin

    Full Text Available A traditional traffic signal control system is established based on vehicular delay, queue length, saturation and other indicators. However, due to the increasing severity of urban environmental pollution issues and the development of a resource-saving and environmentally friendly social philosophy, the development of low-carbon and energy-efficient urban transport is required. This paper first defines vehicular trajectories and the calculation of vehicular emissions based on VSP. Next, a regression analysis method is used to quantify the relationship between vehicular emissions and delay, and a traffic signal control model is established to reduce emissions and delay using the enumeration method combined with saturation constraints. Finally, one typical intersection of Changchun is selected to verify the model proposed in this paper; its performance efficiency is also compared using simulations in VISSIM. The results of this study show that the proposed model can significantly reduce vehicle delay and traffic emissions simultaneously.

  19. Optimal integrated scheduling of distributed energy resources in power systems by virtual power plant.

    Science.gov (United States)

    Kasaei, Mohammad Javad; Gandomkar, Majid; Nikoukar, Javad

    2017-12-13

    Due to many environmental and economic influences, the application of Renewable Energy Sources (RESs) such as Photovoltaic (PV), Wind Turbine (WT), Fuel Cell (FC), and Micro Turbine (MT) have quickly been increased. The rapid growth of the RESs has provided both advantages and disadvantages for the power systems. In the side of advantages, lower environmental pollution, less power losses and better power quality and in the side of disadvantages, intermittent nature of RESs and higher uncertainties that cause the variable generation and uncertainty in distribution systems can be mentioned. Under this condition, an idea to solve problems due to the variable outputs of these resources is to aggregate them altogether. A collection of Distributed Energy Resources (DERs), energy storage devices and controllable loads which are aggregated and then are managed by an Energy Management System (EMS) and can operate as a single power plant is called Virtual Power Plant (VPP). This paper proposes a meta-heuristic optimization method based on Imperialist Competitive Algorithm (ICA), to minimize the total operating cost by VPP, considering energy loss cost in a 24h time interval. In order to see the effectiveness and satisfying performance of the proposed algorithm a case study including RESs, storage battery and controllable loads is studied as test system. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

  20. A hybrid expert system, clustering and ant colony optimization approach for scheduling and routing problem in courier services

    Directory of Open Access Journals (Sweden)

    Eduyn López-Santana

    2018-10-01

    Full Text Available This paper focuses on the problem of scheduling and routing workers in a courier service to deliver packages for a set of geographically distributed customers and, on a specific date and time window. The crew of workers has a limited capacity and a time window that represents their labor length. The problem deals with a combination of multiples variants of the vehicle routing problem as capacity, multiple periods, time windows, due dates and distance as constraints. Since in the courier services the demands could be of hundreds or thousands of packages to be delivered, the problem is computationally unmanageable. We present a three-phase solution approach. In the first phase, a scheduling model determines the visit date for each customer in the planning horizon by considering the release date, due date to visit and travel times. We use an expert system based on the know-how of the courier service, which uses an inference engine that works as a rule interpreter. In the second phase, a clustering model assigns, for each period, customers to workers according to the travel times, maximum load capacity and customer’s time windows. We use a centroid based and sweep algorithms to solve the resulted problem. Finally, in the third phase, a routing model finds the order in which each worker will visit all customers taking into account their time windows and worker’s available time. To solve the routing problem we use an Ant Colony Optimization metaheuristic. We present some numerical results using a case study, in which the proposed method of this paper finds better results in comparison with the current method used in the case study

  1. Scheduling optimization of a real-world multi product pipeline network; Otimizacao das operacoes de transporte de derivados de petroleo em redes de dutos

    Energy Technology Data Exchange (ETDEWEB)

    Boschetto, Suelen N.; Felizari, Luiz C.; Magatao, Leandro; Stebel, Sergio L.; Neves Junior, Flavio; Lueders, Ricardo; Arruda, Lucia V.R. de [Universidade Tecnologica Federal do Parana (UTFPR), Curitiba, PR (Brazil); Ribas, Paulo Cesar; Bernardo, Luiz F.J. [PETROBRAS S.A., Rio de Janeiro, RJ (Brazil). Centro de Pesquisas (CENPES)

    2008-07-01

    This work develops an optimization structure to aid the operational decision-making of scheduling activities in a real world pipeline network. The proposed approach is based on a decomposition method to address complex problems with high computational burden. The Pre-analysis makes a previous evaluation of a batch sequencing, getting information to be entered into optimization block. The continuous time Mixed Integer Linear Program (MILP) model gets such information and calculates the scheduling. The models are applied to a pipeline network that connects different areas including refineries, terminals, and final clients. Many oil derivatives (e.g. gasoline, liquefied petroleum gas, naphtha) can be sent or received in this network. The computational burden to determine a short-term scheduling within the considered scenario is a relevant issue. Many insights have been derived from the obtained solutions, which are given in a reduced computational time for oil industrial-size scenarios. (author)

  2. A Lifetime Optimization Algorithm Limited by Data Transmission Delay and Hops for Mobile Sink-Based Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Yourong Chen

    2017-01-01

    Full Text Available To improve the lifetime of mobile sink-based wireless sensor networks and considering that data transmission delay and hops are limited in actual system, a lifetime optimization algorithm limited by data transmission delay and hops (LOA_DH for mobile sink-based wireless sensor networks is proposed. In LOA_DH, some constraints are analyzed, and an optimization model is proposed. Maximum capacity path routing algorithm is used to calculate the energy consumption of communication. Improved genetic algorithm which modifies individuals to meet all constraints is used to solve the optimization model. The optimal solution of sink node’s sojourn grid centers and sojourn times which maximizes network lifetime is obtained. Simulation results show that, in three node distribution scenes, LOA_DH can find the movement solution of sink node which covers all sensor nodes. Compared with MCP_RAND, MCP_GMRE, and EASR, the solution improves network lifetime and reduces average amount of node discarded data and average energy consumption of nodes.

  3. Echocardiographic estimation of acute haemodynamic response during optimization of multisite pace-maker using different pacing modalities and atrioventricular delays

    Directory of Open Access Journals (Sweden)

    Šalinger-Martinović Sonja

    2009-01-01

    Full Text Available Background/Aim. Cardiac resynchronization therapy (CRT improves ventricular dyssynchrony and is associated with an improvement in symptoms, quality of life and prognosis in patients with severe heart failure and intraventricular conduction delay. Different pacing modalities produce variable activation patterns and may be a cause of different haemodynamic changes. The aim of our study was to investigate acute haemodynamic changes with different CRT configurations during optimization procedure. Methods. This study included 30 patients with severe left ventricular systolic dysfunction and left bundle branch block with wide QRS (EF 24.33 ± 3.7%, QRS 159 ± 17.3 ms, New York Heart Association III/IV 25/5 with implanted CRT device. The whole group of patients had severe mitral regurgitation in order to measure dP/dt. After implantation and before discharge all the patients underwent optimization procedure guided by Doppler echocardiography. Left and right ventricular pre-ejection intervals (LVPEI and RVPEI, interventricular mechanical delay (IVD and the maximal rate of ventricular pressure rise during early systole (max dP/dt were measured during left and biventricular pacing with three different atrioventricular (AV delays. Results. After CRT device optimization, optimal AV delay and CRT mode were defined. Left ventricular pre-ejection intervals changed from 170.5 ± 24.6 to 145.9 ± 9.5 (p < 0.001, RVPEI from 102.4 ± 15.9 to 119.8 ± 10.9 (p < 0.001, IVD from 68.1 ± 18.3 to 26.5 ± 8.2 (p < 0.001 and dP/dt from 524.2 ± 67 to 678.2 ± 88.5 (p < 0.01. Conclusion. In patients receiving CRT echocardiographic assessment of the acute haemodynamic response to CRT is a useful tool in optimization procedure. The variability of Doppler parameters with different CRT modalities emphasizes the necessity of individualized approach in optimization procedure.

  4. Delay Efficient Backpressure Routing in Wireless Ad Hoc Networks

    Directory of Open Access Journals (Sweden)

    Leandros A. Maglaras

    2014-09-01

    Full Text Available Packet scheduling/routing in wireless ad hoc networks is a fundamental problem for ad hoc networking. Backpressure routing is a solid and throughput optimal policy for such networks, but suffers from increased delays. In this article, we present two holistic approaches to improve upon the delay problems of backpressuretype algorithms. We develop two scheduling algorithms, namely Voting backpressure and Layered backpressure routing, which are throughput optimal. We experimentally compare the proposed algorithms against state-of-the-art delay-aware backpressure algorithms, which provide optimal throughput, for different payloads and network topologies, both for static and mobile networks. The experimental evaluation of the proposed delay reduction algorithms attest their superiority in terms of QoS, robustness, low computational complexity and simplicity.

  5. Real-time integration of optimal generation scheduling with MPC for the energy management of a renewable hydrogen-based microgrid

    International Nuclear Information System (INIS)

    Petrollese, Mario; Valverde, Luis; Cocco, Daniele; Cau, Giorgio; Guerra, José

    2016-01-01

    Highlights: • Energy management strategy for a renewable hydrogen-based microgrid. • Integration of optimal generation scheduling with a model predictive control. • Experimental tests are carried out simulating typical summer and winter days. • Effective improvement in performance and reduction in microgrid operating cost are achieved. - Abstract: This paper presents a novel control strategy for the optimal management of microgrids with high penetration of renewable energy sources and different energy storage systems. The control strategy is based on the integration of optimal generation scheduling with a model predictive control in order to achieve both long and short-term optimal planning. In particular, long-term optimization of the various microgrid components is obtained by the adoption of an optimal generation scheduling, in which a statistical approach is used to take into account weather and load forecasting uncertainties. The real-time management of the microgrid is instead entrusted to a model predictive controller, which has the important feature of using the results obtained by the optimal generation scheduling. The proposed control strategy was tested in a laboratory-scale microgrid present at the University of Seville, which is composed of an electronic power source that emulates a photovoltaic system, a battery bank and a hydrogen production and storage system. Two different experimental tests that simulate a summer and a winter day were carried out over a 24-h period to verify the reliability and performance enhancement of the control system. Results show an effective improvement in performance in terms of reduction of the microgrid operating cost and greater involvement of the hydrogen storage system for the maintenance of a spinning reserve in batteries.

  6. Convergence Study of Minimizing the Nonconvex Total Delay Using the Lane-Based Optimization Method for Signal-Controlled Junctions

    Directory of Open Access Journals (Sweden)

    C. K. Wong

    2012-01-01

    Full Text Available This paper presents a 2D convergence density criterion for minimizing the total junction delay at isolated junctions in the lane-based optimization framework. The lane-based method integrates the design of lane markings and signal settings for traffic movements in a unified framework. The problem of delay minimization is formulated as a Binary Mix Integer Non Linear Program (BMINLP. A cutting plane algorithm can be applied to solve this difficult BMINLP problem by adding hyperplanes sequentially until sufficient numbers of planes are created in the form of solution constraints to replicate the original nonlinear surface in the solution space. A set of constraints is set up to ensure the feasibility and safety of the resultant optimized lane markings and signal settings. The main difficulty to solve this high-dimension nonlinear nonconvex delay minimization problem using cutting plane algorithm is the requirement of substantial computational efforts to reach a good-quality solution while approximating the nonlinear solution space. A new stopping criterion is proposed by monitoring a 2D convergence density to obtain a converged solution. A numerical example is given to demonstrate the effectiveness of the proposed methodology. The cutting-plane algorithm producing an effective signal design will become more computationally attractive with adopting the proposed stopping criterion.

  7. Optimal Scheduling of Energy Storage System for Self-Sustainable Base Station Operation Considering Battery Wear-Out Cost

    Directory of Open Access Journals (Sweden)

    Yohwan Choi

    2016-06-01

    Full Text Available A self-sustainable base station (BS where renewable resources and energy storage system (ESS are interoperably utilized as power sources is a promising approach to save energy and operational cost in communication networks. However, high battery price and low utilization of ESS intended for uninterruptible power supply (UPS necessitates active utilization of ESS. This paper proposes a multi-functional framework of ESS using dynamic programming (DP for realizing a sustainable BS. We develop an optimal charging and discharging scheduling algorithm considering a detailed battery wear-out model to minimize operational cost as well as to prolong battery lifetime. Our approach significantly reduces total cost compared to the conventional method that does not consider battery wear-out. Extensive experiments for several scenarios exhibit that total cost is reduced by up to 70.6% while battery wear-out is also reduced by 53.6%. The virtue of the proposed framework is its wide applicability beyond sustainable BS and thus can be also used for other types of load in principle.

  8. Short-term bulk energy storage system scheduling for load leveling in unit commitment: modeling, optimization, and sensitivity analysis.

    Science.gov (United States)

    Hemmati, Reza; Saboori, Hedayat

    2016-05-01

    Energy storage systems (ESSs) have experienced a very rapid growth in recent years and are expected to be a promising tool in order to improving power system reliability and being economically efficient. The ESSs possess many potential benefits in various areas in the electric power systems. One of the main benefits of an ESS, especially a bulk unit, relies on smoothing the load pattern by decreasing on-peak and increasing off-peak loads, known as load leveling. These devices require new methods and tools in order to model and optimize their effects in the power system studies. In this respect, this paper will model bulk ESSs based on the several technical characteristics, introduce the proposed model in the thermal unit commitment (UC) problem, and analyze it with respect to the various sensitive parameters. The technical limitations of the thermal units and transmission network constraints are also considered in the model. The proposed model is a Mixed Integer Linear Programming (MILP) which can be easily solved by strong commercial solvers (for instance CPLEX) and it is appropriate to be used in the practical large scale networks. The results of implementing the proposed model on a test system reveal that proper load leveling through optimum storage scheduling leads to considerable operation cost reduction with respect to the storage system characteristics.

  9. Short-term bulk energy storage system scheduling for load leveling in unit commitment: modeling, optimization, and sensitivity analysis

    Science.gov (United States)

    Hemmati, Reza; Saboori, Hedayat

    2016-01-01

    Energy storage systems (ESSs) have experienced a very rapid growth in recent years and are expected to be a promising tool in order to improving power system reliability and being economically efficient. The ESSs possess many potential benefits in various areas in the electric power systems. One of the main benefits of an ESS, especially a bulk unit, relies on smoothing the load pattern by decreasing on-peak and increasing off-peak loads, known as load leveling. These devices require new methods and tools in order to model and optimize their effects in the power system studies. In this respect, this paper will model bulk ESSs based on the several technical characteristics, introduce the proposed model in the thermal unit commitment (UC) problem, and analyze it with respect to the various sensitive parameters. The technical limitations of the thermal units and transmission network constraints are also considered in the model. The proposed model is a Mixed Integer Linear Programming (MILP) which can be easily solved by strong commercial solvers (for instance CPLEX) and it is appropriate to be used in the practical large scale networks. The results of implementing the proposed model on a test system reveal that proper load leveling through optimum storage scheduling leads to considerable operation cost reduction with respect to the storage system characteristics. PMID:27222741

  10. Wide-area Power System Damping Control Coordination Based on Particle Swarm Optimization with Time Delay Considered

    Science.gov (United States)

    Zhang, J. Y.; Jiang, Y.

    2017-10-01

    To ensure satisfactory dynamic performance of controllers in time-delayed power systems, a WAMS-based control strategy is investigated in the presence of output feedback delay. An integrated approach based on Pade approximation and particle swarm optimization (PSO) is employed for parameter configuration of PSS. The coordination configuration scheme of power system controllers is achieved by a series of stability constraints at the aim of maximizing the minimum damping ratio of inter-area mode of power system. The validity of this derived PSS is verified on a prototype power system. The findings demonstrate that the proposed approach for control design could damp the inter-area oscillation and enhance the small-signal stability.

  11. Robust output observer-based control of neutral uncertain systems with discrete and distributed time delays: LMI optimization approach

    International Nuclear Information System (INIS)

    Chen, J.-D.

    2007-01-01

    In this paper, the robust control problem of output dynamic observer-based control for a class of uncertain neutral systems with discrete and distributed time delays is considered. Linear matrix inequality (LMI) optimization approach is used to design the new output dynamic observer-based controls. Three classes of observer-based controls are proposed and the maximal perturbed bound is given. Based on the results of this paper, the constraint of matrix equality is not necessary for designing the observer-based controls. Finally, a numerical example is given to illustrate the usefulness of the proposed method

  12. An optimal PID controller via LQR for standard second order plus time delay systems.

    Science.gov (United States)

    Srivastava, Saurabh; Misra, Anuraag; Thakur, S K; Pandit, V S

    2016-01-01

    An improved tuning methodology of PID controller for standard second order plus time delay systems (SOPTD) is developed using the approach of Linear Quadratic Regulator (LQR) and pole placement technique to obtain the desired performance measures. The pole placement method together with LQR is ingeniously used for SOPTD systems where the time delay part is handled in the controller output equation instead of characteristic equation. The effectiveness of the proposed methodology has been demonstrated via simulation of stable open loop oscillatory, over damped, critical damped and unstable open loop systems. Results show improved closed loop time response over the existing LQR based PI/PID tuning methods with less control effort. The effect of non-dominant pole on the stability and robustness of the controller has also been discussed. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

  13. A NOVEL DESIGN OF MULTIPLEXER BASED FULL-ADDER CELL FOR POWER AND PROPAGATION DELAY OPTIMIZATIONS

    Directory of Open Access Journals (Sweden)

    G. RAMANA MURTHY

    2013-12-01

    Full Text Available This paper presents a novel high-speed and high-performance multiplexer based full adder cell for low-power applications. The proposed full adder is composed of two separate modules with identical hardware configurations that generate Sum and Carry signals in a parallel manner. The proposed adder circuit has an advantage in terms of short critical path when compared with various existing previous designs. Comprehensive experiments were performed in various situations to evaluate the performance of the proposed design. Simulations were performed by Microwind 2 VLSI CAD tool for LVS and BSIM 4 for parametric analysis of various feature sizes. The simulation results demonstrate clearly the improvement of the proposed design in terms of lower power dissipation, less propagation delay, less occupying area and low power delay product (PDP compared to other widely used existing full adder circuits.

  14. Delayed coking unit preheat train optimization; Otimizacao do preaquecimento das Unidades de Coque

    Energy Technology Data Exchange (ETDEWEB)

    Marins, Edson R.; Geraldelli, Washington O.; Barros, Francisco C. [PETROBRAS, Rio de Janeiro, RJ (Brazil). Centro de Pesquisas (CENPES)

    2004-07-01

    The oil industry has been investing in research and development of new techniques and process improvements with the objective to increase the residual fraction profitability and to fulfill the market demands. The adequacy of the refining scheme has led to the development of bottom of the barrel processes that has the objective to convert heavy fractions into products of higher aggregate value. In this context, the process of Delayed Coking presents a great importance in the production of distillates in the diesel range as well as the processing of heavy residues, mostly in the markets where the fuel oil consumption is being reduced. With the approach to help PETROBRAS decide which route to follow during new designs of Delayed Coking units, this work presents a comparative study of the preheat train performance among the energy recovery to preheat the feed, in contrast with preheating the feed and generating steam, simultaneously. In this study the Pinch Technology methodology was used as a procedure for heat integration with the objective of getting the maximum energy recovery from the process, finding the best trade-off between operational cost and investment cost. The alternative of steam generation aims to provide an appropriate flexibility in Delayed Coking units design and operation. (author)

  15. A bi-level stochastic scheduling optimization model for a virtual power plant connected to a wind–photovoltaic–energy storage system considering the uncertainty and demand response

    International Nuclear Information System (INIS)

    Ju, Liwei; Tan, Zhongfu; Yuan, Jinyun; Tan, Qingkun; Li, Huanhuan; Dong, Fugui

    2016-01-01

    Highlights: • Our research focuses on Virtual Power Plant (VPP). • Virtual Power Plant consists of WPP, PV, CGT, ESSs and DRPs. • Robust optimization theory is introduced to analyze uncertainties. • A bi-level stochastic scheduling optimization model is proposed for VPP. • Models are built to measure the impacts of ESSs and DERPs on VPP operation. - Abstract: To reduce the uncertain influence of wind power and solar photovoltaic power on virtual power plant (VPP) operation, robust optimization theory (ROT) is introduced to build a stochastic scheduling model for VPP considering the uncertainty, price-based demand response (PBDR) and incentive-based demand response (IBDR). First, the VPP components are described including the wind power plant (WPP), photovoltaic generators (PV), convention gas turbine (CGT), energy storage systems (ESSs) and demand resource providers (DRPs). Then, a scenario generation and reduction frame is proposed for analyzing and simulating output stochastics based on the interval method and the Kantorovich distance. Second, a bi-level robust scheduling model is proposed with a double robust coefficient for WPP and PV. In the upper layer model, the maximum VPP operation income is taken as the optimization objective for building the scheduling model with the day-ahead prediction output of WPP and PV. In the lower layer model, the day-ahead scheduling scheme is revised with the actual output of the WPP and PV under the objectives of the minimum system net load and the minimum system operation cost. Finally, the independent micro-grid in a coastal island in eastern China is used for the simulation analysis. The results illustrate that the model can overcome the influence of uncertainty on VPP operations and reduce the system power shortage cost by connecting the day-ahead scheduling with the real-time scheduling. ROT could provide a flexible decision tool for decision makers, effectively addressing system uncertainties. ESSs could

  16. Application of cultural algorithm to generation scheduling of hydrothermal systems

    International Nuclear Information System (INIS)

    Yuan Xiaohui; Yuan Yanbin

    2006-01-01

    The daily generation scheduling of hydrothermal power systems plays an important role in the operation of electric power systems for economics and security, which is a large scale dynamic non-linear constrained optimization problem. It is difficult to solve using traditional optimization methods. This paper proposes a new cultural algorithm to solve the optimal daily generation scheduling of hydrothermal power systems. The approach takes the water transport delay time between connected reservoirs into consideration and can conveniently deal with the complicated hydraulic coupling simultaneously. An example is used to verify the correctness and effectiveness of the proposed cultural algorithm, comparing with both the Lagrange method and the genetic algorithm method. The simulation results demonstrate that the proposed algorithm has rapid convergence speed and higher solution precision. Thus, an effective method is provided to solve the optimal daily generation scheduling of hydrothermal systems

  17. A Personalized Rolling Optimal Charging Schedule for Plug-In Hybrid Electric Vehicle Based on Statistical Energy Demand Analysis and Heuristic Algorithm

    Directory of Open Access Journals (Sweden)

    Fanrong Kong

    2017-09-01

    Full Text Available To alleviate the emission of greenhouse gas and the dependence on fossil fuel, Plug-in Hybrid Electrical Vehicles (PHEVs have gained an increasing popularity in current decades. Due to the fluctuating electricity prices in the power market, a charging schedule is very influential to driving cost. Although the next-day electricity prices can be obtained in a day-ahead power market, a driving plan is not easily made in advance. Although PHEV owners can input a next-day plan into a charging system, e.g., aggregators, day-ahead, it is a very trivial task to do everyday. Moreover, the driving plan may not be very accurate. To address this problem, in this paper, we analyze energy demands according to a PHEV owner’s historical driving records and build a personalized statistic driving model. Based on the model and the electricity spot prices, a rolling optimization strategy is proposed to help make a charging decision in the current time slot. On one hand, by employing a heuristic algorithm, the schedule is made according to the situations in the following time slots. On the other hand, however, after the current time slot, the schedule will be remade according to the next tens of time slots. Hence, the schedule is made by a dynamic rolling optimization, but it only decides the charging decision in the current time slot. In this way, the fluctuation of electricity prices and driving routine are both involved in the scheduling. Moreover, it is not necessary for PHEV owners to input a day-ahead driving plan. By the optimization simulation, the results demonstrate that the proposed method is feasible to help owners save charging costs and also meet requirements for driving.

  18. Runway Scheduling Using Generalized Dynamic Programming

    Science.gov (United States)

    Montoya, Justin; Wood, Zachary; Rathinam, Sivakumar

    2011-01-01

    A generalized dynamic programming method for finding a set of pareto optimal solutions for a runway scheduling problem is introduced. The algorithm generates a set of runway fight sequences that are optimal for both runway throughput and delay. Realistic time-based operational constraints are considered, including miles-in-trail separation, runway crossings, and wake vortex separation. The authors also model divergent runway takeoff operations to allow for reduced wake vortex separation. A modeled Dallas/Fort Worth International airport and three baseline heuristics are used to illustrate preliminary benefits of using the generalized dynamic programming method. Simulated traffic levels ranged from 10 aircraft to 30 aircraft with each test case spanning 15 minutes. The optimal solution shows a 40-70 percent decrease in the expected delay per aircraft over the baseline schedulers. Computational results suggest that the algorithm is promising for real-time application with an average computation time of 4.5 seconds. For even faster computation times, two heuristics are developed. As compared to the optimal, the heuristics are within 5% of the expected delay per aircraft and 1% of the expected number of runway operations per hour ad can be 100x faster.

  19. Non-fragile robust optimal guaranteed cost control of uncertain 2-D discrete state-delayed systems

    Science.gov (United States)

    Tandon, Akshata; Dhawan, Amit

    2016-10-01

    This paper is concerned with the problem of non-fragile robust optimal guaranteed cost control for a class of uncertain two-dimensional (2-D) discrete state-delayed systems described by the general model with norm-bounded uncertainties. Our attention is focused on the design of non-fragile state feedback controllers such that the resulting closed-loop system is asymptotically stable and the closed-loop cost function value is not more than a specified upper bound for all admissible parameter uncertainties and controller gain variations. A sufficient condition for the existence of such controllers is established under the linear matrix inequality framework. Moreover, a convex optimisation problem is proposed to select a non-fragile robust optimal guaranteed cost controller stabilising the 2-D discrete state-delayed system as well as achieving the least guaranteed cost for the resulting closed-loop system. The proposed method is compared with the previously reported criterion. Finally, illustrative examples are given to show the potential of the proposed technique.

  20. Adaptable System Increasing the Transmission Speed and Reliability in Packet Network by Optimizing Delay

    Directory of Open Access Journals (Sweden)

    Zbynek Kocur

    2014-01-01

    Full Text Available There is a great diversity in the transmission technologies in current data networks. Individual technologies are in most cases incompatible at physical and partially also at the link layer of the reference ISO/OSI model. Network compatibility, as the ability to transmit data, is realizable through the third layer, which is able to guarantee the operation of the different devices across their technological differences. The proposed inverse packet multiplexer addresses increase of the speed and reliability of packet transmission to the third layer, and at the same time it increases the stability of the data communication by the regulation of the delay value during the transmission. This article presents implementation of a communication system and its verification in real conditions. The conclusion compares the strengths and weaknesses of the proposed control system.

  1. Implementation of a New Quasi-Optimal Controller Tuning Algorithm for Time-Delay Systems

    OpenAIRE

    Pekař, Libor; Prokop, Roman

    2011-01-01

    The aim of this chapter is to describe, demonstrate and implement a new quasi-optimal pole placement algorithm for SISO LTI-TDS based on the quasi-continuous pole shifting to the prescribed positions. The desired positions are obtained by overshoot analysis of the step response for a dominant pair of complex conjugate poles. A controller structure is initially obtained by algebraic controller design in RMS. Note that the maximum number of prescribed poles (including their multiplicities) equa...

  2. Improving perfusion quantification in arterial spin labeling for delayed arrival times by using optimized acquisition schemes

    International Nuclear Information System (INIS)

    Kramme, Johanna; Diehl, Volker; Madai, Vince I.; Sobesky, Jan; Guenther, Matthias

    2015-01-01

    The improvement in Arterial Spin Labeling (ASL) perfusion quantification, especially for delayed bolus arrival times (BAT), with an acquisition redistribution scheme mitigating the T1 decay of the label in multi-TI ASL measurements is investigated. A multi inflow time (TI) 3D-GRASE sequence is presented which adapts the distribution of acquisitions accordingly, by keeping the scan time constant. The MR sequence increases the number of averages at long TIs and decreases their number at short TIs and thus compensating the T1 decay of the label. The improvement of perfusion quantification is evaluated in simulations as well as in-vivo in healthy volunteers and patients with prolonged BATs due to age or steno-occlusive disease. The improvement in perfusion quantification depends on BAT. At healthy BATs the differences are small, but become larger for longer BATs typically found in certain diseases. The relative error of perfusion is improved up to 30% at BATs > 1500 ms in comparison to the standard acquisition scheme. This adapted acquisition scheme improves the perfusion measurement in comparison to standard multi-TI ASL implementations. It provides relevant benefit in clinical conditions that cause prolonged BATs and is therefore of high clinical relevance for neuroimaging of steno-occlusive diseases.

  3. Optimal Placement of Actors in WSANs Based on Imposed Delay Constraints

    Directory of Open Access Journals (Sweden)

    Chunxi Yang

    2014-01-01

    Full Text Available Wireless Sensor and Actor Networks (WSANs refer to a group of sensors and actors linked by wireless medium to probe environment and perform specific actions. Such certain actions should always be taken before a deadline when an event of interest is detected. In order to provide such services, the whole monitor area is divided into several virtual areas and nodes in the same area form a cluster. Clustering of the WSANs is often pursued to give that each actor acts as a cluster-head. The number of actors is related to the size and the deployment of WSANs cluster. In this paper, we find a method to determine the accurate number of actors which enables them to receive data and take actions in an imposed time-delay. The k-MinTE and the k-MaxTE clustering algorithm are proposed to form the minimum and maximum size of cluster, respectively. In those clustering algorithms, actors are deployed in such a way that sensors could route data to actors within k hops. Then, clusters are arranged by the regular hexagon. At last, we evaluate the placement of actors and results show that our approach is effective.

  4. Improving perfusion quantification in arterial spin labeling for delayed arrival times by using optimized acquisition schemes

    Energy Technology Data Exchange (ETDEWEB)

    Kramme, Johanna [Fraunhofer MEVIS-Institute for Medical Image Computing, Bremen (Germany); Univ. Bremen (Germany). Faculty of Physics and Electronics; Gregori, Johannes [mediri GmbH, Heidelberg (Germany); Diehl, Volker [Fraunhofer MEVIS-Institute for Medical Image Computing, Bremen (Germany); ZEMODI (Zentrum fuer morderne Diagnostik), Bremen (Germany); Madai, Vince I.; Sobesky, Jan [Charite-Universitaetsmedizin Berlin (Germany). Center for Stroke Research Berlin (CSB); Charite-Universitaetsmedizin Berlin (Germany). Dept. of Neurology; Samson-Himmelstjerna, Frederico C. von [Fraunhofer MEVIS-Institute for Medical Image Computing, Bremen (Germany); Charite-Universitaetsmedizin Berlin (Germany). Center for Stroke Research Berlin (CSB); Charite-Universitaetsmedizin Berlin (Germany). Dept. of Neurology; Lentschig, Markus [ZEMODI (Zentrum fuer morderne Diagnostik), Bremen (Germany); Guenther, Matthias [Fraunhofer MEVIS-Institute for Medical Image Computing, Bremen (Germany); Univ. Bremen (Germany). Faculty of Physics and Electronics; mediri GmbH, Heidelberg (Germany)

    2015-07-01

    The improvement in Arterial Spin Labeling (ASL) perfusion quantification, especially for delayed bolus arrival times (BAT), with an acquisition redistribution scheme mitigating the T1 decay of the label in multi-TI ASL measurements is investigated. A multi inflow time (TI) 3D-GRASE sequence is presented which adapts the distribution of acquisitions accordingly, by keeping the scan time constant. The MR sequence increases the number of averages at long TIs and decreases their number at short TIs and thus compensating the T1 decay of the label. The improvement of perfusion quantification is evaluated in simulations as well as in-vivo in healthy volunteers and patients with prolonged BATs due to age or steno-occlusive disease. The improvement in perfusion quantification depends on BAT. At healthy BATs the differences are small, but become larger for longer BATs typically found in certain diseases. The relative error of perfusion is improved up to 30% at BATs > 1500 ms in comparison to the standard acquisition scheme. This adapted acquisition scheme improves the perfusion measurement in comparison to standard multi-TI ASL implementations. It provides relevant benefit in clinical conditions that cause prolonged BATs and is therefore of high clinical relevance for neuroimaging of steno-occlusive diseases.

  5. Final Report on DOE Project entitled Dynamic Optimized Advanced Scheduling of Bandwidth Demands for Large-Scale Science Applications

    Energy Technology Data Exchange (ETDEWEB)

    Ramamurthy, Byravamurthy [University of Nebraska-Lincoln

    2014-05-05

    In this project, developed scheduling frameworks for dynamic bandwidth demands for large-scale science applications. In particular, we developed scheduling algorithms for dynamic bandwidth demands in this project. Apart from theoretical approaches such as Integer Linear Programming, Tabu Search and Genetic Algorithm heuristics, we have utilized practical data from ESnet OSCARS project (from our DOE lab partners) to conduct realistic simulations of our approaches. We have disseminated our work through conference paper presentations and journal papers and a book chapter. In this project we addressed the problem of scheduling of lightpaths over optical wavelength division multiplexed (WDM) networks. We published several conference papers and journal papers on this topic. We also addressed the problems of joint allocation of computing, storage and networking resources in Grid/Cloud networks and proposed energy-efficient mechanisms for operatin optical WDM networks.

  6. Multi-objective stochastic scheduling optimization model for connecting a virtual power plant to wind-photovoltaic-electric vehicles considering uncertainties and demand response

    International Nuclear Information System (INIS)

    Ju, Liwei; Li, Huanhuan; Zhao, Junwei; Chen, Kangting; Tan, Qingkun; Tan, Zhongfu

    2016-01-01

    Highlights: • Our research focuses on virtual power plant. • Electric vehicle group and demand response are integrated into virtual power plant. • Stochastic chance constraint planning is applied to overcome uncertainties. • A multi-objective stochastic scheduling model is proposed for virtual power plant. • A three-stage hybrid intelligent solution algorithm is proposed for solving the model. - Abstract: A stochastic chance-constrained planning method is applied to build a multi-objective optimization model for virtual power plant scheduling. Firstly, the implementation cost of demand response is calculated using the system income difference. Secondly, a wind power plant, photovoltaic power, an electric vehicle group and a conventional power plant are aggregated into a virtual power plant. A stochastic scheduling model is proposed for the virtual power plant, considering uncertainties under three objective functions. Thirdly, a three-stage hybrid intelligent solution algorithm is proposed, featuring the particle swarm optimization algorithm, the entropy weight method and the fuzzy satisfaction theory. Finally, the Yunnan distributed power demonstration project in China is utilized for example analysis. Simulation results demonstrate that when considering uncertainties, the system will reduce the grid connection of the wind power plant and photovoltaic power to decrease the power shortage punishment cost. The average reduction of the system power shortage punishment cost and the operation revenue of virtual power plant are 61.5% and 1.76%, respectively, while the average increase of the system abandoned energy cost is 40.4%. The output of the virtual power plant exhibits a reverse distribution with the confidence degree of the uncertainty variable. The proposed algorithm rapidly calculates a global optimal set. The electric vehicle group could provide spinning reserve to ensure stability of the output of the virtual power plant. Demand response could

  7. Delayed Speech or Language Development

    Science.gov (United States)

    ... Safe Videos for Educators Search English Español Delayed Speech or Language Development KidsHealth / For Parents / Delayed Speech ... their child is right on schedule. How Are Speech and Language Different? Speech is the verbal expression ...

  8. A Multiobjective Robust Scheduling Optimization Mode for Multienergy Hybrid System Integrated by Wind Power, Solar Photovoltaic Power, and Pumped Storage Power

    Directory of Open Access Journals (Sweden)

    Lihui Zhang

    2017-01-01

    Full Text Available Wind power plant (WPP, photovoltaic generators (PV, cell-gas turbine (CGT, and pumped storage power station (PHSP are integrated into multienergy hybrid system (MEHS. Firstly, this paper presents MEHS structure and constructs a scheduling model with the objective functions of maximum economic benefit and minimum power output fluctuation. Secondly, in order to relieve the uncertainty influence of WPP and PV on system, robust stochastic theory is introduced to describe uncertainty and propose a multiobjective stochastic scheduling optimization mode by transforming constraint conditions with uncertain variables. Finally, a 9.6 MW WPP, a 6.5 MW PV, three CGT units, and an upper reservoir with 10 MW·h equivalent capacity are chosen as simulation system. The results show MEHS system can achieve the best operation result by using the multienergy hybrid generation characteristic. PHSP could shave peak and fill valley of load curve by optimizing pumping storage and inflowing generating behaviors based on the load supply and demand status and the available power of WPP and PV. Robust coefficients can relieve the uncertainty of WPP and PV and provide flexible scheduling decision tools for decision-makers with different risk attitudes by setting different robust coefficients, which could maximize economic benefits and minimize operation risks at the same time.

  9. Efficient Scheduling of Scientific Workflows with Energy Reduction Using Novel Discrete Particle Swarm Optimization and Dynamic Voltage Scaling for Computational Grids.

    Science.gov (United States)

    Christobel, M; Tamil Selvi, S; Benedict, Shajulin

    2015-01-01

    One of the most significant and the topmost parameters in the real world computing environment is energy. Minimizing energy imposes benefits like reduction in power consumption, decrease in cooling rates of the computing processors, provision of a green environment, and so forth. In fact, computation time and energy are directly proportional to each other and the minimization of computation time may yield a cost effective energy consumption. Proficient scheduling of Bag-of-Tasks in the grid environment ravages in minimum computation time. In this paper, a novel discrete particle swarm optimization (DPSO) algorithm based on the particle's best position (pbDPSO) and global best position (gbDPSO) is adopted to find the global optimal solution for higher dimensions. This novel DPSO yields better schedule with minimum computation time compared to Earliest Deadline First (EDF) and First Come First Serve (FCFS) algorithms which comparably reduces energy. Other scheduling parameters, such as job completion ratio and lateness, are also calculated and compared with EDF and FCFS. An energy improvement of up to 28% was obtained when Makespan Conservative Energy Reduction (MCER) and Dynamic Voltage Scaling (DVS) were used in the proposed DPSO algorithm.

  10. Efficient Scheduling of Scientific Workflows with Energy Reduction Using Novel Discrete Particle Swarm Optimization and Dynamic Voltage Scaling for Computational Grids

    Directory of Open Access Journals (Sweden)

    M. Christobel

    2015-01-01

    Full Text Available One of the most significant and the topmost parameters in the real world computing environment is energy. Minimizing energy imposes benefits like reduction in power consumption, decrease in cooling rates of the computing processors, provision of a green environment, and so forth. In fact, computation time and energy are directly proportional to each other and the minimization of computation time may yield a cost effective energy consumption. Proficient scheduling of Bag-of-Tasks in the grid environment ravages in minimum computation time. In this paper, a novel discrete particle swarm optimization (DPSO algorithm based on the particle’s best position (pbDPSO and global best position (gbDPSO is adopted to find the global optimal solution for higher dimensions. This novel DPSO yields better schedule with minimum computation time compared to Earliest Deadline First (EDF and First Come First Serve (FCFS algorithms which comparably reduces energy. Other scheduling parameters, such as job completion ratio and lateness, are also calculated and compared with EDF and FCFS. An energy improvement of up to 28% was obtained when Makespan Conservative Energy Reduction (MCER and Dynamic Voltage Scaling (DVS were used in the proposed DPSO algorithm.

  11. Cardiac index in atrio- and interventricular delay optimized cardiac resynchronization therapy and cardiac contractility modulation

    Directory of Open Access Journals (Sweden)

    Tumampos J.

    2015-09-01

    Full Text Available Cardiac resynchronization therapy (CRT is an established therapy for heart failure patients and improves quality of life in patients with sinus rhythm, reduced left ventricular ejection fraction (LVEF, left bundle branch block and wide QRS duration. Since approximately sixty percent of heart failure patients have a normal QRS duration they do not benefit or respond to the CRT. Cardiac contractility modulation (CCM releases nonexcitatoy impulses during the absolute refractory period in order to enhance the strength of the left ventricular contraction. The aim of the investigation was to evaluate differences in cardiac index between optimized and nonoptimized CRT and CCM devices versus standard values. Impedance cardiography, a noninvasive method was used to measure cardiac index (CI, a useful parameter which describes the blood volume during one minutes heart pumps related to the body surface. CRT patients indicate an increase of 39.74 percent and CCM patients an improvement of 21.89 percent more cardiac index with an optimized device.

  12. Integrated Circuit Conception: A Wire Optimization Technic Reducing Interconnection Delay in Advanced Technology Nodes

    Directory of Open Access Journals (Sweden)

    Mohammed Darmi

    2017-10-01

    Full Text Available As we increasingly use advanced technology nodes to design integrated circuits (ICs, physical designers and electronic design automation (EDA providers are facing multiple challenges, firstly, to honor all physical constraints coming with cutting-edge technologies and, secondly, to achieve expected quality of results (QoR. An advanced technology should be able to bring better performances with minimum cost whatever the complexity. A high effort to develop out-of-the-box optimization techniques is more than needed. In this paper, we will introduce a new routing technique, with the objective to optimize timing, by only acting on routing topology, and without impacting the IC Area. In fact, the self-aligned double patterning (SADP technology offers an important difference on layer resistance between SADP and No-SADP layers; this property will be taken as an advantage to drive the global router to use No-SADP less resistive layers for critical nets. To prove the benefit on real test cases, we will use Mentor Graphics’ physical design EDA tool Nitro-SoC™ and several 7 nm technology node designs. The experiments show that worst negative slack (WNS and total negative slack (TNS improved up to 13% and 56%, respectively, compared to the baseline flow.

  13. When greediness fails: examples from stochastic scheduling

    NARCIS (Netherlands)

    Uetz, Marc Jochen

    2003-01-01

    The purpose of this paper is to present examples for the sometimes surprisingly different behavior of deterministic and stochastic scheduling problems. In particular, it demonstrates some seemingly counterintuitive properties of optimal scheduling policies for stochastic machine scheduling problems.

  14. Small-Signal Modeling, Stability Analysis and Design Optimization of Single-Phase Delay-Based PLLs

    DEFF Research Database (Denmark)

    Golestan, Saeed; Guerrero, Josep M.; Vidal, Ana

    2016-01-01

    have been proposed, the simplest perhaps being the transfer delay based method. In the transfer delay based PLL (TD-PLL), the orthogonal signal is generated by delaying the original singlephase signal by T=4 (one-quarter of a period). The phase shift caused by the transfer delay block, however...

  15. Optimal Scheduling of a Battery-Based Energy Storage System for a Microgrid with High Penetration of Renewable Sources

    DEFF Research Database (Denmark)

    Dulout, Jeremy; Hernández, Adriana Carolina Luna; Anvari-Moghaddam, Amjad

    2017-01-01

    A new scheduling method is proposed to manage efficiently the integration of renewable sources in microgrids (MGs) with energy storage systems (ESSs). The purpose of this work is to take into account the main stress factors influencing the ageing mechanisms of a battery energy storage system (BES...

  16. Comparison of different invasive hemodynamic methods for AV delay optimization in patients with cardiac resynchronization therapy: Implications for clinical trial design and clinical practice☆☆☆

    Science.gov (United States)

    Whinnett, Zachary I.; Francis, Darrel P.; Denis, Arnaud; Willson, Keith; Pascale, Patrizio; van Geldorp, Irene; De Guillebon, Maxime; Ploux, Sylvain; Ellenbogen, Kenneth; Haïssaguerre, Michel; Ritter, Philippe; Bordachar, Pierre

    2013-01-01

    Background Reproducibility and hemodynamic efficacy of optimization of AV delay (AVD) of cardiac resynchronization therapy (CRT) using invasive LV dp/dtmax are unknown. Method and results 25 patients underwent AV delay (AVD) optimisation twice, using continuous left ventricular (LV) dp/dtmax, systolic blood pressure (SBP) and pulse pressure (PP). We compared 4 protocols for comparing dp/dtmax between AV delays:Immediate absolute: mean of 10 s recording of dp/dtmax acquired immediately after programming the tested AVD,Delayed absolute: mean of 10 s recording acquired 30 s after programming AVD,Single relative: relative difference between reference AVD and the tested AVD,Multiple relative: averaged difference, from multiple alternations between reference and tested AVD. We assessed for dp/dtmax, LVSBP and LVPP, test–retest reproducibility of the optimum. Optimization using immediate absolute dp/dtmax had poor reproducibility (SDD of replicate optima = 41 ms; R2 = 0.45) as did delayed absolute (SDD 39 ms; R2 = 0.50). Multiple relative had better reproducibility: SDD 23 ms, R2 = 0.76, and (p AV delay was LVSBP 2% and LVdp/dtmax 5%, while CRT with pre-determined optimal AVD gave 6% and 9% respectively. Conclusions Because of inevitable background fluctuations, optimization by absolute dp/dtmax has poor same-day reproducibility, unsuitable for clinical or research purposes. Reproducibility is improved by comparing to a reference AVD and making multiple consecutive measurements. More than 6 measurements would be required for even more precise optimization — and might be advisable for future study designs. With optimal AVD, instead of nominal, the hemodynamic increment of CRT is approximately doubled. PMID:23481908

  17. Optimal pricing and lot-sizing policies for an economic production quantity model with non-instantaneous deteriorating items, permissible delay in payments, customer returns, and inflation

    DEFF Research Database (Denmark)

    Ghoreishi, Maryam; Mirzazadeh, Abolfazl; Nakhai Kamalabadi, Isa

    2014-01-01

    . The effects of time value of money are studied using the Discounted Cash Flow approach. The main objective is to determine the optimal selling price, the optimal length of the production period, and the optimal length of inventory cycle simultaneously such that the present value of total profit is maximized....... An efficient algorithm is presented to find the optimal solution of the developed model. Finally, a numerical example is extracted to solve the presented inventory model using our proposed algorithm, and the effects of the customer returns, inflation, and delay in payments are also discussed....

  18. Technical Report: Optimizing the Slab Yard Planning and Crane Scheduling Problem using a Two-Stage Approach

    DEFF Research Database (Denmark)

    Hansen, Anders Dohn; Clausen, Jens

    2008-01-01

    . The aim of the planning problem is twofold. A number of compulsory operations are generated, in order to comply with short term planning requirements. These operations are mostly moves of arriving and leaving slabs in the yard. A number of non-compulsory operations with a long term purpose are also...... tests are run on a generic setup with artificially generated data. The test results are very promising. The production delays are reduced significantly in the new solutions compared to the corresponding delays observed in a simulation of manual planning. The work presented in this paper is focused...

  19. Optimization of cord blood unit sterility testing: impact of dilution, analysis delay, and inhibitory substances.

    Science.gov (United States)

    Girard, Mélissa; Laforce-Lavoie, Audrey; de Grandmont, Marie Joëlle; Cayer, Marie-Pierre; Fournier, Diane; Delage, Gilles; Thibault, Louis

    2017-08-01

    Different methods are used by cord blood banks to prepare samples for sterility testing. Suboptimal methods can result in the release of contaminated products. In our organization, samples are prepared by diluting the final product in RPMI-1640 medium. In this work, we have compared our method with different approaches to verify whether optimization should be sought. Cord blood units (n = 6 units per bacterial strain) characterized to contain inhibitory substances or not were inoculated (10 colony-forming units/mL) with Streptococcus agalactiae, Staphylococcus epidermidis, Klebsiella pneumoniae, Escherichia coli, or Bacteroides fragilis. After plasma and red blood cell removal, stem cell concentrates were diluted in RPMI-1640, thioglycollate, or the unit's plasma. These products, as well as final product, plasma, and red blood cell fractions, were held from 0 to 72 hours at 20 to 24°C before inoculation in culture bottles and detection using the BacT/ALERT 3D system. Dilution of cell concentrates in RPMI-1640 allowed bacterial detection in 93.3% of noninhibitory cord blood samples after a 24-hour storage period. Thioglycollate medium better promoted bacterial growth in inhibitory cord blood samples that were held for 72 hours before testing (66.7%) compared with RPMI-1640 (45.0%). Less than 33% of all spiked plasma samples were detected by the BacT/ALERT 3D system. Diluting cord blood samples in culture medium containing bacterial growth promoting substances is a suitable option for sterility testing, whereas the use of plasma should be proscribed, because it might lead to false-negative results. Because inhibitory substances affect bacterial growth, inoculation of culture bottles should be done rapidly after sample preparation. © 2017 AABB.

  20. A multi-objective optimization of the active and reactive resource scheduling at a distribution level in a smart grid context

    DEFF Research Database (Denmark)

    Sousa, Tiago; Morais, Hugo; Vale, Zita

    2015-01-01

    at a distribution level, due to the high number of resources connected in distribution levels. This paper proposes a new multi-objective methodology to deal with the optimal resource scheduling considering the distributed generation, electric vehicles and capacitor banks for the joint active and reactive power...... the best compromise solution. The proposed methodology has been tested in the 33-bus distribution network. The case study shows the results of three different scenarios for the economic, technical, and multi-objective perspectives, and the results demonstrated the importance of incorporating the reactive...

  1. Optimal scheduling for vehicle-to-grid operation with stochastic connection of plug-in electric vehicles to smart grid

    International Nuclear Information System (INIS)

    Jian, Linni; Zheng, Yanchong; Xiao, Xinping; Chan, C.C.

    2015-01-01

    Highlights: • A novel event-triggered scheduling scheme for vehicle-to-grid (V2G) operation is proposed. • New scheme can handle the uncertainty arising from stochastic connection of electric vehicles. • New scheme aims at minimizing the overall load variance of power grid by V2G operation. • Method to evaluate the performance of proposed scheme is elaborated and demonstrated. - Abstract: Vehicle-to-grid (V2G) operation of plug-in electric vehicles (PEVs) is attracting increasing attention since it can assist to improve the efficiency and reliability of power grid, as well as reduce the operating cost and greenhouse gas emission of electric vehicles. Within the scheme of V2G operation, PEVs are expected to serve as a novel distributed energy storage system (ESS) to help achieve the balance between supply and demand of power grid. One of the key difficulties concerning its practical implementation lies in that the availability of PEVs as ESS for grid remains highly uncertain due to their mobility as transportation tools. To address this issue, a novel event-triggered scheduling scheme for V2G operation based on the scenario of stochastic PEV connection to smart grid is proposed in this paper. Firstly, the mathematical model is formulated. Secondly, the preparation of input data for systematic evaluation is introduced and the case study is conducted. Finally, statistic analysis results demonstrate that our proposed V2G scheduling scheme can dramatically smooth out the fluctuation in power load profiles

  2. Determining optimal maintenance schedules for adjuvant intravesical bacillus Calmette-Guerin immunotherapy in non-muscle-invasive bladder cancer: a systematic review and network meta-analysis.

    Science.gov (United States)

    Huang, Zixiong; Liu, Huixin; Wang, Yizeng; Zhang, Chunfang; Xu, Tao

    2017-08-01

    To figure out optimal bacillus Calmette-Guerin (BCG) maintenance schedules for non-muscle-invasive bladder cancer (NMIBC) patients by comparing different schedules in a systematic review using conventional and network meta-analysis. Literature was searched in the databases of Medline, Embase, Cochrane library, Clinicaltrials.gov, Wanfang, CNKI and SinoMed in April 2016 and 9 randomized clinical trials comparing intravesical BCG maintenance therapy with BCG induction-only therapy or comparing different BCG maintenance schedules (induction-only, 1 year, 1.5 year, 2 year, 3 year maintenance) in NMIBC patients were included. Conventional and network meta-analyses within a Bayesian framework were performed to calculate odds ratios of tumor recurrence, progression and side effects (cystitis, hematuria, general malaise and fever). The surface under the cumulative ranking curve (SUCRA) mean ranking was used to obtain schedule hierarchy. Data from 1951 patients showed that longer-term maintenance BCG therapy does not significantly decrease tumor recurrence and progression rate of NMIBC compared to shorter-term maintenance BCG therapy. However, longer-maintenance therapy does not increase side effect incidence compared to induction-only therapy. According to SUCRA results, induction-only therapy has the highest probability of recurrence and progression but least probability of side effects. Longer BCG maintenance therapy (such as 3 years) is not superior to shorter maintenance therapy (such as 1 year). But maintenance therapy overall is better than induction-only BCG therapy while not increasing side effects. Though further evidence and clinical practice with balanced confounding factors (risk stratification and BCG strain) are wished for, the current study suggests the common use of 1 year intravesical BCG instillation for NMIBC patients.

  3. Providing delay guarantees in Bluetooth

    NARCIS (Netherlands)

    Ait Yaiz, R.; Heijenk, Geert; Titsworth, F.

    2003-01-01

    Bluetooth polling, also referred to as Bluetooth MAC scheduling or intra-piconet scheduling, is the mechanism that schedules the traffic between the participants in a Bluetooth network. Hence, this mechanism is highly determining with respect to the delay packets experience in a Bluetooth network.

  4. Optimization Technique With Sensitivity Analysis On Menu Scheduling For Boarding School Student Aged 13-18 Using “Sufahani-Ismail Algorithm”

    Science.gov (United States)

    Sudin, Azila M.; Sufahani, Suliadi

    2018-04-01

    Boarding school student aged 13-18 need to eat nutritious meals which contains proper calories, vitality and nutrients for appropriate development with a specific end goal to repair and upkeep the body tissues. Furthermore, it averts undesired diseases and contamination. Serving healthier food is a noteworthy stride towards accomplishing that goal. However, arranging a nutritious and balance menu manually is convoluted, wasteful and tedious. Therefore, the aim of this study is to develop a mathematical model with an optimization technique for menu scheduling that fulfill the whole supplement prerequisite for boarding school student, reduce processing time, minimize the budget and furthermore serve assortment type of food each day. It additionally gives the flexibility for the cook to choose any food to be considered in the beginning of the process and change any favored menu even after the ideal arrangement and optimal solution has been obtained. This is called sensitivity analysis. A recalculation procedure will be performed in light of the ideal arrangement and seven days menu was produced. The data was gathered from the Malaysian Ministry of Education and schools authorities. Menu arranging is a known optimization problem. Therefore Binary Programming alongside optimization technique and “Sufahani-Ismail Algorithm” were utilized to take care of this issue. In future, this model can be implemented to other menu problem, for example, for sports, endless disease patients, militaries, colleges, healing facilities and nursing homes.

  5. Revisiting the NEH algorithm- the power of job insertion technique for optimizing the makespan in permutation flow shop scheduling

    Directory of Open Access Journals (Sweden)

    A. Baskar

    2016-04-01

    Full Text Available Permutation flow shop scheduling problems have been an interesting area of research for over six decades. Out of the several parameters, minimization of makespan has been studied much over the years. The problems are widely regarded as NP-Complete if the number of machines is more than three. As the computation time grows exponentially with respect to the problem size, heuristics and meta-heuristics have been proposed by many authors that give reasonably accurate and acceptable results. The NEH algorithm proposed in 1983 is still considered as one of the best simple, constructive heuristics for the minimization of makespan. This paper analyses the powerful job insertion technique used by NEH algorithm and proposes seven new variants, the complexity level remains same. 120 numbers of problem instances proposed by Taillard have been used for the purpose of validating the algorithms. Out of the seven, three produce better results than the original NEH algorithm.

  6. Test scheduling optimization for 3D network-on-chip based on cloud evolutionary algorithm of Pareto multi-objective

    Science.gov (United States)

    Xu, Chuanpei; Niu, Junhao; Ling, Jing; Wang, Suyan

    2018-03-01

    In this paper, we present a parallel test strategy for bandwidth division multiplexing under the test access mechanism bandwidth constraint. The Pareto solution set is combined with a cloud evolutionary algorithm to optimize the test time and power consumption of a three-dimensional network-on-chip (3D NoC). In the proposed method, all individuals in the population are sorted in non-dominated order and allocated to the corresponding level. Individuals with extreme and similar characteristics are then removed. To increase the diversity of the population and prevent the algorithm from becoming stuck around local optima, a competition strategy is designed for the individuals. Finally, we adopt an elite reservation strategy and update the individuals according to the cloud model. Experimental results show that the proposed algorithm converges to the optimal Pareto solution set rapidly and accurately. This not only obtains the shortest test time, but also optimizes the power consumption of the 3D NoC.

  7. Multi-objective demand side scheduling considering the operational safety of appliances

    International Nuclear Information System (INIS)

    Du, Y.F.; Jiang, L.; Li, Y.Z.; Counsell, J.; Smith, J.S.

    2016-01-01

    Highlights: • Operational safety of appliances is introduced in multi-objective scheduling. • Relationships between operational safety and other objectives are investigated. • Adopted Pareto approach is compared with Weigh and Constraint approaches. • Decision making of Pareto approach is proposed for final appliances’ scheduling. - Abstract: The safe operation of appliances is of great concern to users. The safety risk increases when the appliances are in operation during periods when users are not at home or when they are asleep. In this paper, multi-objective demand side scheduling is investigated with consideration to the appliances’ operational safety together with the electricity cost and the operational delay. The formulation of appliances’ operational safety is proposed based on users’ at-home status and awake status. Then the relationships between the operational safety and the other two objectives are investigated through the approach of finding the Pareto-optimal front. Moreover, this approach is compared with the Weigh and Constraint approaches. As the Pareto-optimal front consists of a set of optimal solutions, this paper proposes a method to make the final scheduling decision based on the relationships among the multiple objectives. Simulation results demonstrate that the operational safety is improved with the sacrifice of the electricity cost and the operational delay, and that the approach of finding the Pareto-optimal front is effective in presenting comprehensive optimal solutions of the multi-objective demand side scheduling.

  8. Gradient decent based multi-objective cultural differential evolution for short-term hydrothermal optimal scheduling of economic emission with integrating wind power and photovoltaic power

    International Nuclear Information System (INIS)

    Zhang, Huifeng; Yue, Dong; Xie, Xiangpeng; Dou, Chunxia; Sun, Feng

    2017-01-01

    With the integration of wind power and photovoltaic power, optimal operation of hydrothermal power system becomes great challenge due to its non-convex, stochastic and complex-coupled constrained characteristics. This paper extends short-term hydrothermal system optimal model into short-term hydrothermal optimal scheduling of economic emission while considering integrated intermittent energy resources (SHOSEE-IIER). For properly solving SHOSEE-IIER problem, a gradient decent based multi-objective cultural differential evolution (GD-MOCDE) is proposed to improve the optimal efficiency of SHOSEE-IIER combined with three designed knowledge structures, which mainly enhances search ability of differential evolution in the shortest way. With considering those complex-coupled and stochastic constraints, a heuristic constraint-handling measurement is utilized to tackle with them both in coarse and fine tuning way, and probability constraint-handling procedures are taken to properly handle those stochastic constraints combined with their probability density functions. Ultimately, those approaches are implemented on five test systems, which testify the optimization efficiency of proposed GD-MOCDE and constraint-handling efficiency for system load balance, water balance and stochastic constraint-handling measurements, those obtained results reveal that the proposed GD-MOCDE can properly solve the SHOSEE-IIER problem combined with those constraint-handling approaches. - Highlights: • Gradient decent method is proposed to improve mutation operator. • Hydrothermal system is extended to hybrid energy system. • The uncertainty constraint is converted into deterministic constraint. • The results show the viability and efficiency of proposed algorithm.

  9. A Personalized Rolling Optimal Charging Schedule for Plug-In Hybrid Electric Vehicle Based on Statistical Energy Demand Analysis and Heuristic Algorithm

    DEFF Research Database (Denmark)

    Kong, Fanrong; Jiang, Jianhui; Ding, Zhigang

    2017-01-01

    To alleviate the emission of greenhouse gas and the dependence on fossil fuel, Plug-in Hybrid Electrical Vehicles (PHEVs) have gained an increasing popularity in current decades. Due to the fluctuating electricity prices in the power market, a charging schedule is very influential to driving cost....... Although the next-day electricity prices can be obtained in a day-ahead power market, a driving plan is not easily made in advance. Although PHEV owners can input a next-day plan into a charging system, e.g., aggregators, day-ahead, it is a very trivial task to do everyday. Moreover, the driving plan may...... not be very accurate. To address this problem, in this paper, we analyze energy demands according to a PHEV owner's historical driving records and build a personalized statistic driving model. Based on the model and the electricity spot prices, a rolling optimization strategy is proposed to help make...

  10. Statistical modelling for precision agriculture: A case study in optimal environmental schedules for Agaricus Bisporus production via variable domain functional regression.

    Science.gov (United States)

    Panayi, Efstathios; Peters, Gareth W; Kyriakides, George

    2017-01-01

    Quantifying the effects of environmental factors over the duration of the growing process on Agaricus Bisporus (button mushroom) yields has been difficult, as common functional data analysis approaches require fixed length functional data. The data available from commercial growers, however, is of variable duration, due to commercial considerations. We employ a recently proposed regression technique termed Variable-Domain Functional Regression in order to be able to accommodate these irregular-length datasets. In this way, we are able to quantify the contribution of covariates such as temperature, humidity and water spraying volumes across the growing process, and for different lengths of growing processes. Our results indicate that optimal oxygen and temperature levels vary across the growing cycle and we propose environmental schedules for these covariates to optimise overall yields.

  11. Analysis Of The Performance Of An Optimization Model For Time-Shiftable Electrical Load Scheduling Under Uncertainty

    Science.gov (United States)

    2016-12-01

    with a capital planning optimization model by using historical solar data and simulated forecasts for wind data to formulate a mixed integer linear...Works – SolarEagle • Google Titan Aerospace – Solara • Facebook Ascenta – High-speed internet via drones • AeroVironment/NASA – Gossamer Penguin...state-of-the-art system enabling the harvesting and use of solar and wind power, energy storage, energy distribution and monitoring, and mobility; it

  12. Impact of Scheduling Flexibility on Demand Profile Flatness and User Inconvenience in Residential Smart Grid System

    Directory of Open Access Journals (Sweden)

    Naveed Ul Hassan

    2013-12-01

    Full Text Available The objective of this paper is to study the impact of scheduling flexibility on both demand profile flatness and user inconvenience in residential smart grid systems. Temporal variations in energy consumption by end users result in peaks and troughs in the aggregated demand profile. In a residential smart grid, some of these peaks and troughs can be eliminated through appropriate load balancing algorithms. However, load balancing requires user participation by allowing the grid to re-schedule some of their loads. In general, more scheduling flexibility can result in more demand profile flatness, however the resulting inconvenience to users would also increase. In this paper, our objective is to help the grid determine an appropriate amount of scheduling flexibility that it should demand from users, based on which, proper incentives can be designed. We consider three different types of scheduling flexibility (delay, advance scheduling and flexible re-scheduling in flexible loads and develop both optimal and sub-optimal scheduling algorithms. We discuss their implementation in centralized and distributed manners. We also identify the existence of a saturation point. Beyond this saturation point, any increase in scheduling flexibility does not significantly affect the flatness of the demand profile while user inconvenience continues to increase. Moreover, full participation of all the households is not required since increasing user participation only marginally increases demand profile flatness.

  13. ATLAS construction schedule

    CERN Multimedia

    Kotamaki, M

    The goal during the last few months has been to freeze and baseline as much as possible the schedules of various ATLAS systems and activities. The main motivations for the re-baselining of the schedules have been the new LHC schedule aiming at first collisions in early 2006 and the encountered delays in civil engineering as well as in the production of some of the detectors. The process was started by first preparing a new installation schedule that takes into account all the new external constraints and the new ATLAS staging scenario. The installation schedule version 3 was approved in the March EB and it provides the Ready For Installation (RFI) milestones for each system, i.e. the date when the system should be available for the start of the installation. TCn is now interacting with the systems aiming at a more realistic and resource loaded version 4 before the end of the year. Using the new RFI milestones as driving dates a new summary schedule has been prepared, or is under preparation, for each system....

  14. Exploring a QoS Driven Scheduling Approach for Peer-to-Peer Live Streaming Systems with Network Coding

    Science.gov (United States)

    Cui, Laizhong; Lu, Nan; Chen, Fu

    2014-01-01

    Most large-scale peer-to-peer (P2P) live streaming systems use mesh to organize peers and leverage pull scheduling to transmit packets for providing robustness in dynamic environment. The pull scheduling brings large packet delay. Network coding makes the push scheduling feasible in mesh P2P live streaming and improves the efficiency. However, it may also introduce some extra delays and coding computational overhead. To improve the packet delay, streaming quality, and coding overhead, in this paper are as follows. we propose a QoS driven push scheduling approach. The main contributions of this paper are: (i) We introduce a new network coding method to increase the content diversity and reduce the complexity of scheduling; (ii) we formulate the push scheduling as an optimization problem and transform it to a min-cost flow problem for solving it in polynomial time; (iii) we propose a push scheduling algorithm to reduce the coding overhead and do extensive experiments to validate the effectiveness of our approach. Compared with previous approaches, the simulation results demonstrate that packet delay, continuity index, and coding ratio of our system can be significantly improved, especially in dynamic environments. PMID:25114968

  15. Gadobenate dimeglumine-enhanced MR of VX2 carcinoma in rabbit liver: usefulness of the delayed phase imaging and optimal pulse sequence

    Energy Technology Data Exchange (ETDEWEB)

    Cho, Seung Il; Lee, Jeong Min; Kim, Young Kon; Kim, Chong Soo [College of Medicine, Chonbuk National Univ., Chonju (Korea, Republic of)

    2002-07-01

    To assess the diagnostic value of delayed imaging using gadobenate dimeglumine (MultiHance) and to determine the optimal pulse sequence for the detection of VX2 carcinoma lesions in the rabbit. Twelve VX2 carcinomas implanted in the livers of eleven New Zealand rabbits were studied. All patients underwent an MR protocal consisting of precontrast T2-and T1-weighted sequences, followed by repetition of the T1-weighted sequence at 0 to 30 (arterial phase). 31-60 (portal phase), and 40 minutes (delayed phase) after the intravenous administration of 0.1 mmol/kg of gadobenate dimeglumine. The signal-to-noise ratio (SNR) of the liver and VX2 tumor, and the lesion-to-liver contrast-to-noise ratio (CNR) of precontrast and postcontrast MR images were quantitatively analyzed, and two experienced radiologists evaluated image quality in terms of lesion conspicuity, artifact, mass delineation, and vascular anatomy. Liver SNR was significantly higher at delayed imaging than at precontrast, arterial, and portal imaging (p<0.05), while lesion SNR was significantly higher at delayed imaging than at precontrast imaging (p<0.05). Lesion CNR was higher at delayed imaging than at precontrast and portal phase imaging (p<0.05), but there was no difference between arterial and delayed imaging. The latter provided better mass delineation than precontrast, arterial and portal phase imaging (p<0.05). While in terms of lesion conspicuity and vascular anatomy, the delayed phase was better than the arterial phase (p<0.05) but similar to the precontrast and portal phase. During the delayed phase, the gradient-echo sequence showed better results than the spin-echo in terms of liver SNR, and lesion SNR and CNR (p<0.05). Because it provides better lesion conspicuity and mass delineation by improving liver SNR and lesion-to-liver CNR, the addition of the delayed phase to a dynamic MRI sequence after gadobenate dimeglumine adminstration facilitates lesion detection. For delayed-phase imaging, the

  16. Gadobenate dimeglumine-enhanced MR of VX2 carcinoma in rabbit liver: usefulness of the delayed phase imaging and optimal pulse sequence

    International Nuclear Information System (INIS)

    Cho, Seung Il; Lee, Jeong Min; Kim, Young Kon; Kim, Chong Soo

    2002-01-01

    To assess the diagnostic value of delayed imaging using gadobenate dimeglumine (MultiHance) and to determine the optimal pulse sequence for the detection of VX2 carcinoma lesions in the rabbit. Twelve VX2 carcinomas implanted in the livers of eleven New Zealand rabbits were studied. All patients underwent an MR protocal consisting of precontrast T2-and T1-weighted sequences, followed by repetition of the T1-weighted sequence at 0 to 30 (arterial phase). 31-60 (portal phase), and 40 minutes (delayed phase) after the intravenous administration of 0.1 mmol/kg of gadobenate dimeglumine. The signal-to-noise ratio (SNR) of the liver and VX2 tumor, and the lesion-to-liver contrast-to-noise ratio (CNR) of precontrast and postcontrast MR images were quantitatively analyzed, and two experienced radiologists evaluated image quality in terms of lesion conspicuity, artifact, mass delineation, and vascular anatomy. Liver SNR was significantly higher at delayed imaging than at precontrast, arterial, and portal imaging (p<0.05), while lesion SNR was significantly higher at delayed imaging than at precontrast imaging (p<0.05). Lesion CNR was higher at delayed imaging than at precontrast and portal phase imaging (p<0.05), but there was no difference between arterial and delayed imaging. The latter provided better mass delineation than precontrast, arterial and portal phase imaging (p<0.05). While in terms of lesion conspicuity and vascular anatomy, the delayed phase was better than the arterial phase (p<0.05) but similar to the precontrast and portal phase. During the delayed phase, the gradient-echo sequence showed better results than the spin-echo in terms of liver SNR, and lesion SNR and CNR (p<0.05). Because it provides better lesion conspicuity and mass delineation by improving liver SNR and lesion-to-liver CNR, the addition of the delayed phase to a dynamic MRI sequence after gadobenate dimeglumine adminstration facilitates lesion detection. For delayed-phase imaging, the

  17. How to reliably deliver narrow individual-patient error bars for optimization of pacemaker AV or VV delay using a "pick-the-highest" strategy with haemodynamic measurements.

    Science.gov (United States)

    Francis, Darrel P

    2013-03-10

    Intuitive and easily-described, "pick-the-highest" is often recommended for quantitative optimization of AV and especially VV delay settings of biventricular pacemakers (BVP; cardiac resynchronization therapy, CRT). But reliable selection of the optimum setting is challenged by beat-to-beat physiological variation, which "pick-the-highest" combats by averaging multiple heartbeats. Optimization is not optimization unless the optimum is identified confidently. This document shows how to calculate how many heartbeats must be averaged to optimize reliably by pick-the-highest. Any reader, by conducting a few measurements, can calculate for locally-available methods (i) biological scatter between replicate measurements, and (ii) curvature of the biological response. With these, for any clinically-desired precision of optimization, the necessary number of heartbeats can be calculated. To achieve 95% confidence of getting within ±∆x of the true optimum, the number of heartbeats needed is 2(scatter/curvature)(2)/∆x(4) per setting. Applying published scatter/curvature values (which readers should re-evaluate locally) indicates that optimizing AV, even coarsely with a 40ms-wide band of precision, requires many thousand beats. For VV delay, the number approaches a million. Moreover, identifying the optimum twice as precisely requires 30-fold more beats. "Pick the highest" is quick to say but slow to do. We must not expect staff to do the impossible; nor criticise them for not doing so. Nor should we assume recommendations and published protocols are well-designed. Reliable AV or VV optimization, using "pick-the-highest" on commonly-recommended manual measurements, is unrealistic. Improving time-efficiency of the optimization process to become clinically realistic may need a curve-fitting strategy instead, with all acquired data marshalled conjointly. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

  18. A novel approach using flexible scheduling and aggregation to optimize demand response in the developing interactive grid market architecture

    International Nuclear Information System (INIS)

    Reihani, Ehsan; Motalleb, Mahdi; Thornton, Matsu; Ghorbani, Reza

    2016-01-01

    Highlights: • Designing a DR market to increase renewable resources and decrease air pollution. • Explaining two economic models for DR market for selling available DR quantities. • Optimal allocating DR quantity to houses under each DR aggregator control. • Proposing a discomfort cost function for residential DR resources. • Performing a sensitivity analysis on discomfort cost function coefficients. - Abstract: With the increasing presence of intermittent renewable energy generation sources, variable control over loads and energy storage devices on the grid become even more important to maintain this balance. Increasing renewable energy penetration depends on both technical and economic factors. Distribution system consumers can contribute to grid stability by controlling residential electrical device power consumed by water heaters and battery storage systems. Coupled with dynamic supply pricing strategies, a comprehensive system for demand response (DR) exist. Proper DR management will allow greater integration of renewable energy sources partially replacing energy demand currently met by the combustion of fossil-fuels. An enticing economic framework providing increased value to consumers compensates them for reduced control of devices placed under a DR aggregator. Much work has already been done to develop more effective ways to implement DR control systems. Utilizing an integrated approach that combines consumer requirements into aggregate pools, and provides a dynamic response to market and grid conditions, we have developed a mathematical model that can quantify control parameters for optimum demand response and decide which resources to switch and when. In this model, optimization is achieved as a function of cost savings vs. customer comfort using mathematical market analysis. Two market modeling approaches—the Cournot and SFE—are presented and compared. A quadratic function is used for presenting the cost function of each DRA (Demand

  19. Multi-objective optimization of short-term hydrothermal scheduling using non-dominated sorting gravitational search algorithm with chaotic mutation

    International Nuclear Information System (INIS)

    Tian, Hao; Yuan, Xiaohui; Ji, Bin; Chen, Zhihuan

    2014-01-01

    Highlights: • An improved non-dominated sorting gravitational search algorithm (NSGSA-CM) is proposed. • NSGSA-CM is used to solve the problem of short-term multi-objective hydrothermal scheduling. • We enhance the search capability of NSGSA-CM by chaotic mutation. • New strategies are devised to handle various constraints in NSGSA-CM. • We obtain better compromise solutions with less fuel cost and emissions. - Abstract: This paper proposes a non-dominated sorting gravitational search algorithm with chaotic mutation (NSGSA-CM) to solve short-term economic/environmental hydrothermal scheduling (SEEHTS) problem. The SEEHTS problem is formulated as a multi-objective optimization problem with many equality and inequality constraints. By introducing the concept of non-dominated sorting and crowding distance, NSGSA-CM can optimize two objectives of fuel cost and pollutant emission simultaneously and obtain a set of Pareto optimal solutions in one trial. In order to improve the performance of NSGSA-CM, the paper introduces particle memory character and population social information in velocity update process. And a chaotic mutation is adopted to prevent the premature convergence. Furthermore, NSGSA-CM utilizes an elitism strategy which selects better solutions in parent and offspring populations based on their non-domination rank and crowding distance to update new generations. When dealing with the constraints of the SEEHTS, new strategies without penalty factors are proposed. In order to handle the water dynamic balance and system load balance constraints, this paper uses a combined strategy which adjusts the violation averagely to each decision variable at first and adjusts the rest violation randomly later. Meanwhile, a new symmetrical adjustment strategy by modifying the discharges at current and later interval without breaking water dynamic balance is adopted to handle reservoir storage constraints. To test the performance of the proposed NSGSA

  20. Comparison between IEGM-based approach and echocardiography in AV/PV and VV delay optimization in CRT-D recipients (Quicksept study).

    Science.gov (United States)

    Giammaria, Massimo; Quirino, Gianluca; Cecchi, Enrico; Senatore, Gaetano; Pistelli, Paolo; Bocchiardo, Mario; Mureddu, Roberto; Diotallevi, Paolo; Occhetta, Eraldo; Magnani, Andrea; Bensoni, Mauro; Checchinato, Catia; Conti, Valentina; Badolati, Sandra; Mazza, Antonio

    2016-01-01

    AtrioVentricular (AV) and InterVentricular (VV) delay optimization can improve ventricular function in Cardiac Resynchronization Therapy (CRT) and is usually performed by means of echocardiography. St Jude Medical has developed an automated algorhythm which calculates the optimal AV and VV delays (QuickOpt™) based on Intracardiac ElectroGrams, (IEGM), within 2 min. So far, the efficacy of the algorhythm has been tested acutely with standard lead position at right ventricular (RV) apex. Aim of this project is to evaluate the algorhythm performance in the mid- and long-term with RV lead located in mid-septum. AV and VV delays optimization data were collected in 13 centers using both echocardiographic and QuickOpt™ guidance in CRTD implanted patients provided with this algorhythm. Measurements of the aortic Velocity Time Integral (aVTI) were performed with both methods in a random order at pre-discharge, 6-month and 12-month follow-up. Fifty-three patients were studied (46 males; age 68 ± 10y; EF 28 ± 7%). Maximum aVTI obtained by echocardiography at different AV delays, were compared with aVTI acquired at AV delays suggested by QuickOpt. The AV Pearson correlations were 0.96 at pre-discharge, 0.95 and 0,98 at 6- and 12- month follow-up respectively. After programming optimal AV, the same approach was used to compare echocardiographic aVTI with aVTI corresponding to the VV values provided by QuickOpt. The VV Pearson Correlation were 0,92 at pre-discharge, 0,88 and 0.90 at 6-month and 12- month follow-up respectively. IEGM-based optimization provides comparable results with echocardiographic method (maximum aVTI) used as reference with mid-septum RV lead location. Copyright © 2016 Indian Heart Rhythm Society. Production and hosting by Elsevier B.V. All rights reserved.

  1. LHC opening delayed, operating schedule extended

    CERN Multimedia

    2009-01-01

    "The Large Hadron Collider (LHC) will reportedly reopen in October rather than this summer [...]. The $ 6.5 billion particle accelerator has 1'232 superconducting dipole magnets out of a total of more than 1'700 large magnets" (0.5 page)

  2. The Integration of Group Technology and Simulation Optimization to Solve the Flow Shop with Highly Variable Cycle Time Process: A Surgery Scheduling Case Study

    Directory of Open Access Journals (Sweden)

    T. K. Wang

    2014-01-01

    Full Text Available Surgery scheduling must balance capacity utilization and demand so that the arrival rate does not exceed the effective production rate. However, authorized overtime increases because of random patient arrivals and cycle times. This paper proposes an algorithm that allows the estimation of the mean effective process time and the coefficient of variation. The algorithm quantifies patient flow variability. When the parameters are identified, takt time approach gives a solution that minimizes the variability in production rates and workload, as mentioned in the literature. However, this approach has limitations for the problem of a flow shop with an unbalanced, highly variable cycle time process. The main contribution of the paper is to develop a method called takt time, which is based on group technology. A simulation model is combined with the case study, and the capacity buffers are optimized against the remaining variability for each group. The proposed methodology results in a decrease in the waiting time for each operating room from 46 minutes to 5 minutes and a decrease in overtime from 139 minutes to 75 minutes, which represents an improvement of 89% and 46%, respectively.

  3. Construction schedules slack time minimizing

    Science.gov (United States)

    Krzemiński, Michał

    2017-07-01

    The article presents two copyright models for minimizing downtime working brigades. Models have been developed for construction schedules performed using the method of work uniform. Application of flow shop models is possible and useful for the implementation of large objects, which can be divided into plots. The article also presents a condition describing gives which model should be used, as well as a brief example of optimization schedule. The optimization results confirm the legitimacy of the work on the newly-developed models.

  4. Experience in scheduled maintenance

    International Nuclear Information System (INIS)

    Tsai, M.T.

    1985-01-01

    As outage management affects both the cost and reliability of a nuclear power plant, performance of a scheduled maintenance outage in an efficient and effective manner is an important task in the operation of nuclear power plant. This paper covers the experience gained in the past ten refueling outages for the two BWR units at the First Nuclear Power Station of Taipower. The key to optimizing both the cost and schedule of a refueling outage is to maintain a high level of quality workmanship. The outage management in planning, scheduling, preparation, coordination, and cooperation, accompanied by the qualified in-house capability and sufficient outside support, have placed the refueling outages at the FNPS in a well controlled situation and have established the capacity factors of these two BWR units at a level which is 20% higher than the world average in the past years

  5. An avulsion fracture of the calcaneal tuberosity: delay of treatment causes the ‘Achilles heel’ of optimal recovery

    Science.gov (United States)

    Bosman, Willem-Maarten; Leijnen, Michiel; van den Bremer, Jephta; Ritchie, Ewan D

    2016-01-01

    A 72-year-old woman was diagnosed with an avulsion fracture of the tuberosity of the calcaneus. The fracture was planned for elective fixation 12 days after the accident. The planned open reduction and internal fixation was not possible due to a decubital wound on the Achilles heel as a result of pressure on the skin of the fractured tuberosity. Closed reduction and internal fixation was performed, leading to an acceptable outcome. Avulsion fractures of the tuberosity of the calcaneus are rare injuries, and delay in treatment should be avoided as it may lead to preventable complications. PMID:26759395

  6. Self-directed practice schedule enhances learning of suturing skills.

    Science.gov (United States)

    Safir, Oleg; Williams, Camille K; Dubrowski, Adam; Backstein, David; Carnahan, Heather

    2013-12-01

    Most preoperative surgical training programs experience challenges with the availability of expert surgeons to teach trainees. Some research suggests that trainees may benefit from being allowed to actively shape their learning environments, which could alleviate some of the time and resource pressures in surgical training. The purpose of this study was to investigate the effects of self-directed or prescribed practice schedules (random or blocked) on learning suturing skills. Participants watched an instructional video for simple interrupted, vertical mattress and horizontal mattress suturing then completed a pretest to assess baseline skills. Participants were assigned to 1 of 4 practice groups: self-directed practice schedule, prescribed blocked practice schedule, prescribed random practice schedule or matched to the self-directed group (control). Practice of the skill was followed by a delayed (1 h) posttest. Improvement from pretest to posttest was determined based on differences in performance time and expert-based assessments. Analyses revealed a significant effect of group for difference in performance time of the simple interrupted suture. Random practice did not show the expected advantage for skill learning, but there was an advantage of self-directed practice. Self-directed practice schedules may be desirable for optimal learning of simple technical skills, even when expert instruction is available. Instructors must also take into account the interaction between task difficulty and conditions of practice to develop ideal training environments.

  7. Schedulability-Driven Frame Packing for Multi-Cluster Distributed Embedded Systems

    DEFF Research Database (Denmark)

    Pop, Paul; Eles, Petru; Peng, Zebo

    2003-01-01

    We present an approach to frame packing for multi-cluster distributed embedded systems consisting of time-triggered and event-triggered clusters, interconnected via gateways. In our approach, the application messages are packed into frames such that the application is schedulable. Thus, we have...... also proposed a schedulability analysis for applications consisting of mixed event-triggered and time-triggered processes and messages, and a worst case queuing delay analysis for the gateways, responsible for routing inter-cluster traffic. Optimization heuristics for frame packing aiming at producing...

  8. A pre-analysis for the optimal operational scheduling of a pipeline network; Uma pre-analise do problema de otimizacao da programacao das operacoes de uma malha dutoviaria

    Energy Technology Data Exchange (ETDEWEB)

    Czaikowski, Daniel I.; Brondani, William M.; Arantes, Lucas G.; Boschetto, Suelen N.; Lueders, Ricardo; Magatao, Leandro; Stebel, Sergio L. [Universidade Tecnologica Federal do Parana (UTFPR), Curitiba, PR (Brazil); Ribas, Paulo C. [PETROBRAS S.A., Rio de Janeiro, RJ (Brazil). Centro de Pesquisas (CENPES)

    2008-07-01

    This work suggests a Pre-analysis in the input parameters of an optimization system (Bonacin et al., 2007; Boschetto et al., 2008). The proposed method is based on programming techniques that use lists of objects threaded, where objects are elements belonging to the same class, according to the concept of the object-oriented programming. The Preanalysis makes a previous evaluation of a batch sequencing, getting information to be entered into an optimization block. The continuous time Mixed Integer Linear Programming (MILP) model gets such information and determines the scheduling. The models are applied on a pipeline network that connects different areas including refineries, terminals, and final clients. Many oil derivatives (e.g. gasoline, liquefied petroleum gas, naphtha) can be sent or received in this network. The Pre-analysis objective is to reduce the computational time of an MILP model, and the proposed approach can aid the decision-making process to obtain a more detailed scheduling. (author)

  9. Schedule Analytics

    Science.gov (United States)

    2016-04-30

    led several cost research initiatives in cloud computing, service-oriented architecture, and agile development and various independent schedule...and he supports DoD and federal acquisition efforts with a focus on rapid and agile practices to speed solutions with the lowest practical program...assessment, and risk management to control cost and deliver on time. A Government Accountability Office (GAO) assessment of 86 programs that made up the

  10. Optimization of maintenance scheduling with genetic algorithms regarding the storage behavior during the availability prognosis of power plants; Optimierung der Instandhaltungsplanung mit genetischen Algorithmen unter Beruecksichtigung des Speicherverhaltens bei der Verfuegbarkeitsprognose von Kraftwerksanlagen

    Energy Technology Data Exchange (ETDEWEB)

    Warnecke, Martin

    2008-12-19

    In the age of the liberalized energy market the power plant raisers and operators have to consider several factors when choosing the fuel type and dimensioning their power plants, e.g. emissions, erection cost and last but not least operating cost. Simulations assuming different scenarios are required. The rivaling aspects of erection cost, partially dependant availability, maintenance philosophy and operating cost are motivating the optimization of maintenance scheduling and the availability prognosis which are the topic of this thesis. The focus of this thesis is on the scheduling of the time based maintenance strategy. This strategy defines the time spans between the repeating inspections of each component. This is based on the experience of operators and manufacturers. The mathematic problem itself is especially challenging because of strong interdependencies between the single components due to synergy effects. Each component has its own theoretically optimal lifetime and maintenance period. Yet as part of a compound it might be more cost efficient in the long run to maintain some components together shifting some of them forward or backward. The thereby caused interdependencies constitute a non-linear, mixed-whole-numbered calculation of the cost approximation. For the optimization of this maintenance scheduling a new approach was developed. It was realized that the problem couldn't be solved satisfyingly with classic optimization algorithms. Afterwards a solution based on ''genetic algorithms'' was developed. In the meantime the methods for the availability prognosis of complex power plant facilities were enhanced. Especially a new component with storage behavior (with optional losses) was added to the prognosis tool. This storage model integrates the behavior of a storage into the computing time reduced Monte-Carlo-Method. (orig.)

  11. A Time Scheduling Model of Logistics Service Supply Chain with Mass Customized Logistics Service

    Directory of Open Access Journals (Sweden)

    Weihua Liu

    2012-01-01

    Full Text Available With the increasing demand for customized logistics services in the manufacturing industry, the key factor in realizing the competitiveness of a logistics service supply chain (LSSC is whether it can meet specific requirements with the cost of mass service. In this case, in-depth research on the time-scheduling of LSSC is required. Setting the total cost, completion time, and the satisfaction of functional logistics service providers (FLSPs as optimal targets, this paper establishes a time scheduling model of LSSC, which is constrained by the service order time requirement. Numerical analysis is conducted by using Matlab 7.0 software. The effects of the relationship cost coefficient and the time delay coefficient on the comprehensive performance of LSSC are discussed. The results demonstrate that with the time scheduling model in mass-customized logistics services (MCLSs environment, the logistics service integrator (LSI can complete the order earlier or later than scheduled. With the increase of the relationship cost coefficient and the time delay coefficient, the comprehensive performance of LSSC also increases and tends towards stability. In addition, the time delay coefficient has a better effect in increasing the LSSC’s comprehensive performance than the relationship cost coefficient does.

  12. Routing and scheduling of hazardous materials shipments: algorithmic approaches to managing spent nuclear fuel transport

    International Nuclear Information System (INIS)

    Cox, R.G.

    1984-01-01

    Much controversy surrounds government regulation of routing and scheduling of Hazardous Materials Transportation (HMT). Increases in operating costs must be balanced against expected benefits from local HMT bans and curfews when promulgating or preempting HMT regulations. Algorithmic approaches for evaluating HMT routing and scheduling regulatory policy are described. A review of current US HMT regulatory policy is presented to provide a context for the analysis. Next, a multiobjective shortest path algorithm to find the set of efficient routes under conflicting objectives is presented. This algorithm generates all efficient routes under any partial ordering in a single pass through the network. Also, scheduling algorithms are presented to estimate the travel time delay due to HMT curfews along a route. Algorithms are presented assuming either deterministic or stochastic travel times between curfew cities and also possible rerouting to avoid such cities. These algorithms are applied to the case study of US highway transport of spent nuclear fuel from reactors to permanent repositories. Two data sets were used. One data set included the US Interstate Highway System (IHS) network with reactor locations, possible repository sites, and 150 heavily populated areas (HPAs). The other data set contained estimates of the population residing with 0.5 miles of the IHS and the Eastern US. Curfew delay is dramatically reduced by optimally scheduling departure times unless inter-HPA travel times are highly uncertain. Rerouting shipments to avoid HPAs is a less efficient approach to reducing delay

  13. The Probability of Small Schedule Values and Preference for Random-Interval Schedules

    Science.gov (United States)

    Soreth, Michelle Ennis; Hineline, Philip N.

    2009-01-01

    Preference for working on variable schedules and temporal discrimination were simultaneously examined in two experiments using a discrete-trial, concurrent-chains arrangement with fixed interval (FI) and random interval (RI) terminal links. The random schedule was generated by first sampling a probability distribution after the programmed delay to…

  14. Decision support tool for Virtual Power Players: Hybrid Particle Swarm Optimization applied to Day-ahead Vehicle-To-Grid Scheduling

    DEFF Research Database (Denmark)

    Soares, João; Valle, Zita; Morais, Hugo

    2013-01-01

    of a new hybrid method combing a particle swarm approach and a deterministic technique based on mixedinteger linear programming (MILP) to solve the day-ahead scheduling minimizing total operation costs from the aggregator point of view. A realistic mathematical formulation, considering the electric network...

  15. Biobjective Optimization and Evaluation for Transit Signal Priority Strategies at Bus Stop-to-Stop Segment

    Directory of Open Access Journals (Sweden)

    Rui Li

    2016-01-01

    Full Text Available This paper proposes a new optimization framework for the transit signal priority strategies in terms of green extension, red truncation, and phase insertion at the stop-to-stop segment of bus lines. The optimization objective is to minimize both passenger delay and the deviation from bus schedule simultaneously. The objective functions are defined with respect to the segment between bus stops, which can include the adjacent signalized intersections and downstream bus stops. The transit priority signal timing is optimized by using a biobjective optimization framework considering both the total delay at a segment and the delay deviation from the arrival schedules at bus stops. The proposed framework is evaluated using a VISSIM model calibrated with field traffic volume and traffic signal data of Caochangmen Boulevard in Nanjing, China. The optimized TSP-based phasing plans result in the reduced delay and improved reliability, compared with the non-TSP scenario under the different traffic flow conditions in the morning peak hour. The evaluation results indicate the promising performance of the proposed optimization framework in reducing the passenger delay and improving the bus schedule adherence for the urban transit system.

  16. Optimal design of distributed control and embedded systems

    CERN Document Server

    Çela, Arben; Li, Xu-Guang; Niculescu, Silviu-Iulian

    2014-01-01

    Optimal Design of Distributed Control and Embedded Systems focuses on the design of special control and scheduling algorithms based on system structural properties as well as on analysis of the influence of induced time-delay on systems performances. It treats the optimal design of distributed and embedded control systems (DCESs) with respect to communication and calculation-resource constraints, quantization aspects, and potential time-delays induced by the associated  communication and calculation model. Particular emphasis is put on optimal control signal scheduling based on the system state. In order to render  this complex optimization problem feasible in real time, a time decomposition is based on periodicity induced by the static scheduling is operated. The authors present a co-design approach which subsumes the synthesis of the optimal control laws and the generation of an optimal schedule of control signals on real-time networks as well as the execution of control tasks on a single processor. The a...

  17. Multidrug resistance circumvention by a new triazinoaminopiperidine derivative S9788 in vitro: definition of the optimal schedule and comparison with verapamil.

    Science.gov (United States)

    Julia, A. M.; Roché, H.; Berlion, M.; Lucas, C.; Milano, G.; Robert, J.; Bizzari, J. P.; Canal, P.

    1994-01-01

    The current work was undertaken to investigate the importance of exposure sequence and duration in achieving the maximum reversal action of S9788 on doxorubicin (DOX) cytotoxicity against cells that exhibit the (MDR) multidrug resistance phenotype: the MCF7/DOX cell line. Accumulation and release of DOX were examined in this cell line. The reversal effect was compared with that obtained with verapamil. S9788 activity was schedule dependent: when comparing incubation with S9788 before or after treatment with DOX, the best reversal factor was obtained in the case of a post-treatment incubation (65.6 +/- 7.7 vs 20.8 +/- 7.0). S9788 was a more potent modulating agent than verapamil, whatever the schedule of exposure of the cells to the reversal agent. The reversal of resistance after short-term DOX exposures was caused not only by prolonged cellular accumulation of DOX, but also by its prolonged retention after transfer of cells to DOX-free medium. A relationship was noted between cellular exposure to DOX and the cytotoxic effect, and so the reversal of resistance induced by S9788 appears to be directly linked to the level of cell exposure to DOX. This work provided a rationale for improving the schedule of administration of S9788 in clinical trials. PMID:8180016

  18. PRIORITY BASED PACKET SCHEDULING APPROACH FOR WIRELESS SENSOR NETWORKS

    OpenAIRE

    K. K. Kannan

    2017-01-01

    A priority based packet scheduling scheme is proposed which aims at scheduling different types of data packets, such as real time and non-real-time data packets at sensor nodes with resource constraints in Wireless Sensor Networks. Most of the existing packet-scheduling mechanisms of Wireless Sensor Networks use First Come First Served (FCFS), non-preemptive priority and preemptive priority scheduling algorithms. These algorithms results in long end-to-end data transmission delay, high energy...

  19. Solving no-wait two-stage flexible flow shop scheduling problem with unrelated parallel machines and rework time by the adjusted discrete Multi Objective Invasive Weed Optimization and fuzzy dominance approach

    International Nuclear Information System (INIS)

    Jafarzadeh, Hassan; Moradinasab, Nazanin; Gerami, Ali

    2017-01-01

    Adjusted discrete Multi-Objective Invasive Weed Optimization (DMOIWO) algorithm, which uses fuzzy dominant approach for ordering, has been proposed to solve No-wait two-stage flexible flow shop scheduling problem. Design/methodology/approach: No-wait two-stage flexible flow shop scheduling problem by considering sequence-dependent setup times and probable rework in both stations, different ready times for all jobs and rework times for both stations as well as unrelated parallel machines with regards to the simultaneous minimization of maximum job completion time and average latency functions have been investigated in a multi-objective manner. In this study, the parameter setting has been carried out using Taguchi Method based on the quality indicator for beater performance of the algorithm. Findings: The results of this algorithm have been compared with those of conventional, multi-objective algorithms to show the better performance of the proposed algorithm. The results clearly indicated the greater performance of the proposed algorithm. Originality/value: This study provides an efficient method for solving multi objective no-wait two-stage flexible flow shop scheduling problem by considering sequence-dependent setup times, probable rework in both stations, different ready times for all jobs, rework times for both stations and unrelated parallel machines which are the real constraints.

  20. Solving no-wait two-stage flexible flow shop scheduling problem with unrelated parallel machines and rework time by the adjusted discrete Multi Objective Invasive Weed Optimization and fuzzy dominance approach

    Energy Technology Data Exchange (ETDEWEB)

    Jafarzadeh, Hassan; Moradinasab, Nazanin; Gerami, Ali

    2017-07-01

    Adjusted discrete Multi-Objective Invasive Weed Optimization (DMOIWO) algorithm, which uses fuzzy dominant approach for ordering, has been proposed to solve No-wait two-stage flexible flow shop scheduling problem. Design/methodology/approach: No-wait two-stage flexible flow shop scheduling problem by considering sequence-dependent setup times and probable rework in both stations, different ready times for all jobs and rework times for both stations as well as unrelated parallel machines with regards to the simultaneous minimization of maximum job completion time and average latency functions have been investigated in a multi-objective manner. In this study, the parameter setting has been carried out using Taguchi Method based on the quality indicator for beater performance of the algorithm. Findings: The results of this algorithm have been compared with those of conventional, multi-objective algorithms to show the better performance of the proposed algorithm. The results clearly indicated the greater performance of the proposed algorithm. Originality/value: This study provides an efficient method for solving multi objective no-wait two-stage flexible flow shop scheduling problem by considering sequence-dependent setup times, probable rework in both stations, different ready times for all jobs, rework times for both stations and unrelated parallel machines which are the real constraints.

  1. A time scheduling model of logistics service supply chain based on the customer order decoupling point: a perspective from the constant service operation time.

    Science.gov (United States)

    Liu, Weihua; Yang, Yi; Xu, Haitao; Liu, Xiaoyan; Wang, Yijia; Liang, Zhicheng

    2014-01-01

    In mass customization logistics service, reasonable scheduling of the logistics service supply chain (LSSC), especially time scheduling, is benefit to increase its competitiveness. Therefore, the effect of a customer order decoupling point (CODP) on the time scheduling performance should be considered. To minimize the total order operation cost of the LSSC, minimize the difference between the expected and actual time of completing the service orders, and maximize the satisfaction of functional logistics service providers, this study establishes an LSSC time scheduling model based on the CODP. Matlab 7.8 software is used in the numerical analysis for a specific example. Results show that the order completion time of the LSSC can be delayed or be ahead of schedule but cannot be infinitely advanced or infinitely delayed. Obtaining the optimal comprehensive performance can be effective if the expected order completion time is appropriately delayed. The increase in supply chain comprehensive performance caused by the increase in the relationship coefficient of logistics service integrator (LSI) is limited. The relative concern degree of LSI on cost and service delivery punctuality leads to not only changes in CODP but also to those in the scheduling performance of the LSSC.

  2. A Time Scheduling Model of Logistics Service Supply Chain Based on the Customer Order Decoupling Point: A Perspective from the Constant Service Operation Time

    Science.gov (United States)

    Yang, Yi; Xu, Haitao; Liu, Xiaoyan; Wang, Yijia; Liang, Zhicheng

    2014-01-01

    In mass customization logistics service, reasonable scheduling of the logistics service supply chain (LSSC), especially time scheduling, is benefit to increase its competitiveness. Therefore, the effect of a customer order decoupling point (CODP) on the time scheduling performance should be considered. To minimize the total order operation cost of the LSSC, minimize the difference between the expected and actual time of completing the service orders, and maximize the satisfaction of functional logistics service providers, this study establishes an LSSC time scheduling model based on the CODP. Matlab 7.8 software is used in the numerical analysis for a specific example. Results show that the order completion time of the LSSC can be delayed or be ahead of schedule but cannot be infinitely advanced or infinitely delayed. Obtaining the optimal comprehensive performance can be effective if the expected order completion time is appropriately delayed. The increase in supply chain comprehensive performance caused by the increase in the relationship coefficient of logistics service integrator (LSI) is limited. The relative concern degree of LSI on cost and service delivery punctuality leads to not only changes in CODP but also to those in the scheduling performance of the LSSC. PMID:24715818

  3. A Time Scheduling Model of Logistics Service Supply Chain Based on the Customer Order Decoupling Point: A Perspective from the Constant Service Operation Time

    Directory of Open Access Journals (Sweden)

    Weihua Liu

    2014-01-01

    Full Text Available In mass customization logistics service, reasonable scheduling of the logistics service supply chain (LSSC, especially time scheduling, is benefit to increase its competitiveness. Therefore, the effect of a customer order decoupling point (CODP on the time scheduling performance should be considered. To minimize the total order operation cost of the LSSC, minimize the difference between the expected and actual time of completing the service orders, and maximize the satisfaction of functional logistics service providers, this study establishes an LSSC time scheduling model based on the CODP. Matlab 7.8 software is used in the numerical analysis for a specific example. Results show that the order completion time of the LSSC can be delayed or be ahead of schedule but cannot be infinitely advanced or infinitely delayed. Obtaining the optimal comprehensive performance can be effective if the expected order completion time is appropriately delayed. The increase in supply chain comprehensive performance caused by the increase in the relationship coefficient of logistics service integrator (LSI is limited. The relative concern degree of LSI on cost and service delivery punctuality leads to not only changes in CODP but also to those in the scheduling performance of the LSSC.

  4. Multi-Objective Scheduling Optimization Based on a Modified Non-Dominated Sorting Genetic Algorithm-II in Voltage Source Converter−Multi-Terminal High Voltage DC Grid-Connected Offshore Wind Farms with Battery Energy Storage Systems

    Directory of Open Access Journals (Sweden)

    Ho-Young Kim

    2017-07-01

    Full Text Available Improving the performance of power systems has become a challenging task for system operators in an open access environment. This paper presents an optimization approach for solving the multi-objective scheduling problem using a modified non-dominated sorting genetic algorithm in a hybrid network of meshed alternating current (AC/wind farm grids. This approach considers voltage and power control modes based on multi-terminal voltage source converter high-voltage direct current (MTDC and battery energy storage systems (BESS. To enhance the hybrid network station performance, we implement an optimal process based on the battery energy storage system operational strategy for multi-objective scheduling over a 24 h demand profile. Furthermore, the proposed approach is formulated as a master problem and a set of sub-problems associated with the hybrid network station to improve the overall computational efficiency using Benders’ decomposition. Based on the results of the simulations conducted on modified institute of electrical and electronics engineers (IEEE-14 bus and IEEE-118 bus test systems, we demonstrate and confirm the applicability, effectiveness and validity of the proposed approach.

  5. Choice between Single and Multiple Reinforcers in Concurrent-Chains Schedules

    Science.gov (United States)

    Mazur, James E.

    2006-01-01

    Pigeons responded on concurrent-chains schedules with equal variable-interval schedules as initial links. One terminal link delivered a single reinforcer after a fixed delay, and the other terminal link delivered either three or five reinforcers, each preceded by a fixed delay. Some conditions included a postreinforcer delay after the single…

  6. Elastic Scheduling of Scientific Workflows under Deadline Constraints in Cloud Computing Environments

    Directory of Open Access Journals (Sweden)

    Nazia Anwar

    2018-01-01

    Full Text Available Scientific workflow applications are collections of several structured activities and fine-grained computational tasks. Scientific workflow scheduling in cloud computing is a challenging research topic due to its distinctive features. In cloud environments, it has become critical to perform efficient task scheduling resulting in reduced scheduling overhead, minimized cost and maximized resource utilization while still meeting the user-specified overall deadline. This paper proposes a strategy, Dynamic Scheduling of Bag of Tasks based workflows (DSB, for scheduling scientific workflows with the aim to minimize financial cost of leasing Virtual Machines (VMs under a user-defined deadline constraint. The proposed model groups the workflow into Bag of Tasks (BoTs based on data dependency and priority constraints and thereafter optimizes the allocation and scheduling of BoTs on elastic, heterogeneous and dynamically provisioned cloud resources called VMs in order to attain the proposed method’s objectives. The proposed approach considers pay-as-you-go Infrastructure as a Service (IaaS clouds having inherent features such as elasticity, abundance, heterogeneity and VM provisioning delays. A trace-based simulation using benchmark scientific workflows representing real world applications, demonstrates a significant reduction in workflow computation cost while the workflow deadline is met. The results validate that the proposed model produces better success rates to meet deadlines and cost efficiencies in comparison to adapted state-of-the-art algorithms for similar problems.

  7. Delayed Puberty

    DEFF Research Database (Denmark)

    Kolby, Nanna; Busch, Alexander Siegfried; Juul, Anders

    2017-01-01

    Delayed puberty can be a source of great concern and anxiety, although it usually is caused by a self-limiting variant of the normal physiological timing named constitutional delay of growth and puberty (CDGP). Delayed puberty can, however, also be the first presentation of a permanent condition ...... mineral density) and psychological (e.g., low self-esteem) and underline the importance of careful clinical assessment of the patients....

  8. Records Control Schedules Repository

    Data.gov (United States)

    National Archives and Records Administration — The Records Control Schedules (RCS) repository provides access to scanned versions of records schedules, or Standard Form 115, Request for Records Disposition...

  9. Non-clairvoyant Scheduling Games

    Science.gov (United States)

    Dürr, Christoph; Nguyen, Kim Thang

    In a scheduling game, each player owns a job and chooses a machine to execute it. While the social cost is the maximal load over all machines (makespan), the cost (disutility) of each player is the completion time of its own job. In the game, players may follow selfish strategies to optimize their cost and therefore their behaviors do not necessarily lead the game to an equilibrium. Even in the case there is an equilibrium, its makespan might be much larger than the social optimum, and this inefficiency is measured by the price of anarchy - the worst ratio between the makespan of an equilibrium and the optimum. Coordination mechanisms aim to reduce the price of anarchy by designing scheduling policies that specify how jobs assigned to a same machine are to be scheduled. Typically these policies define the schedule according to the processing times as announced by the jobs. One could wonder if there are policies that do not require this knowledge, and still provide a good price of anarchy. This would make the processing times be private information and avoid the problem of truthfulness. In this paper we study these so-called non-clairvoyant policies. In particular, we study the RANDOM policy that schedules the jobs in a random order without preemption, and the EQUI policy that schedules the jobs in parallel using time-multiplexing, assigning each job an equal fraction of CPU time.

  10. Real-time energy-saving metro train rescheduling with primary delay identification

    Science.gov (United States)

    Li, Keping; Schonfeld, Paul

    2018-01-01

    This paper aims to reschedule online metro trains in delay scenarios. A graph representation and a mixed integer programming model are proposed to formulate the optimization problem. The solution approach is a two-stage optimization method. In the first stage, based on a proposed train state graph and system analysis, the primary and flow-on delays are specifically analyzed and identified with a critical path algorithm. For the second stage a hybrid genetic algorithm is designed to optimize the schedule, with the delay identification results as input. Then, based on the infrastructure data of Beijing Subway Line 4 of China, case studies are presented to demonstrate the effectiveness and efficiency of the solution approach. The results show that the algorithm can quickly and accurately identify primary delays among different types of delays. The economic cost of energy consumption and total delay is considerably reduced (by more than 10% in each case). The computation time of the Hybrid-GA is low enough for rescheduling online. Sensitivity analyses further demonstrate that the proposed approach can be used as a decision-making support tool for operators. PMID:29474471

  11. Permissible Delay in Payments

    Directory of Open Access Journals (Sweden)

    Yung-Fu Huang

    2007-01-01

    Full Text Available The main purpose of this paper wants to investigate the optimal retailer's lot-sizing policy with two warehouses under partially permissible delay in payments within the economic order quantity (EOQ framework. In this paper, we want to extend that fully permissible delay in payments to the supplier would offer the retailer partially permissible delay in payments. That is, the retailer must make a partial payment to the supplier when the order is received. Then the retailer must pay off the remaining balance at the end of the permissible delay period. In addition, we want to add the assumption that the retailer's storage space is limited. That is, the retailer will rent the warehouse to store these exceeding items when the order quantity is larger than retailer's storage space. Under these conditions, we model the retailer's inventory system as a cost minimization problem to determine the retailer's optimal cycle time and optimal order quantity. Three theorems are developed to efficiently determine the optimal replenishment policy for the retailer. Finally, numerical examples are given to illustrate these theorems and obtained a lot of managerial insights.

  12. Optimization

    CERN Document Server

    Pearce, Charles

    2009-01-01

    Focuses on mathematical structure, and on real-world applications. This book includes developments in several optimization-related topics such as decision theory, linear programming, turnpike theory, duality theory, convex analysis, and queuing theory.

  13. Evaluation of different initial solution algorithms to be used in the heuristics optimization to solve the energy resource scheduling in smart grids

    DEFF Research Database (Denmark)

    Sousa, Tiago; Morais, Hugo; Castro, Rui

    2016-01-01

    of finding a final solution near to the optimal than using a random initial solution. This paper proposes two initial solution algorithms to be used by a metaheuristic technique (simulated annealing). These algorithms are tested and evaluated with other published algorithms that obtain initial solution....... The proposed algorithms have been developed as modules to be more flexible their use by other metaheuristics than just simulated annealing. The simulated annealing with different initial solution algorithms has been tested in a 37-bus distribution network with distributed resources, especially electric...... vehicles. The proposed algorithms proved to present results very close to the optimal with a small difference between 0.1%. A deterministic technique is used as comparison and it took around 26 h to obtain the optimal one. On the other hand, the simulated annealing was able of obtaining results around 1...

  14. Optimal Load-Tracking Operation of Grid-Connected Solid Oxide Fuel Cells through Set Point Scheduling and Combined L1-MPC Control

    Directory of Open Access Journals (Sweden)

    Siwei Han

    2018-03-01

    Full Text Available An optimal load-tracking operation strategy for a grid-connected tubular solid oxide fuel cell (SOFC is studied based on the steady-state analysis of the system thermodynamics and electrochemistry. Control of the SOFC is achieved by a two-level hierarchical control system. In the upper level, optimal setpoints of output voltage and the current corresponding to unit load demand is obtained through a nonlinear optimization by minimizing the SOFC’s internal power waste. In the lower level, a combined L1-MPC control strategy is designed to achieve fast set point tracking under system nonlinearities, while maintaining a constant fuel utilization factor. To prevent fuel starvation during the transient state resulting from the output power surging, a fuel flow constraint is imposed on the MPC with direct electron balance calculation. The proposed control schemes are testified on the grid-connected SOFC model.

  15. On Reducing Delay in Mesh-Based P2P Streaming: A Mesh-Push Approach

    Science.gov (United States)

    Liu, Zheng; Xue, Kaiping; Hong, Peilin

    The peer-assisted streaming paradigm has been widely employed to distribute live video data on the internet recently. In general, the mesh-based pull approach is more robust and efficient than the tree-based push approach. However, pull protocol brings about longer streaming delay, which is caused by the handshaking process of advertising buffer map message, sending request message and scheduling of the data block. In this paper, we propose a new approach, mesh-push, to address this issue. Different from the traditional pull approach, mesh-push implements block scheduling algorithm at sender side, where the block transmission is initiated by the sender rather than by the receiver. We first formulate the optimal upload bandwidth utilization problem, then present the mesh-push approach, in which a token protocol is designed to avoid block redundancy; a min-cost flow model is employed to derive the optimal scheduling for the push peer; and a push peer selection algorithm is introduced to reduce control overhead. Finally, we evaluate mesh-push through simulation, the results of which show mesh-push outperforms the pull scheduling in streaming delay, and achieves comparable delivery ratio at the same time.

  16. Multiobjective Synergistic Scheduling Optimization Model for Wind Power and Plug-In Hybrid Electric Vehicles under Different Grid-Connected Modes

    Directory of Open Access Journals (Sweden)

    Liwei Ju

    2014-01-01

    Full Text Available In order to promote grid’s wind power absorptive capacity and to overcome the adverse impacts of wind power on the stable operation of power system, this paper establishes benefit contrastive analysis models of wind power and plug-in hybrid electric vehicles (PHEVs under the optimization goal of minimum coal consumption and pollutant emission considering multigrid connected modes. Then, a two-step adaptive solving algorithm is put forward to get the optimal system operation scheme with the highest membership degree based on the improved ε constraints method and fuzzy decision theory. Thirdly, the IEEE36 nodes 10-unit system is used as the simulation system. Finally, the sensitive analysis for PHEV’s grid connected number is made. The result shows the proposed algorithm is feasible and effective to solve the model. PHEV’s grid connection could achieve load shifting effect and promote wind power grid connection. Especially, the optimization goals reach the optimum in fully optimal charging mode. As PHEV’s number increases, both abandoned wind and thermal power generation cost would decrease and the peak and valley difference of load curve would gradually be reduced.

  17. Rostering and Task Scheduling

    DEFF Research Database (Denmark)

    Dohn, Anders Høeg

    to scheduling problems with temporal dependencies between tasks. However, these problems appear in various contexts and with different properties. A group of the problems considered are related to vehicle routing problems, where transportation and time windows are important factors that must be accounted for....... Mathematical and logic-based models are presented for the problems considered. Novel components are added to existing models and the modeling decisions are justified. In one case, the model is solved by a simple, but efficient greedy construction heuristic. In the remaining cases, column generation is applied....... Column generation is an iterative exact solution method based on the theory of linear programming and is capable of providing provably optimal solutions. In some of the applications, the approach is modified to provide feasible solutions of high-quality in less time. The exceptional solution quality...

  18. Exploration of the Reasons for Delays in Construction

    DEFF Research Database (Denmark)

    Lindhard, Søren Munch; Wandahl, Søren

    2014-01-01

    ) was introduced as a production planning and control system to increase the reliability of scheduling task. By focusing on the removal of constraints, the LPS has successfully decreased the number of delayed activities. To further decrease delays, this research investigates the causes for delays at three......Construction sites are dominated by chaos and complexity, enforcing challenging conditions for establishing reliable and robust schedules that are easy to observe. The consequence is a large amount of delayed activities that again results in an unreliable schedule. Last planner system (LPS...

  19. MEDICAL STAFF SCHEDULING USING SIMULATED ANNEALING

    Directory of Open Access Journals (Sweden)

    Ladislav Rosocha

    2015-07-01

    Full Text Available Purpose: The efficiency of medical staff is a fundamental feature of healthcare facilities quality. Therefore the better implementation of their preferences into the scheduling problem might not only rise the work-life balance of doctors and nurses, but also may result into better patient care. This paper focuses on optimization of medical staff preferences considering the scheduling problem.Methodology/Approach: We propose a medical staff scheduling algorithm based on simulated annealing, a well-known method from statistical thermodynamics. We define hard constraints, which are linked to legal and working regulations, and minimize the violations of soft constraints, which are related to the quality of work, psychic, and work-life balance of staff.Findings: On a sample of 60 physicians and nurses from gynecology department we generated monthly schedules and optimized their preferences in terms of soft constraints. Our results indicate that the final value of objective function optimized by proposed algorithm is more than 18-times better in violations of soft constraints than initially generated random schedule that satisfied hard constraints.Research Limitation/implication: Even though the global optimality of final outcome is not guaranteed, desirable solutionwas obtained in reasonable time. Originality/Value of paper: We show that designed algorithm is able to successfully generate schedules regarding hard and soft constraints. Moreover, presented method is significantly faster than standard schedule generation and is able to effectively reschedule due to the local neighborhood search characteristics of simulated annealing.

  20. Minimization of Delay Costs in the Realization of Production Orders in Two-Machine System

    Science.gov (United States)

    Dylewski, Robert; Jardzioch, Andrzej; Dworak, Oliver

    2018-03-01

    The article presents a new algorithm that enables the allocation of the optimal scheduling of the production orders in the two-machine system based on the minimum cost of order delays. The formulated algorithm uses the method of branch and bounds and it is a particular generalisation of the algorithm enabling for the determination of the sequence of the production orders with the minimal sum of the delays. In order to illustrate the proposed algorithm in the best way, the article contains examples accompanied by the graphical trees of solutions. The research analysing the utility of the said algorithm was conducted. The achieved results proved the usefulness of the proposed algorithm when applied to scheduling of orders. The formulated algorithm was implemented in the Matlab programme. In addition, the studies for different sets of production orders were conducted.