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Sample records for scheduling method based

  1. Distributed Research Project Scheduling Based on Multi-Agent Methods

    Directory of Open Access Journals (Sweden)

    Constanta Nicoleta Bodea

    2011-01-01

    Full Text Available Different project planning and scheduling approaches have been developed. The Operational Research (OR provides two major planning techniques: CPM (Critical Path Method and PERT (Program Evaluation and Review Technique. Due to projects complexity and difficulty to use classical methods, new approaches were developed. Artificial Intelligence (AI initially promoted the automatic planner concept, but model-based planning and scheduling methods emerged later on. The paper adresses the project scheduling optimization problem, when projects are seen as Complex Adaptive Systems (CAS. Taken into consideration two different approaches for project scheduling optimization: TCPSP (Time- Constrained Project Scheduling and RCPSP (Resource-Constrained Project Scheduling, the paper focuses on a multiagent implementation in MATLAB for TCSP. Using the research project as a case study, the paper includes a comparison between two multi-agent methods: Genetic Algorithm (GA and Ant Colony Algorithm (ACO.

  2. A QUADTREE ORGANIZATION CONSTRUCTION AND SCHEDULING METHOD FOR URBAN 3D MODEL BASED ON WEIGHT

    OpenAIRE

    C. Yao; G. Peng; Y. Song; M. Duan

    2017-01-01

    The increasement of Urban 3D model precision and data quantity puts forward higher requirements for real-time rendering of digital city model. Improving the organization, management and scheduling of 3D model data in 3D digital city can improve the rendering effect and efficiency. This paper takes the complexity of urban models into account, proposes a Quadtree construction and scheduling rendering method for Urban 3D model based on weight. Divide Urban 3D model into different rendering weigh...

  3. An Application-Level QoS Control Method Based on Local Bandwidth Scheduling

    Directory of Open Access Journals (Sweden)

    Yong Wang

    2018-01-01

    Full Text Available Quality of service (QoS is an important performance indicator for Web applications and bandwidth is a key factor affecting QoS. Current methods use network protocols or ports to schedule bandwidth, which require tedious manual configurations or modifications of the underlying network. Some applications use dynamic ports and the traditional port-based bandwidth control methods cannot deal with them. A new QoS control method based on local bandwidth scheduling is proposed, which can schedule bandwidth at application level in a user-transparent way and it does not require tedious manual configurations. Experimental results indicate that the new method can effectively improve the QoS for applications, and it can be easily integrated into current Web applications without the need to modify the underlying network.

  4. Efficient operation scheduling for adsorption chillers using predictive optimization-based control methods

    Science.gov (United States)

    Bürger, Adrian; Sawant, Parantapa; Bohlayer, Markus; Altmann-Dieses, Angelika; Braun, Marco; Diehl, Moritz

    2017-10-01

    Within this work, the benefits of using predictive control methods for the operation of Adsorption Cooling Machines (ACMs) are shown on a simulation study. Since the internal control decisions of series-manufactured ACMs often cannot be influenced, the work focuses on optimized scheduling of an ACM considering its internal functioning as well as forecasts for load and driving energy occurrence. For illustration, an assumed solar thermal climate system is introduced and a system model suitable for use within gradient-based optimization methods is developed. The results of a system simulation using a conventional scheme for ACM scheduling are compared to the results of a predictive, optimization-based scheduling approach for the same exemplary scenario of load and driving energy occurrence. The benefits of the latter approach are shown and future actions for application of these methods for system control are addressed.

  5. Constraint-based scheduling

    Science.gov (United States)

    Zweben, Monte

    1993-01-01

    The GERRY scheduling system developed by NASA Ames with assistance from the Lockheed Space Operations Company, and the Lockheed Artificial Intelligence Center, uses a method called constraint-based iterative repair. Using this technique, one encodes both hard rules and preference criteria into data structures called constraints. GERRY repeatedly attempts to improve schedules by seeking repairs for violated constraints. The system provides a general scheduling framework which is being tested on two NASA applications. The larger of the two is the Space Shuttle Ground Processing problem which entails the scheduling of all the inspection, repair, and maintenance tasks required to prepare the orbiter for flight. The other application involves power allocation for the NASA Ames wind tunnels. Here the system will be used to schedule wind tunnel tests with the goal of minimizing power costs. In this paper, we describe the GERRY system and its application to the Space Shuttle problem. We also speculate as to how the system would be used for manufacturing, transportation, and military problems.

  6. Location-based Scheduling

    DEFF Research Database (Denmark)

    Andersson, Niclas; Christensen, Knud

    on the market. However, CPM is primarily an activity based method that takes the activity as the unit of focus and there is criticism raised, specifically in the case of construction projects, on the method for deficient management of construction work and continuous flow of resources. To seek solutions...... to the identified limitations of the CPM method, an alternative planning and scheduling methodology that includes locations is tested. Location-based Scheduling (LBS) implies a shift in focus, from primarily the activities to the flow of work through the various locations of the project, i.e. the building. LBS uses...... the graphical presentation technique of Line-of-balance, which is adapted for planning and management of work-flows that facilitates resources to perform their work without interruptions caused by other resources working with other activities in the same location. As such, LBS and Lean Construction share...

  7. a Quadtree Organization Construction and Scheduling Method for Urban 3d Model Based on Weight

    Science.gov (United States)

    Yao, C.; Peng, G.; Song, Y.; Duan, M.

    2017-09-01

    The increasement of Urban 3D model precision and data quantity puts forward higher requirements for real-time rendering of digital city model. Improving the organization, management and scheduling of 3D model data in 3D digital city can improve the rendering effect and efficiency. This paper takes the complexity of urban models into account, proposes a Quadtree construction and scheduling rendering method for Urban 3D model based on weight. Divide Urban 3D model into different rendering weights according to certain rules, perform Quadtree construction and schedule rendering according to different rendering weights. Also proposed an algorithm for extracting bounding box extraction based on model drawing primitives to generate LOD model automatically. Using the algorithm proposed in this paper, developed a 3D urban planning&management software, the practice has showed the algorithm is efficient and feasible, the render frame rate of big scene and small scene are both stable at around 25 frames.

  8. A QUADTREE ORGANIZATION CONSTRUCTION AND SCHEDULING METHOD FOR URBAN 3D MODEL BASED ON WEIGHT

    Directory of Open Access Journals (Sweden)

    C. Yao

    2017-09-01

    Full Text Available The increasement of Urban 3D model precision and data quantity puts forward higher requirements for real-time rendering of digital city model. Improving the organization, management and scheduling of 3D model data in 3D digital city can improve the rendering effect and efficiency. This paper takes the complexity of urban models into account, proposes a Quadtree construction and scheduling rendering method for Urban 3D model based on weight. Divide Urban 3D model into different rendering weights according to certain rules, perform Quadtree construction and schedule rendering according to different rendering weights. Also proposed an algorithm for extracting bounding box extraction based on model drawing primitives to generate LOD model automatically. Using the algorithm proposed in this paper, developed a 3D urban planning&management software, the practice has showed the algorithm is efficient and feasible, the render frame rate of big scene and small scene are both stable at around 25 frames.

  9. A Dynamic Resource Scheduling Method Based on Fuzzy Control Theory in Cloud Environment

    Directory of Open Access Journals (Sweden)

    Zhijia Chen

    2015-01-01

    Full Text Available The resources in cloud environment have features such as large-scale, diversity, and heterogeneity. Moreover, the user requirements for cloud computing resources are commonly characterized by uncertainty and imprecision. Hereby, to improve the quality of cloud computing service, not merely should the traditional standards such as cost and bandwidth be satisfied, but also particular emphasis should be laid on some extended standards such as system friendliness. This paper proposes a dynamic resource scheduling method based on fuzzy control theory. Firstly, the resource requirements prediction model is established. Then the relationships between resource availability and the resource requirements are concluded. Afterwards fuzzy control theory is adopted to realize a friendly match between user needs and resources availability. Results show that this approach improves the resources scheduling efficiency and the quality of service (QoS of cloud computing.

  10. Multi-Agent Based Beam Search for Real-Time Production Scheduling and Control Method, Software and Industrial Application

    CERN Document Server

    Kang, Shu Gang

    2013-01-01

    The Multi-Agent Based Beam Search (MABBS) method systematically integrates four major requirements of manufacturing production - representation capability, solution quality, computation efficiency, and implementation difficulty - within a unified framework to deal with the many challenges of complex real-world production planning and scheduling problems. Multi-agent Based Beam Search for Real-time Production Scheduling and Control introduces this method, together with its software implementation and industrial applications.  This book connects academic research with industrial practice, and develops a practical solution to production planning and scheduling problems. To simplify implementation, a reusable software platform is developed to build the MABBS method into a generic computation engine.  This engine is integrated with a script language, called the Embedded Extensible Application Script Language (EXASL), to provide a flexible and straightforward approach to representing complex real-world problems. ...

  11. Constraint-based job shop scheduling with ILOG SCHEDULER

    NARCIS (Netherlands)

    Nuijten, W.P.M.; Le Pape, C.

    1998-01-01

    We introduce constraint-based scheduling and discuss its main principles. An approximation algorithm based on tree search is developed for the job shop scheduling problem using ILOG SCHEDULER. A new way of calculating lower bounds on the makespan of the job shop scheduling problem is presented and

  12. Efficient Load Scheduling Method For Power Management

    Directory of Open Access Journals (Sweden)

    Vijo M Joy

    2015-08-01

    Full Text Available An efficient load scheduling method to meet varying power supply needs is presented in this paper. At peak load times the power generation system fails due to its instability. Traditionally we use load shedding process. In load shedding process disconnect the unnecessary and extra loads. The proposed method overcomes this problem by scheduling the load based on the requirement. Artificial neural networks are used for this optimal load scheduling process. For generate economic scheduling artificial neural network has been used because generation of power from each source is economically different. In this the total load required is the inputs of this network and the power generation from each source and power losses at the time of transmission are the output of the neural network. Training and programming of the artificial neural networks are done using MATLAB.

  13. Knowledge-based scheduling of arrival aircraft

    Science.gov (United States)

    Krzeczowski, K.; Davis, T.; Erzberger, H.; Lev-Ram, I.; Bergh, C.

    1995-01-01

    A knowledge-based method for scheduling arrival aircraft in the terminal area has been implemented and tested in real-time simulation. The scheduling system automatically sequences, assigns landing times, and assigns runways to arrival aircraft by utilizing continuous updates of aircraft radar data and controller inputs. The scheduling algorithms is driven by a knowledge base which was obtained in over two thousand hours of controller-in-the-loop real-time simulation. The knowledge base contains a series of hierarchical 'rules' and decision logic that examines both performance criteria, such as delay reduction, as well as workload reduction criteria, such as conflict avoidance. The objective of the algorithms is to devise an efficient plan to land the aircraft in a manner acceptable to the air traffic controllers. This paper will describe the scheduling algorithms, give examples of their use, and present data regarding their potential benefits to the air traffic system.

  14. Power Scheduling Method for Demand Response based on Home Energy Management System using Stochastic Process

    OpenAIRE

    Moreno, Pablo; García, Marcelo

    2016-01-01

    The increase in energy consumption, especially in residential consumers, means that the electrical system should grow at pair, in infrastructure and installed capacity, the energy prices vary to meet these needs, so this paper uses the methodology of demand response using stochastic methods such as Markov, to optimize energy consumption of residential users. It is necessary to involve customers in the electrical system because in this way it can be verified the actual amount of electric charg...

  15. 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.

  16. Constraint-based scheduling applying constraint programming to scheduling problems

    CERN Document Server

    Baptiste, Philippe; Nuijten, Wim

    2001-01-01

    Constraint Programming is a problem-solving paradigm that establishes a clear distinction between two pivotal aspects of a problem: (1) a precise definition of the constraints that define the problem to be solved and (2) the algorithms and heuristics enabling the selection of decisions to solve the problem. It is because of these capabilities that Constraint Programming is increasingly being employed as a problem-solving tool to solve scheduling problems. Hence the development of Constraint-Based Scheduling as a field of study. The aim of this book is to provide an overview of the most widely used Constraint-Based Scheduling techniques. Following the principles of Constraint Programming, the book consists of three distinct parts: The first chapter introduces the basic principles of Constraint Programming and provides a model of the constraints that are the most often encountered in scheduling problems. Chapters 2, 3, 4, and 5 are focused on the propagation of resource constraints, which usually are responsibl...

  17. PRACTICAL IMPLICATIONS OF LOCATION-BASED SCHEDULING

    DEFF Research Database (Denmark)

    Andersson, Niclas; Christensen, Knud

    2007-01-01

    The traditional method for planning, scheduling and controlling activities and resources in construction projects is the CPM-scheduling, which has been the predominant scheduling method since its introduction in the late 1950s. Over the years, CPM has proven to be a very powerful technique...... that will be used in this study. LBS is a scheduling method that rests upon the theories of line-of-balance and which uses the graphic representation of a flowline chart. As such, LBS is adapted for planning and management of workflows and, thus, may provide a solution to the identified shortcomings of CPM. Even...

  18. BIM-BASED SCHEDULING OF CONSTRUCTION

    DEFF Research Database (Denmark)

    Andersson, Niclas; Büchmann-Slorup, Rolf

    2010-01-01

    The potential of BIM is generally recognized in the construction industry, but the practical application of BIM for management purposes is, however, still limited among contractors. The objective of this study is to review the current scheduling process of construction in light of BIM...... and communicate. Scheduling on the detailed level, on the other hand, follows a stipulated approach to scheduling, i.e. the Last Planner System (LPS), which is characterized by involvement of all actors in the construction phase. Thus, the major challenge when implementing BIM-based scheduling is to improve...

  19. PLACEMENT APPLICATIONS SCHEDULING LECTURE IN INTERNATIONAL PROGRAM UNIKOM BASED ANDROID

    Directory of Open Access Journals (Sweden)

    Andri Sahata Sitanggang

    2017-12-01

    Full Text Available One who determines life of a classroom namely mapping scheduling courses especially at college. The process scheduling has included time or schedule of a class of available, room available, lecture who is scheduled for, and schedule for lecturer going to teach. Hopefully with a scheduling it will facilitate the students and teachers in obtaining information lecture schedule. With the emergence of the android application ( is implanted in mobile phones , the public can now use the internet so fast that is based .So with that researchers give one a technology based solutions to build android application .This is because one of the technology has given the functions which may make it easier for students and university lecturers in terms of access to information. In building this application used method of the prototype consisting 2 access namely access user and admin , where module user consisting of modules register , login , scheduling module , while for admin given module login , register and arrangement information scheduling courses both the administration and lecturers .Application made will be integrated with internet so that this program is real-time application.

  20. Simulation methods for nuclear production scheduling

    International Nuclear Information System (INIS)

    Miles, W.T.; Markel, L.C.

    1975-01-01

    Recent developments and applications of simulation methods for use in nuclear production scheduling and fuel management are reviewed. The unique characteristics of the nuclear fuel cycle as they relate to the overall optimization of a mixed nuclear-fossil system in both the short-and mid-range time frame are described. Emphasis is placed on the various formulations and approaches to the mid-range planning problem, whose objective is the determination of an optimal (least cost) system operation strategy over a multi-year planning horizon. The decomposition of the mid-range problem into power system simulation, reactor core simulation and nuclear fuel management optimization, and system integration models is discussed. Present utility practices, requirements, and research trends are described. 37 references

  1. National contingency plan product schedule data base

    International Nuclear Information System (INIS)

    Putukian, J.; Hiltabrand, R.R.

    1993-01-01

    During oil spills there are always proposals by the technical community and industry to use chemical agents to help in oil spill cleanups. Federal Clean Water Act regulations require that any chemical agents that the federal on-scene coordinator (FOSC) wants to use for oil cleanup be listed on the US Environmental Protection Agency (EPA) National Contingency Plan (NCP) Product Schedule. Chemical countermeasures are among the most controversial, complex, and time-critical issues facing decision-making officials choosing response methods to use on coastal oil spills. There are situations in which dispersants are likely to be one of the most appropriate counter-measure strategies. Dispersants are most effective when applied to fresh oil, and their effectiveness dramatically decreases as the oil weathers, which can begin in as little as 24 hours. To logistically implement dispersant use, a decision would need to be made within roughly the first 4 hours after the release. Most of the information that the FOSC needs to make the determination to use a specific chemical agent exists in manuals, EPA bulletins, and the published literature. This information is not in an easy-to-use format under field emergency conditions. Hence the need to collect and disseminate the information in an automated data base. The sources for the information in this data base are the following. Published results of tests performed by Environment Canada; EPA bulletins associated with the NCP Product Schedule; Published results of tests by the chemical industry. The data base resides on a Macintosh computer and contains information about 70 NCP products, including dispersants, surface collecting agents, and biological additives. It contains information on physical properties, toxicity, heavy metal content, safety precautions, use conditions, etc

  2. Segment scheduling method for reducing 360° video streaming latency

    Science.gov (United States)

    Gudumasu, Srinivas; Asbun, Eduardo; He, Yong; Ye, Yan

    2017-09-01

    360° video is an emerging new format in the media industry enabled by the growing availability of virtual reality devices. It provides the viewer a new sense of presence and immersion. Compared to conventional rectilinear video (2D or 3D), 360° video poses a new and difficult set of engineering challenges on video processing and delivery. Enabling comfortable and immersive user experience requires very high video quality and very low latency, while the large video file size poses a challenge to delivering 360° video in a quality manner at scale. Conventionally, 360° video represented in equirectangular or other projection formats can be encoded as a single standards-compliant bitstream using existing video codecs such as H.264/AVC or H.265/HEVC. Such method usually needs very high bandwidth to provide an immersive user experience. While at the client side, much of such high bandwidth and the computational power used to decode the video are wasted because the user only watches a small portion (i.e., viewport) of the entire picture. Viewport dependent 360°video processing and delivery approaches spend more bandwidth on the viewport than on non-viewports and are therefore able to reduce the overall transmission bandwidth. This paper proposes a dual buffer segment scheduling algorithm for viewport adaptive streaming methods to reduce latency when switching between high quality viewports in 360° video streaming. The approach decouples the scheduling of viewport segments and non-viewport segments to ensure the viewport segment requested matches the latest user head orientation. A base layer buffer stores all lower quality segments, and a viewport buffer stores high quality viewport segments corresponding to the most recent viewer's head orientation. The scheduling scheme determines viewport requesting time based on the buffer status and the head orientation. This paper also discusses how to deploy the proposed scheduling design for various viewport adaptive video

  3. Mid and long-term optimize scheduling of cascade hydro-power stations based on modified GA-POA method

    Directory of Open Access Journals (Sweden)

    J. Li

    2018-06-01

    Full Text Available In this paper, to explore the efficiency and rationality of the cascade combined generation, a cascade combined optimal model with the maximum generating capacity is established, and solving the model by the modified GA-POA method. It provides a useful reference for the joint development of cascade hydro-power stations in large river basins. The typical annual runoff data are selected to calculate the difference between the calculated results under different representative years. The results show that the cascade operation of cascaded hydro-power stations can significantly increase the overall power generation of cascade and ease the flood risk caused by concentration of flood season.

  4. Method and apparatus for scheduling broadcasts in social networks

    KAUST Repository

    Manzoor, Emaad Ahmed

    2016-08-25

    A method, apparatus, and computer readable medium are provided for maximizing consumption of broadcasts by a producer. An example method includes receiving selection of a total number of time slots to use for scheduling broadcasts, and receiving information regarding the producer\\'s followers. The example method further 5 includes identifying, by a processor and based on the received information, discount factors associated with the producer\\'s followers, and calculating, by the processor and based on the received information, a predicted number of competitor broadcasts during each time slot of the total number of time slots. Finally, the example method includes determining, by the processor and based on the discount factors and the predicted 10 number of competitor broadcasts during each time slot, a number of broadcasts for the producer to transmit in each time slot of the total number of time slots.

  5. Gain Scheduling of Observer-Based Controllers with Integral Action

    DEFF Research Database (Denmark)

    Trangbæk, Klaus; Stoustrup, Jakob; Bendtsen, Jan Dimon

    2006-01-01

     This paper presents a method for continuous gain scheduling of  observer-based controllers with integral action. Given two stabilising controllers for a given system, explicit state space formulae are presented, allowing to change gradually from one  controller to the other while preserving...

  6. A Monte-Carlo-Based Method for the Optimal Placement and Operation Scheduling of Sewer Mining Units in Urban Wastewater Networks

    Directory of Open Access Journals (Sweden)

    Eleftheria Psarrou

    2018-02-01

    Full Text Available Pressures on water resources, which have increased significantly nowadays mainly due to rapid urbanization, population growth and climate change impacts, necessitate the development of innovative wastewater treatment and reuse technologies. In this context, a mid-scale decentralized technology concerning wastewater reuse is that of sewer mining. It is based on extracting wastewater from a wastewater system, treating it on-site and producing recycled water applicable for non-potable uses. Despite the technology’s considerable benefits, several challenges hinder its implementation. Sewer mining disturbs biochemical processes inside sewers and affects hydrogen sulfide build-up, resulting in odor, corrosion and health-related problems. In this study, a tool for optimal sewer mining unit placement aiming to minimize hydrogen sulfide production is presented. The Monte-Carlo method coupled with the Environmental Protection Agency’s Storm Water Management Model (SWMM is used to conduct multiple simulations of the network. The network’s response when sewage is extracted from it is also examined. Additionally, the study deals with optimal pumping scheduling. The overall methodology is applied in a sewer network in Greece providing useful results. It can therefore assist in selecting appropriate locations for sewer mining implementation, with the focus on eliminating hydrogen sulfide-associated problems while simultaneously ensuring that higher water needs are satisfied.

  7. Consensus based scheduling of storage capacities in a virtual microgrid

    DEFF Research Database (Denmark)

    Brehm, Robert; Top, Søren; Mátéfi-Tempfli, Stefan

    2017-01-01

    We present a distributed, decentralized method for coordinated scheduling of charge/discharge intervals of storage capacities in a utility grid integrated microgrid. The decentralized algorithm is based on a consensus scheme and solves an optimisation problem with the objective of minimising......, by use of storage capacities, the power flow over a transformer substation from/to the utility grid integrated microgrid. It is shown that when using this coordinated scheduling algorithm, load profile flattening (peak-shaving) for the utility grid is achieved. Additionally, mutual charge...

  8. Research on logistics scheduling based on PSO

    Science.gov (United States)

    Bao, Huifang; Zhou, Linli; Liu, Lei

    2017-08-01

    With the rapid development of e-commerce based on the network, the logistics distribution support of e-commerce is becoming more and more obvious. The optimization of vehicle distribution routing can improve the economic benefit and realize the scientific of logistics [1]. Therefore, the study of logistics distribution vehicle routing optimization problem is not only of great theoretical significance, but also of considerable value of value. Particle swarm optimization algorithm is a kind of evolutionary algorithm, which is based on the random solution and the optimal solution by iteration, and the quality of the solution is evaluated through fitness. In order to obtain a more ideal logistics scheduling scheme, this paper proposes a logistics model based on particle swarm optimization algorithm.

  9. Heuristic Method for Decision-Making in Common Scheduling Problems

    Directory of Open Access Journals (Sweden)

    Edyta Kucharska

    2017-10-01

    Full Text Available The aim of the paper is to present a heuristic method for decision-making regarding an NP-hard scheduling problem with limitations related to tasks and the resources dependent on the current state of the process. The presented approach is based on the algebraic-logical meta-model (ALMM, which enables making collective decisions in successive process stages, not separately for individual objects or executors. Moreover, taking into account the limitations of the problem, it involves constructing only an acceptable solution and significantly reduces the amount of calculations. A general algorithm based on the presented method is composed of the following elements: preliminary analysis of the problem, techniques for the choice of decision at a given state, the pruning non-perspective trajectory, selection technique of the initial state for the trajectory final part, and the trajectory generation parameters modification. The paper includes applications of the presented approach to scheduling problems on unrelated parallel machines with a deadline and machine setup time dependent on the process state, where the relationship between tasks is defined by the graph. The article also presents the results of computational experiments.

  10. Heuristic algorithm for single resource constrained project scheduling problem based on the dynamic programming

    Directory of Open Access Journals (Sweden)

    Stanimirović Ivan

    2009-01-01

    Full Text Available We introduce a heuristic method for the single resource constrained project scheduling problem, based on the dynamic programming solution of the knapsack problem. This method schedules projects with one type of resources, in the non-preemptive case: once started an activity is not interrupted and runs to completion. We compare the implementation of this method with well-known heuristic scheduling method, called Minimum Slack First (known also as Gray-Kidd algorithm, as well as with Microsoft Project.

  11. A meta-heuristic method for solving scheduling problem: crow search algorithm

    Science.gov (United States)

    Adhi, Antono; Santosa, Budi; Siswanto, Nurhadi

    2018-04-01

    Scheduling is one of the most important processes in an industry both in manufacturingand services. The scheduling process is the process of selecting resources to perform an operation on tasks. Resources can be machines, peoples, tasks, jobs or operations.. The selection of optimum sequence of jobs from a permutation is an essential issue in every research in scheduling problem. Optimum sequence becomes optimum solution to resolve scheduling problem. Scheduling problem becomes NP-hard problem since the number of job in the sequence is more than normal number can be processed by exact algorithm. In order to obtain optimum results, it needs a method with capability to solve complex scheduling problems in an acceptable time. Meta-heuristic is a method usually used to solve scheduling problem. The recently published method called Crow Search Algorithm (CSA) is adopted in this research to solve scheduling problem. CSA is an evolutionary meta-heuristic method which is based on the behavior in flocks of crow. The calculation result of CSA for solving scheduling problem is compared with other algorithms. From the comparison, it is found that CSA has better performance in term of optimum solution and time calculation than other algorithms.

  12. Topology-based hierarchical scheduling using deficit round robin

    DEFF Research Database (Denmark)

    Yu, Hao; Yan, Ying; Berger, Michael Stubert

    2009-01-01

    according to the topology. The mapping process could be completed through the network management plane or by manual configuration. Based on the knowledge of the network, the scheduler can manage the traffic on behalf of other less advanced nodes, avoid potential traffic congestion, and provide flow...... protection and isolation. Comparisons between hierarchical scheduling, flow-based scheduling, and class-based scheduling schemes have been carried out under a symmetric tree topology. Results have shown that the hierarchical scheduling scheme provides better flow protection and isolation from attack...

  13. Agent-based scheduling for aircraft deicing

    NARCIS (Netherlands)

    Mao, X.; Ter Mors, A.W.; Roos, N.; Witteveen, C.

    2006-01-01

    The planning and scheduling of the deicing and anti-icing activities is an important and challenging part of airport departure planning. Deicing planning has to be done in a highly dynamic environment involving several autonomous and self-interested parties. Traditional centralized scheduling

  14. An EV Charging Scheduling Mechanism Based on Price Negotiation

    Directory of Open Access Journals (Sweden)

    Baocheng Wang

    2018-05-01

    Full Text Available Scheduling EV user’s charging behavior based on charging price and applying renewable energy resources are the effective methods to release the load pressure of power grids brought about by the large-scale popularity of electric vehicles (EVs. This paper presents a novel approach for EV charging scheduling based on price negotiation. Firstly, the EV charging system framework based on price negotiation and renewable energy resources is discussed. Secondly, the price negotiation model is presented, including the initial price models and the conditions of transactions. Finally, an EV charging scheduling mechanism based on price negotiation (CSM-PN, including the price adjustment strategies of both the operator and EV users is proposed to seek a final transaction during multi-round price negotiation. Simulation results show that this novel approach can effectively improve the charging station operator’s income, reduce the EV users’ costs, and balance the load of the power grid while improving the efficiency of the EV charging system.

  15. Tramp Ship Routing and Scheduling - Models, Methods and Opportunities

    DEFF Research Database (Denmark)

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

    of their demand in advance. However, the detailed requirements of these contract cargoes can be subject to ongoing changes, e.g. the destination port can be altered. For tramp operators, a main concern is therefore the efficient and continuous planning of routes and schedules for the individual ships. Due...... and scheduling problem, focus should now be on extending this basic problem to include additional real-world complexities and develop suitable solution methods for those extensions. Such extensions will enable more tramp operators to benefit from the solution methods while simultaneously creating new...

  16. Tree Canopy Light Interception Estimates in Almond and a Walnut Orchards Using Ground, Low Flying Aircraft, and Satellite Based Methods to Improve Irrigation Scheduling Programs

    Science.gov (United States)

    Rosecrance, Richard C.; Johnson, Lee; Soderstrom, Dominic

    2016-01-01

    Canopy light interception is a main driver of water use and crop yield in almond and walnut production. Fractional green canopy cover (Fc) is a good indicator of light interception and can be estimated remotely from satellite using the normalized difference vegetation index (NDVI) data. Satellite-based Fc estimates could be used to inform crop evapotranspiration models, and hence support improvements in irrigation evaluation and management capabilities. Satellite estimates of Fc in almond and walnut orchards, however, need to be verified before incorporating them into irrigation scheduling or other crop water management programs. In this study, Landsat-based NDVI and Fc from NASA's Satellite Irrigation Management Support (SIMS) were compared with four estimates of canopy cover: 1. light bar measurement, 2. in-situ and image-based dimensional tree-crown analyses, 3. high-resolution NDVI data from low flying aircraft, and 4. orchard photos obtained via Google Earth and processed by an Image J thresholding routine. Correlations between the various estimates are discussed.

  17. Development of an irrigation scheduling software based on model predicted crop water stress

    Science.gov (United States)

    Modern irrigation scheduling methods are generally based on sensor-monitored soil moisture regimes rather than crop water stress which is difficult to measure in real-time, but can be computed using agricultural system models. In this study, an irrigation scheduling software based on RZWQM2 model pr...

  18. Bumpless Transfer between Observer-based Gain Scheduled Controllers

    DEFF Research Database (Denmark)

    Bendtsen, Jan Dimon; Stoustrup, Jakob; Trangbæk, Klaus

    2005-01-01

    This paper deals with bumpless transfer between a number of observer-based controllers in a gain scheduling architecture. Linear observer-based controllers are designed for a number of linear approximations of a nonlinear system in a set of operating points, and gain scheduling control can...

  19. Agent-based transportation planning compared with scheduling heuristics

    NARCIS (Netherlands)

    Mes, Martijn R.K.; van der Heijden, Matthijs C.; van Harten, Aart

    2004-01-01

    Here we consider the problem of dynamically assigning vehicles to transportation orders that have di¤erent time windows and should be handled in real time. We introduce a new agent-based system for the planning and scheduling of these transportation networks. Intelligent vehicle agents schedule

  20. Weighted-SNR-based fair scheduling for uplink OFDMA

    KAUST Repository

    Ma, Yao; Leith, Alex; Alouini, Mohamed-Slim; (Sherman) Shen X., Xuemin

    2009-01-01

    rates for different users. The offline optimization technique requires to know the channel distribution information (CDI) at the scheduler. The online method uses the weight adaption combined with individual user rate tracking, which avoids the need

  1. Project Scheduling Based on Risk of Gas Transmission Pipe

    Science.gov (United States)

    Silvianita; Nurbaity, A.; Mulyadi, Y.; Suntoyo; Chamelia, D. M.

    2018-03-01

    The planning of a project has a time limit on which must be completed before or right at a predetermined time. Thus, in a project planning, it is necessary to have scheduling management that is useful for completing a project to achieve maximum results by considering the constraints that will exists. Scheduling management is undertaken to deal with uncertainties and negative impacts of time and cost in project completion. This paper explains about scheduling management in gas transmission pipeline project Gresik-Semarang to find out which scheduling plan is most effectively used in accordance with its risk value. Scheduling management in this paper is assissted by Microsoft Project software to find the critical path of existing project scheduling planning data. Critical path is the longest scheduling path with the fastest completion time. The result is found a critical path on project scheduling with completion time is 152 days. Furthermore, the calculation of risk is done by using House of Risk (HOR) method and it is found that the critical path has a share of 40.98 percent of all causes of the occurence of risk events that will be experienced.

  2. Cloud Computing Task Scheduling Based on Cultural Genetic Algorithm

    Directory of Open Access Journals (Sweden)

    Li Jian-Wen

    2016-01-01

    Full Text Available The task scheduling strategy based on cultural genetic algorithm(CGA is proposed in order to improve the efficiency of task scheduling in the cloud computing platform, which targets at minimizing the total time and cost of task scheduling. The improved genetic algorithm is used to construct the main population space and knowledge space under cultural framework which get independent parallel evolution, forming a mechanism of mutual promotion to dispatch the cloud task. Simultaneously, in order to prevent the defects of the genetic algorithm which is easy to fall into local optimum, the non-uniform mutation operator is introduced to improve the search performance of the algorithm. The experimental results show that CGA reduces the total time and lowers the cost of the scheduling, which is an effective algorithm for the cloud task scheduling.

  3. Adaptive Cost-Based Task Scheduling in Cloud Environment

    Directory of Open Access Journals (Sweden)

    Mohammed A. S. Mosleh

    2016-01-01

    Full Text Available Task execution in cloud computing requires obtaining stored data from remote data centers. Though this storage process reduces the memory constraints of the user’s computer, the time deadline is a serious concern. In this paper, Adaptive Cost-based Task Scheduling (ACTS is proposed to provide data access to the virtual machines (VMs within the deadline without increasing the cost. ACTS considers the data access completion time for selecting the cost effective path to access the data. To allocate data access paths, the data access completion time is computed by considering the mean and variance of the network service time and the arrival rate of network input/output requests. Then the task priority is assigned to the removed tasks based data access time. Finally, the cost of data paths are analyzed and allocated based on the task priority. Minimum cost path is allocated to the low priority tasks and fast access path are allocated to high priority tasks as to meet the time deadline. Thus efficient task scheduling can be achieved by using ACTS. The experimental results conducted in terms of execution time, computation cost, communication cost, bandwidth, and CPU utilization prove that the proposed algorithm provides better performance than the state-of-the-art methods.

  4. Excel-based scheduling for reallocation of nursing staff.

    Science.gov (United States)

    2016-10-19

    Outi Annelli Tuominen and colleagues write in Nursing Management about the use of an Excel-based scheduling system for reallocation of nursing staff, which was trialled on ward managers and assistant ward managers.

  5. Refinery scheduling

    Energy Technology Data Exchange (ETDEWEB)

    Magalhaes, Marcus V.; Fraga, Eder T. [PETROBRAS, Rio de Janeiro, RJ (Brazil); Shah, Nilay [Imperial College, London (United Kingdom)

    2004-07-01

    This work addresses the refinery scheduling problem using mathematical programming techniques. The solution adopted was to decompose the entire refinery model into a crude oil scheduling and a product scheduling problem. The envelope for the crude oil scheduling problem is composed of a terminal, a pipeline and the crude area of a refinery, including the crude distillation units. The solution method adopted includes a decomposition technique based on the topology of the system. The envelope for the product scheduling comprises all tanks, process units and products found in a refinery. Once crude scheduling decisions are Also available the product scheduling is solved using a rolling horizon algorithm. All models were tested with real data from PETROBRAS' REFAP refinery, located in Canoas, Southern Brazil. (author)

  6. DLTAP: A Network-efficient Scheduling Method for Distributed Deep Learning Workload in Containerized Cluster Environment

    Directory of Open Access Journals (Sweden)

    Qiao Wei

    2017-01-01

    Full Text Available Deep neural networks (DNNs have recently yielded strong results on a range of applications. Training these DNNs using a cluster of commodity machines is a promising approach since training is time consuming and compute-intensive. Furthermore, putting DNN tasks into containers of clusters would enable broader and easier deployment of DNN-based algorithms. Toward this end, this paper addresses the problem of scheduling DNN tasks in the containerized cluster environment. Efficiently scheduling data-parallel computation jobs like DNN over containerized clusters is critical for job performance, system throughput, and resource utilization. It becomes even more challenging with the complex workloads. We propose a scheduling method called Deep Learning Task Allocation Priority (DLTAP which performs scheduling decisions in a distributed manner, and each of scheduling decisions takes aggregation degree of parameter sever task and worker task into account, in particularly, to reduce cross-node network transmission traffic and, correspondingly, decrease the DNN training time. We evaluate the DLTAP scheduling method using a state-of-the-art distributed DNN training framework on 3 benchmarks. The results show that the proposed method can averagely reduce 12% cross-node network traffic, and decrease the DNN training time even with the cluster of low-end servers.

  7. A New Method Based on Simulation-Optimization Approach to Find Optimal Solution in Dynamic Job-shop Scheduling Problem with Breakdown and Rework

    Directory of Open Access Journals (Sweden)

    Farzad Amirkhani

    2017-03-01

    The proposed method is implemented on classical job-shop problems with objective of makespan and results are compared with mixed integer programming model. Moreover, the appropriate dispatching priorities are achieved for dynamic job-shop problem minimizing a multi-objective criteria. The results show that simulation-based optimization are highly capable to capture the main characteristics of the shop and produce optimal/near-optimal solutions with highly credibility degree.

  8. Cbs (Contrastrain Based Schedulling Adalah Faktor Penentu Keberhasilan Perusahanan Printing

    Directory of Open Access Journals (Sweden)

    Hendra Achmadi

    2010-06-01

    Full Text Available In a highly competitive industry faces today ranging from small or home-based printing to using machine that can print offset a hundred thousand copies per hour. But, the increasing competition resulted in requiring a faster production time from order entry, print proff until the production process to delivery to customers. Often times in case of orders which will result in the concurrent PPIC will experience vertigo in the setting of production schedules which have concurrent delivery time. Often will end up with no receipt of orders due to difficulties in the production schedule, especially if the orders require the same offset machine and cylinder wear the same length, while the number of cylinders is limited. Therefore, the printing company should be able to do so in the conduct of a penetration timing of production can easily be simulated and implemented on the ground. CBS (Base Constraint scheduling is a technique to do the scheduling of production so that production can be carried out smoothly and quickly that fulfill the promise made to customers. In scheduling, there are several techniques that can be used are: FCFS (First Came First Serve, EDD (Earliest Date, and LCLS (Last Came Last Serve. So, it is required to be able to do way better scheduling to get results quickly in this fast changing schedules.

  9. A Method of Flow-Shop Re-Scheduling Dealing with Variation of Productive Capacity

    Directory of Open Access Journals (Sweden)

    Kenzo KURIHARA

    2005-02-01

    Full Text Available We can make optimum scheduling results using various methods that are proposed by many researchers. However, it is very difficult to process the works on time without delaying the schedule. There are two major causes that disturb the planned optimum schedules; they are (1the variation of productive capacity, and (2the variation of products' quantities themselves. In this paper, we deal with the former variation, or productive capacities, at flow-shop works. When production machines in a shop go out of order at flow-shops, we cannot continue to operate the productions and we have to stop the production line. To the contrary, we can continue to operate the shops even if some workers absent themselves. Of course, in this case, the production capacities become lower, because workers need to move from a machine to another to overcome the shortage of workers and some shops cannot be operated because of the worker shortage. We developed a new re-scheduling method based on Branch-and Bound method. We proposed an equation for calculating the lower bound for our Branch-and Bound method in a practical time. Some evaluation experiments are done using practical data of real flow-shop works. We compared our results with those of another simple scheduling method, and we confirmed the total production time of our result is shorter than that of another method by 4%.

  10. Multiprocessor Global Scheduling on Frame-Based DVFS Systems

    OpenAIRE

    Berten, Vandy; Goossens, Joël

    2008-01-01

    International audience; In this work, we are interested in multiprocessor energy efficient systems where task durations are not known in advance but are known stochastically. More precisely we consider global scheduling algorithms for frame-based multiprocessor stochastic DVFS (Dynamic Voltage and Frequency Scaling) systems. Moreover we consider processors with a discrete set of available frequencies. We provide a global scheduling algorithm, and formally show that no deadline will ever be mi...

  11. Aging based maintenance and reinvestment scheduling of electric distribution

    Energy Technology Data Exchange (ETDEWEB)

    Korpijarvi, J.

    2012-07-01

    The maintenance of electric distribution network is a topical question for distribution system operators because of increasing significance of failure costs. In this dissertation the maintenance practices of the distribution system operators are analyzed and a theory for scheduling maintenance activities and reinvestment of distribution components is created. The scheduling is based on the deterioration of components and the increasing failure rates due to aging. The dynamic programming algorithm is used as a solving method to maintenance problem which is caused by the increasing failure rates of the network. The other impacts of network maintenance like environmental and regulation reasons are not included to the scope of this thesis. Further the tree trimming of the corridors and the major disturbance of the network are not included to the problem optimized in this thesis. For optimizing, four dynamic programming models are presented and the models are tested. Programming is made in VBA-language to the computer. For testing two different kinds of test networks are used. Because electric distribution system operators want to operate with bigger component groups, optimal timing for component groups is also analyzed. A maintenance software package is created to apply the presented theories in practice. An overview of the program is presented (orig.)

  12. Analysis of Issues for Project Scheduling by Multiple, Dispersed Schedulers (distributed Scheduling) and Requirements for Manual Protocols and Computer-based Support

    Science.gov (United States)

    Richards, Stephen F.

    1991-01-01

    Although computerized operations have significant gains realized in many areas, one area, scheduling, has enjoyed few benefits from automation. The traditional methods of industrial engineering and operations research have not proven robust enough to handle the complexities associated with the scheduling of realistic problems. To address this need, NASA has developed the computer-aided scheduling system (COMPASS), a sophisticated, interactive scheduling tool that is in wide-spread use within NASA and the contractor community. Therefore, COMPASS provides no explicit support for the large class of problems in which several people, perhaps at various locations, build separate schedules that share a common pool of resources. This research examines the issue of distributing scheduling, as applied to application domains characterized by the partial ordering of tasks, limited resources, and time restrictions. The focus of this research is on identifying issues related to distributed scheduling, locating applicable problem domains within NASA, and suggesting areas for ongoing research. The issues that this research identifies are goals, rescheduling requirements, database support, the need for communication and coordination among individual schedulers, the potential for expert system support for scheduling, and the possibility of integrating artificially intelligent schedulers into a network of human schedulers.

  13. Microcomputer-based workforce scheduling for hospital porters.

    Science.gov (United States)

    Lin, C K

    1999-01-01

    This paper focuses on labour scheduling for hospital porters who are the major workforce providing routine cleansing of wards, transportation and messenger services. Generating an equitable monthly roster for porters while meeting the daily minimum demand is a tedious task scheduled manually by a supervisor. In considering a variety of constraints and goals, a manual schedule was usually produced in seven to ten days. To be in line with the strategic goal of scientific management of an acute care regional hospital in Hong Kong, a microcomputer-based algorithm was developed to schedule the monthly roster. The algorithm, coded in Digital Visual Fortran 5.0 Professional, could generate a monthly roster in seconds. Implementation has been carried out since September 1998 and the results proved to be useful to hospital administrators and porters. This paper discusses both the technical and human issues involved during the computerization process.

  14. Application of linear scheduling method (LSM) for nuclear power plant (NPP) construction

    International Nuclear Information System (INIS)

    Kim, Woojoong; Ryu, Dongsoo; Jung, Youngsoo

    2014-01-01

    Highlights: • Mixed use of linear scheduling method with traditional CPM is suggested for NPP. • A methodology for selecting promising areas for LSM application is proposed. • A case-study is conducted to validate the proposed LSM selection methodology. • A case-study of reducing NPP construction duration by using LSM is introduced. - Abstract: According to a forecast, global energy demand is expected to increase by 56% from 2010 to 2040 (EIA, 2013). The nuclear power plant construction market is also growing with sharper competition. In nuclear power plant construction, scheduling is one of the most important functions due to its large size and complexity. Therefore, it is crucial to incorporate the ‘distinct characteristics of construction commodities and the complex characteristics of scheduling techniques’ (Jung and Woo, 2004) when selecting appropriate schedule control methods for nuclear power plant construction. However, among various types of construction scheduling techniques, the traditional critical path method (CPM) has been used most frequently in real-world practice. In this context, the purpose of this paper is to examine the viability and effectiveness of linear scheduling method (LSM) applications for specific areas in nuclear power plant construction. In order to identify the criteria for selecting scheduling techniques, the characteristics of CPM and LSM were compared and analyzed first through a literature review. Distinct characteristics of nuclear power plant construction were then explored by using a case project in order to develop a methodology to select effective areas of LSM application to nuclear power plant construction. Finally, promising areas for actual LSM application are suggested based on the proposed evaluation criteria and the case project. Findings and practical implications are discussed for further implementation

  15. Application of linear scheduling method (LSM) for nuclear power plant (NPP) construction

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Woojoong, E-mail: minidung@nate.com [Central Research Institute, Korea Hydro and Nuclear Power Co., Ltd, Daejeon 305-343 (Korea, Republic of); Ryu, Dongsoo, E-mail: energyboy@khnp.co.kr [Central Research Institute, Korea Hydro and Nuclear Power Co., Ltd, Daejeon 305-343 (Korea, Republic of); Jung, Youngsoo, E-mail: yjung97@mju.ac.kr [College of Architecture, Myongji University, Yongin 449-728 (Korea, Republic of)

    2014-04-01

    Highlights: • Mixed use of linear scheduling method with traditional CPM is suggested for NPP. • A methodology for selecting promising areas for LSM application is proposed. • A case-study is conducted to validate the proposed LSM selection methodology. • A case-study of reducing NPP construction duration by using LSM is introduced. - Abstract: According to a forecast, global energy demand is expected to increase by 56% from 2010 to 2040 (EIA, 2013). The nuclear power plant construction market is also growing with sharper competition. In nuclear power plant construction, scheduling is one of the most important functions due to its large size and complexity. Therefore, it is crucial to incorporate the ‘distinct characteristics of construction commodities and the complex characteristics of scheduling techniques’ (Jung and Woo, 2004) when selecting appropriate schedule control methods for nuclear power plant construction. However, among various types of construction scheduling techniques, the traditional critical path method (CPM) has been used most frequently in real-world practice. In this context, the purpose of this paper is to examine the viability and effectiveness of linear scheduling method (LSM) applications for specific areas in nuclear power plant construction. In order to identify the criteria for selecting scheduling techniques, the characteristics of CPM and LSM were compared and analyzed first through a literature review. Distinct characteristics of nuclear power plant construction were then explored by using a case project in order to develop a methodology to select effective areas of LSM application to nuclear power plant construction. Finally, promising areas for actual LSM application are suggested based on the proposed evaluation criteria and the case project. Findings and practical implications are discussed for further implementation.

  16. A Hybrid Node Scheduling Approach Based on Energy Efficient Chain Routing for WSN

    Directory of Open Access Journals (Sweden)

    Yimei Kang

    2014-04-01

    Full Text Available Energy efficiency is usually a significant goal in wireless sensor networks (WSNs. In this work, an energy efficient chain (EEC data routing approach is first presented. The coverage and connectivity of WSNs are discussed based on EEC. A hybrid node scheduling approach is then proposed. It includes sleep scheduling for cyclically monitoring regions of interest in time-driven modes and wakeup scheduling for tracking emergency events in event-driven modes. A failure rate is introduced to the sleep scheduling to improve the reliability of the system. A wakeup sensor threshold and a sleep time threshold are introduced in the wakeup scheduling to reduce the consumption of energy to the possible extent. The results of the simulation show that the proposed algorithm can extend the effective lifetime of the network to twice that of PEAS. In addition, the proposed methods are computing efficient because they are very simple to implement.

  17. A Market-Based Approach to Multi-factory Scheduling

    Science.gov (United States)

    Vytelingum, Perukrishnen; Rogers, Alex; MacBeth, Douglas K.; Dutta, Partha; Stranjak, Armin; Jennings, Nicholas R.

    In this paper, we report on the design of a novel market-based approach for decentralised scheduling across multiple factories. Specifically, because of the limitations of scheduling in a centralised manner - which requires a center to have complete and perfect information for optimality and the truthful revelation of potentially commercially private preferences to that center - we advocate an informationally decentralised approach that is both agile and dynamic. In particular, this work adopts a market-based approach for decentralised scheduling by considering the different stakeholders representing different factories as self-interested, profit-motivated economic agents that trade resources for the scheduling of jobs. The overall schedule of these jobs is then an emergent behaviour of the strategic interaction of these trading agents bidding for resources in a market based on limited information and their own preferences. Using a simple (zero-intelligence) bidding strategy, we empirically demonstrate that our market-based approach achieves a lower bound efficiency of 84%. This represents a trade-off between a reasonable level of efficiency (compared to a centralised approach) and the desirable benefits of a decentralised solution.

  18. Opportunistic splitting for scheduling using a score-based approach

    KAUST Repository

    Rashid, Faraan

    2012-06-01

    We consider the problem of scheduling a user in a multi-user wireless environment in a distributed manner. The opportunistic splitting algorithm is applied to find the best group of users without reporting the channel state information to the centralized scheduler. The users find the best among themselves while requiring just a ternary feedback from the common receiver at the end of each mini-slot. The original splitting algorithm is modified to handle users with asymmetric channel conditions. We use a score-based approach with the splitting algorithm to introduce time and throughput fairness while exploiting the multi-user diversity of the network. Analytical and simulation results are given to show that the modified score-based splitting algorithm works well as a fair scheduling scheme with good spectral efficiency and reduced feedback. © 2012 IEEE.

  19. Performance Evaluation of Bidding-Based Multi-Agent Scheduling Algorithms for Manufacturing Systems

    Directory of Open Access Journals (Sweden)

    Antonio Gordillo

    2014-10-01

    Full Text Available Artificial Intelligence techniques have being applied to many problems in manufacturing systems in recent years. In the specific field of manufacturing scheduling many studies have been published trying to cope with the complexity of the manufacturing environment. One of the most utilized approaches is (multi agent-based scheduling. Nevertheless, despite the large list of studies reported in this field, there is no resource or scientific study on the performance measure of this type of approach under very common and critical execution situations. This paper focuses on multi-agent systems (MAS based algorithms for task allocation, particularly in manufacturing applications. The goal is to provide a mechanism to measure the performance of agent-based scheduling approaches for manufacturing systems under key critical situations such as: dynamic environment, rescheduling, and priority change. With this mechanism it will be possible to simulate critical situations and to stress the system in order to measure the performance of a given agent-based scheduling method. The proposed mechanism is a pioneering approach for performance evaluation of bidding-based MAS approaches for manufacturing scheduling. The proposed method and evaluation methodology can be used to run tests in different manufacturing floors since it is independent of the workshop configuration. Moreover, the evaluation results presented in this paper show the key factors and scenarios that most affect the market-like MAS approaches for manufacturing scheduling.

  20. Size-based scheduling to improve web performance

    NARCIS (Netherlands)

    Harchol-Balter, M.; Schroeder, B.; Bansal, N.; Agrawal, M.

    2003-01-01

    Is it possible to reduce the expected response time of every request at a web server, simply by changing the order in which we schedule the requests? That is the question we ask in this paper.This paper proposes a method for improving the performance of web servers servicing static HTTP requests.

  1. Gain Scheduling Control based on Closed-Loop System Identification

    DEFF Research Database (Denmark)

    Bendtsen, Jan Dimon; Trangbæk, Klaus

    the first and a second operating point is identified in closed-loop using system identification methods with open-loop properties. Next, a linear controller is designed for this linearised model, and gain scheduling control can subsequently be achieved by interpolating between each controller...

  2. Weighted-SNR-based fair scheduling for uplink OFDMA

    KAUST Repository

    Ma, Yao

    2009-11-01

    In this paper, we study the sum rate maximization algorithms with long-term proportional rate fairness (PRF) for uplink orthogonal frequency division multiple access (OFDMA) systems. In contrast to the rate-maximization schemes which used short-term PRF in the literature, we propose to use a selective multiuser diversity (SMuD) scheme to achieve a long-term PRF and improved sum rate performance. This scheme implements weighted channel signal-to-noise ratio (w-SNR)-based ranking for user selection on each subchannel, and then uses either water-filling (WF) or equal power allocation (EPA) along the assigned channels of each user. Both offline and online methods to find the optimal SNR weight factors are designed to achieve the target proportional rates for different users. The offline optimization technique requires to know the channel distribution information (CDI) at the scheduler. The online method uses the weight adaption combined with individual user rate tracking, which avoids the need to know the CDI. Analytical throughput metrics for the proposed w-SNR scheme with WF and EPA over Rayleigh channels are derived, and verified by simulations. Simulation results show that the proposed w-SNR PRF scheme can achieve significantly higher sum rates than the frequency diversity-based short-term and long-term fairness schemes. Besides the improved performance, the proposed schemes have a low complexity which is linear to numbers of users and subchannels.

  3. Deadline based scheduling for data-intensive applications in clouds

    Institute of Scientific and Technical Information of China (English)

    Fu Xiong; Cang Yeliang; Zhu Lipeng; Hu Bin; Deng Song; Wang Dong

    2016-01-01

    Cloud computing emerges as a new computing pattern that can provide elastic services for any users around the world.It provides good chances to solve large scale scientific problems with fewer efforts.Application deployment remains an important issue in clouds.Appropriate scheduling mechanisms can shorten the total completion time of an application and therefore improve the quality of service (QoS) for cloud users.Unlike current scheduling algorithms which mostly focus on single task allocation,we propose a deadline based scheduling approach for data-intensive applications in clouds.It does not simply consider the total completion time of an application as the sum of all its subtasks' completion time.Not only the computation capacity of virtual machine (VM) is considered,but also the communication delay and data access latencies are taken into account.Simulations show that our proposed approach has a decided advantage over the two other algorithms.

  4. Research and Applications of Shop Scheduling Based on Genetic Algorithms

    Directory of Open Access Journals (Sweden)

    Hang ZHAO

    Full Text Available ABSTRACT Shop Scheduling is an important factor affecting the efficiency of production, efficient scheduling method and a research and application for optimization technology play an important role for manufacturing enterprises to improve production efficiency, reduce production costs and many other aspects. Existing studies have shown that improved genetic algorithm has solved the limitations that existed in the genetic algorithm, the objective function is able to meet customers' needs for shop scheduling, and the future research should focus on the combination of genetic algorithm with other optimized algorithms. In this paper, in order to overcome the shortcomings of early convergence of genetic algorithm and resolve local minimization problem in search process,aiming at mixed flow shop scheduling problem, an improved cyclic search genetic algorithm is put forward, and chromosome coding method and corresponding operation are given.The operation has the nature of inheriting the optimal individual ofthe previous generation and is able to avoid the emergence of local minimum, and cyclic and crossover operation and mutation operation can enhance the diversity of the population and then quickly get the optimal individual, and the effectiveness of the algorithm is validated. Experimental results show that the improved algorithm can well avoid the emergency of local minimum and is rapid in convergence.

  5. Method and apparatus for scheduling broadcasts in social networks

    KAUST Repository

    Manzoor, Emaad Ahmed; Kalnis, Panos

    2016-01-01

    information regarding the producer's followers. The example method further 5 includes identifying, by a processor and based on the received information, discount factors associated with the producer's followers, and calculating, by the processor and based

  6. Innovative Production Scheduling with Customer Satisfaction Based Measurement for the Sustainability of Manufacturing Firms

    Directory of Open Access Journals (Sweden)

    Sang-Oh Shim

    2017-12-01

    Full Text Available Scheduling problems for the sustainability of manufacturing firms in the era of the fourth industrial revolution is addressed in this research. In terms of open innovation, innovative production scheduling can be defined as scheduling using big data, cyber-physical systems, internet of things, cloud computing, mobile network, and so on. In this environment, one of the most important things is to develop an innovative scheduling algorithm for the sustainability of manufacturing firms. In this research, a flexible flowshop scheduling problem is considered with the properties of sequence-dependent setup and different process plans for jobs. In a flexible flowshop, there are serial workstations with multiple pieces of equipment that are able to process multiple lots simultaneously. Since the scheduling in this workshop is known to be extremely difficult, it is important to devise an efficient and effective scheduling algorithm. In this research, a heuristic algorithm is proposed based on a few dispatching rules and economic lot size model with the objective of minimizing total tardiness of orders. For the purposes of performance evaluation, a simulation study is conducted on randomly generated problem instances. The results imply that our proposed method outperforms the existing ones, and greatly enhances the sustainability of manufacturing firms.

  7. THE DISCRETE TIME, COST AND QUALITY TRADE-OFF PROBLEM IN PROJECT SCHEDULING: AN EFFICIENT SOLUTION METHOD BASED ON CELLDE ALGORITHM

    Directory of Open Access Journals (Sweden)

    Gh. Assadipour

    2012-01-01

    Full Text Available

    ENGLISH ABSTRACT:The trade-off between time, cost, and quality is one of the important problems of project management. This problem assumes that all project activities can be executed in different modes of cost, time, and quality. Thus a manager should select each activity’s mode such that the project can meet the deadline with the minimum possible cost and the maximum achievable quality. As the problem is NP-hard and the objectives are in conflict with each other, a multi-objective meta-heuristic called CellDE, which is a hybrid cellular genetic algorithm, is implemented as the optimisation method. The proposed algorithm provides project managers with a set of non-dominated or Pareto-optimal solutions, and enables them to choose the best one according to their preferences. A set of problems of different sizes is generated and solved using the proposed algorithm. Three metrics are employed for evaluating the performance of the algorithm, appraising the diversity and convergence of the achieved Pareto fronts. Finally a comparison is made between CellDE and another meta-heuristic available in the literature. The results show the superiority of CellDE.

    AFRIKAANSE OPSOMMING: ‘n Balans tussen tyd, koste en gehalte is een van die belangrike probleme van projekbestuur. Die vraagstuk maak gewoonlik die aanname dat alle projekaktiwiteite uitgevoer kan word op uiteenlopende wyses wat verband hou met koste, tyd en gehalte. ‘n Projekbestuurder selekteer gewoonlik die uitvoeringsmetodes sodanig per aktiwiteit dat gehoor gegegee word aan minimum koste en maksimum gehalte teen die voorwaarde van voltooiingsdatum wat bereik moet word.

    Aangesien die beskrewe problem NP-hard is, word dit behandel ten opsigte van konflikterende doelwitte met ‘n multidoelwit metaheuristiese metode (CellDE. Die metode is ‘n hibride-sellulêre genetiese algoritme. Die algoritme lewer aan die besluitvormer ‘n versameling van ongedomineerde of Pareto

  8. Project Robust Scheduling Based on the Scattered Buffer Technology

    Directory of Open Access Journals (Sweden)

    Nansheng Pang

    2018-04-01

    Full Text Available The research object in this paper is the sub network formed by the predecessor’s affect on the solution activity. This paper is to study three types of influencing factors from the predecessors that lead to the delay of starting time of the solution activity on the longest path, and to analyze the influence degree on the delay of the solution activity’s starting time from different types of factors. On this basis, through the comprehensive analysis of various factors that influence the solution activity, this paper proposes a metric that is used to evaluate the solution robustness of the project scheduling, and this metric is taken as the optimization goal. This paper also adopts the iterative process to design a scattered buffer heuristics algorithm based on the robust scheduling of the time buffer. At the same time, the resource flow network is introduced in this algorithm, using the tabu search algorithm to solve baseline scheduling. For the generation of resource flow network in the baseline scheduling, this algorithm designs a resource allocation algorithm with the maximum use of the precedence relations. Finally, the algorithm proposed in this paper and some other algorithms in previous literature are taken into the simulation experiment; under the comparative analysis, the experimental results show that the algorithm proposed in this paper is reasonable and feasible.

  9. Hybrid IP/CP Methods for Solving Sports Scheduling Problems

    DEFF Research Database (Denmark)

    Rasmussen, Rasmus Vinther

    2006-01-01

    The field of sports scheduling comprises a challenging research areawith a great variety of hard combinatorial optimization problems andchallenging practical applications. This dissertation gives acomprehensive survey of the area and a number of new contributionsare presented. First a general sol...

  10. 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.

  11. 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.

  12. A preliminary analysis of the reactor-based plutonium disposition alternative deployment schedules

    International Nuclear Information System (INIS)

    Zurn, R.M.

    1997-09-01

    This paper discusses the preliminary analysis of the implementation schedules of the reactor-based plutonium disposition alternatives. These schedule analyses are a part of a larger process to examine the nine decision criteria used to determine the most appropriate method of disposing of U.S. surplus weapons plutonium. The preliminary analysis indicates that the mission durations for the reactor-based alternatives range from eleven years to eighteen years and the initial mission fuel assemblies containing surplus weapons-usable plutonium could be loaded into the reactors between nine and fourteen years after the Record of Decision

  13. Multisensors Cooperative Detection Task Scheduling Algorithm Based on Hybrid Task Decomposition and MBPSO

    Directory of Open Access Journals (Sweden)

    Changyun Liu

    2017-01-01

    Full Text Available A multisensor scheduling algorithm based on the hybrid task decomposition and modified binary particle swarm optimization (MBPSO is proposed. Firstly, aiming at the complex relationship between sensor resources and tasks, a hybrid task decomposition method is presented, and the resource scheduling problem is decomposed into subtasks; then the sensor resource scheduling problem is changed into the match problem of sensors and subtasks. Secondly, the resource match optimization model based on the sensor resources and tasks is established, which considers several factors, such as the target priority, detecting benefit, handover times, and resource load. Finally, MBPSO algorithm is proposed to solve the match optimization model effectively, which is based on the improved updating means of particle’s velocity and position through the doubt factor and modified Sigmoid function. The experimental results show that the proposed algorithm is better in terms of convergence velocity, searching capability, solution accuracy, and efficiency.

  14. Computer-based irrigation scheduling for cotton crop

    International Nuclear Information System (INIS)

    Laghari, K.Q.; Memon, H.M.

    2008-01-01

    In this study a real time irrigation schedule for cotton crop has been tested using mehran model, a computer-based DDS (Decision Support System). The irrigation schedule was set on selected MAD (Management Allowable Depletion) and the current root depth position. The total 451 mm irrigation water applied to the crop field. The seasonal computed crop ET (Evapotranspiration) was estimated 421.32 mm and actual (ET/sub ca/) observed was 413 mm. The model over-estimated seasonal ET by only 1.94. WUE (Water Use Efficiency) for seed-cotton achieved 6.59 Kg (ha mm)/sup -1/. The statistical analysis (R/sup 2/=0.96, ARE%=2.00, T-1.17 and F=550.57) showed good performance of the model in simulated and observed ET values. The designed Mehran model is designed quite versatile for irrigation scheduling and can be successfully used as irrigation DSS tool for various crop types. (author)

  15. Web-Based Requesting and Scheduling Use of Facilities

    Science.gov (United States)

    Yeager, Carolyn M.

    2010-01-01

    Automated User's Training Operations Facility Utilization Request (AutoFUR) is prototype software that administers a Web-based system for requesting and allocating facilities and equipment for astronaut-training classes in conjunction with scheduling the classes. AutoFUR also has potential for similar use in such applications as scheduling flight-simulation equipment and instructors in commercial airplane-pilot training, managing preventive- maintenance facilities, and scheduling operating rooms, doctors, nurses, and medical equipment for surgery. Whereas requesting and allocation of facilities was previously a manual process that entailed examination of documents (including paper drawings) from different sources, AutoFUR partly automates the process and makes all of the relevant information available via the requester s computer. By use of AutoFUR, an instructor can fill out a facility-utilization request (FUR) form on line, consult the applicable flight manifest(s) to determine what equipment is needed and where it should be placed in the training facility, reserve the corresponding hardware listed in a training-hardware inventory database, search for alternative hardware if necessary, submit the FUR for processing, and cause paper forms to be printed. Auto-FUR also maintains a searchable archive of prior FURs.

  16. Parallel Branch-and-Bound Methods for the Job Shop Scheduling

    DEFF Research Database (Denmark)

    Clausen, Jens; Perregaard, Michael

    1998-01-01

    Job-shop scheduling (JSS) problems are among the more difficult to solve in the class of NP-complete problems. The only successful approach has been branch-and-bound based algorithms, but such algorithms depend heavily on good bound functions. Much work has been done to identify such functions...... for the JSS problem, but with limited success. Even with recent methods, it is still not possible to solve problems substantially larger than 10 machines and 10 jobs. In the current study, we focus on parallel methods for solving JSS problems. We implement two different parallel branch-and-bound algorithms...

  17. A fast method for the unit scheduling problem with significant renewable power generation

    International Nuclear Information System (INIS)

    Osório, G.J.; Lujano-Rojas, J.M.; Matias, J.C.O.; Catalão, J.P.S.

    2015-01-01

    Highlights: • A model to the scheduling of power systems with significant renewable power generation is provided. • A new methodology that takes information from the analysis of each scenario separately is proposed. • Based on a probabilistic analysis, unit scheduling and corresponding economic dispatch are estimated. • A comparison with others methodologies is in favour of the proposed approach. - Abstract: Optimal operation of power systems with high integration of renewable power sources has become difficult as a consequence of the random nature of some sources like wind energy and photovoltaic energy. Nowadays, this problem is solved using Monte Carlo Simulation (MCS) approach, which allows considering important statistical characteristics of wind and solar power production such as the correlation between consecutive observations, the diurnal profile of the forecasted power production, and the forecasting error. However, MCS method requires the analysis of a representative amount of trials, which is an intensive calculation task that increases considerably with the number of scenarios considered. In this paper, a model to the scheduling of power systems with significant renewable power generation based on scenario generation/reduction method, which establishes a proportional relationship between the number of scenarios and the computational time required to analyse them, is proposed. The methodology takes information from the analysis of each scenario separately to determine the probabilistic behaviour of each generator at each hour in the scheduling problem. Then, considering a determined significance level, the units to be committed are selected and the load dispatch is determined. The proposed technique was illustrated through a case study and the comparison with stochastic programming approach was carried out, concluding that the proposed methodology can provide an acceptable solution in a reduced computational time

  18. An Effective Scheduling-Based RFID Reader Collision Avoidance Model and Its Resource Allocation via Artificial Immune Network

    OpenAIRE

    Wang, Shanjin; Li, Zhonghua; He, Chunhui; Li, Jianming

    2016-01-01

    Radio frequency identification, that is, RFID, is one of important technologies in Internet of Things. Reader collision does impair the tag identification efficiency of an RFID system. Many developed methods, for example, the scheduling-based series, that are used to avoid RFID reader collision, have been developed. For scheduling-based methods, communication resources, that is, time slots, channels, and power, are optimally assigned to readers. In this case, reader collision avoidance is equ...

  19. Real-Time Pricing-Based Scheduling Strategy in Smart Grids: A Hierarchical Game Approach

    Directory of Open Access Journals (Sweden)

    Jie Yang

    2014-01-01

    Full Text Available This paper proposes a scheduling strategy based on real-time pricing in smart grids. A hierarchical game is employed to analyze the decision-making process of generators and consumers. We prove the existence and uniqueness of Nash equilibrium and utilize a backward induction method to obtain the generation and consumption strategies. Then, we propose two dynamic algorithms for the generators and consumers to search for the equilibrium in a distributed fashion. Simulation results demonstrate that the proposed scheduling strategy can match supply with demand and shift load away from peak time.

  20. PERFORMANCE ANALYSIS OF AI BASED QOS SCHEDULER FOR MOBILE WIMAX

    Directory of Open Access Journals (Sweden)

    D. David Neels Pon Kumar

    2012-09-01

    Full Text Available Interest in broadband wireless access (BWA has been growing due to increased user mobility and the need for data access at all times. IEEE 802.16e based WiMAX networks promise the best available quality of experience for mobile data service users. WiMAX networks incorporate several Quality of Service (QoS mechanisms at the Media Access Control (MAC level for guaranteed services for multimedia viz. data, voice and video. The problem of assuring QoS is how to allocate available resources among users to meet the QoS criteria such as delay, delay jitter, fairness and throughput requirements. IEEE standard does not include a standard scheduling mechanism and leaves it for various implementer differentiations. Although a lot of the real-time and non real-time packet scheduling schemes has been proposed, it needs to be modified to apply to Mobile WiMAX system that supports five kinds of service classes. In this paper, we propose a novel Priority based Scheduling scheme that uses Artificial Intelligence to support various services by considering the QoS constraints of each class. The simulation results show that slow mobility does not affect the performances and faster mobility and the increment in users beyond a particular load have their say in defining average throughput, average per user throughput, fairness index, average end to end delay and average delay jitter. Nevertheless the results are encouraging that the proposed scheme provides QoS support for each class efficiently.

  1. Designing of Vague Logic Based 2-Layered Framework for CPU Scheduler

    Directory of Open Access Journals (Sweden)

    Supriya Raheja

    2016-01-01

    Full Text Available Fuzzy based CPU scheduler has become of great interest by operating system because of its ability to handle imprecise information associated with task. This paper introduces an extension to the fuzzy based round robin scheduler to a Vague Logic Based Round Robin (VBRR scheduler. VBRR scheduler works on 2-layered framework. At the first layer, scheduler has a vague inference system which has the ability to handle the impreciseness of task using vague logic. At the second layer, Vague Logic Based Round Robin (VBRR scheduling algorithm works to schedule the tasks. VBRR scheduler has the learning capability based on which scheduler adapts intelligently an optimum length for time quantum. An optimum time quantum reduces the overhead on scheduler by reducing the unnecessary context switches which lead to improve the overall performance of system. The work is simulated using MATLAB and compared with the conventional round robin scheduler and the other two fuzzy based approaches to CPU scheduler. Given simulation analysis and results prove the effectiveness and efficiency of VBRR scheduler.

  2. Cultural-Based Genetic Tabu Algorithm for Multiobjective Job Shop Scheduling

    Directory of Open Access Journals (Sweden)

    Yuzhen Yang

    2014-01-01

    Full Text Available The job shop scheduling problem, which has been dealt with by various traditional optimization methods over the decades, has proved to be an NP-hard problem and difficult in solving, especially in the multiobjective field. In this paper, we have proposed a novel quadspace cultural genetic tabu algorithm (QSCGTA to solve such problem. This algorithm provides a different structure from the original cultural algorithm in containing double brief spaces and population spaces. These spaces deal with different levels of populations globally and locally by applying genetic and tabu searches separately and exchange information regularly to make the process more effective towards promising areas, along with modified multiobjective domination and transform functions. Moreover, we have presented a bidirectional shifting for the decoding process of job shop scheduling. The computational results we presented significantly prove the effectiveness and efficiency of the cultural-based genetic tabu algorithm for the multiobjective job shop scheduling problem.

  3. Comparative study of heuristics algorithms in solving flexible job shop scheduling problem with condition based maintenance

    Directory of Open Access Journals (Sweden)

    Yahong Zheng

    2014-05-01

    Full Text Available Purpose: This paper focuses on a classic optimization problem in operations research, the flexible job shop scheduling problem (FJSP, to discuss the method to deal with uncertainty in a manufacturing system.Design/methodology/approach: In this paper, condition based maintenance (CBM, a kind of preventive maintenance, is suggested to reduce unavailability of machines. Different to the simultaneous scheduling algorithm (SSA used in the previous article (Neale & Cameron,1979, an inserting algorithm (IA is applied, in which firstly a pre-schedule is obtained through heuristic algorithm and then maintenance tasks are inserted into the pre-schedule scheme.Findings: It is encouraging that a new better solution for an instance in benchmark of FJSP is obtained in this research. Moreover, factually SSA used in literature for solving normal FJSPPM (FJSP with PM is not suitable for the dynamic FJSPPM. Through application in the benchmark of normal FJSPPM, it is found that although IA obtains inferior results compared to SSA used in literature, it performs much better in executing speed.Originality/value: Different to traditional scheduling of FJSP, uncertainty of machines is taken into account, which increases the complexity of the problem. An inserting algorithm (IA is proposed to solve the dynamic scheduling problem. It is stated that the quality of the final result depends much on the quality of the pre-schedule obtained during the procedure of solving a normal FJSP. In order to find the best solution of FJSP, a comparative study of three heuristics is carried out, the integrated GA, ACO and ABC. In the comparative study, we find that GA performs best in the three heuristic algorithms. Meanwhile, a new better solution for an instance in benchmark of FJSP is obtained in this research.

  4. A multi-group and preemptable scheduling of cloud resource based on HTCondor

    Science.gov (United States)

    Jiang, Xiaowei; Zou, Jiaheng; Cheng, Yaodong; Shi, Jingyan

    2017-10-01

    Due to the features of virtual machine-flexibility, easy controlling and various system environments, more and more fields utilize the virtualization technology to construct the distributed system with the virtual resources, also including high energy physics. This paper introduce a method used in high energy physics that supports multiple resource group and preemptable cloud resource scheduling, combining virtual machine with HTCondor (a batch system). It makes resource controlling more flexible and more efficient and makes resource scheduling independent of job scheduling. Firstly, the resources belong to different experiment-groups, and the type of user-groups mapping to resource-groups(same as experiment-group) is one-to-one or many-to-one. In order to make the confused group simply to be managed, we designed the permission controlling component to ensure that the different resource-groups can get the suitable jobs. Secondly, for the purpose of elastically allocating resources for suitable resource-group, it is necessary to schedule resources like scheduling jobs. So this paper designs the cloud resource scheduling to maintain a resource queue and allocate an appropriate amount of virtual resources to the request resource-group. Thirdly, in some kind of situations, because of the resource occupied for a long time, resources need to be preempted. This paper adds the preemption function for the resource scheduling that implement resource preemption based on the group priority. Additionally, the way to preempting is soft that when virtual resources are preempted, jobs will not be killed but also be held and rematched later. It is implemented with the help of HTCondor, storing the held job information in scheduler, releasing the job to idle status and doing second matcher. In IHEP (institute of high energy physics), we have built a batch system based on HTCondor with a virtual resources pool based on Openstack. And this paper will show some cases of experiment JUNO

  5. 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)

  6. Simulation-Based Dynamic Passenger Flow Assignment Modelling for a Schedule-Based Transit Network

    Directory of Open Access Journals (Sweden)

    Xiangming Yao

    2017-01-01

    Full Text Available The online operation management and the offline policy evaluation in complex transit networks require an effective dynamic traffic assignment (DTA method that can capture the temporal-spatial nature of traffic flows. The objective of this work is to propose a simulation-based dynamic passenger assignment framework and models for such applications in the context of schedule-based rail transit systems. In the simulation framework, travellers are regarded as individual agents who are able to obtain complete information on the current traffic conditions. A combined route selection model integrated with pretrip route selection and entrip route switch is established for achieving the dynamic network flow equilibrium status. The train agent is operated strictly with the timetable and its capacity limitation is considered. A continuous time-driven simulator based on the proposed framework and models is developed, whose performance is illustrated through a large-scale network of Beijing subway. The results indicate that more than 0.8 million individual passengers and thousands of trains can be simulated simultaneously at a speed ten times faster than real time. This study provides an efficient approach to analyze the dynamic demand-supply relationship for large schedule-based transit networks.

  7. Model-based development of a course of action scheduling tool

    DEFF Research Database (Denmark)

    Kristensen, Lars Michael; Mechlenborg, Peter; Zhang, Lin

    2008-01-01

    . The scheduling capabilities of COAST are based on state space exploration of the embedded CPN model. Planners interact with COAST using a domain-specific graphical user interface (GUI) that hides the embedded CPN model and analysis algorithms. This means that COAST is based on a rigorous semantical model......, but the use of formal methods is transparent to the users. Trials of operational planning using COAST have been conducted within the Australian Defence Force....

  8. Designing of vague logic based multilevel feedback queue scheduler

    Directory of Open Access Journals (Sweden)

    Supriya Raheja

    2016-03-01

    Full Text Available Multilevel feedback queue scheduler suffers from major issues of scheduling such as starvation for long tasks, fixed number of queues, and static length of time quantum in each queue. These factors directly affect the performance of the scheduler. At many times impreciseness exists in attributes of tasks which make the performance even worse. In this paper, our intent is to improve the performance by providing a solution to these issues. We design a multilevel feedback queue scheduler using a vague set which we call as VMLFQ scheduler. VMLFQ scheduler intelligently handles the impreciseness and defines the optimum number of queues as well as the optimal size of time quantum for each queue. It also resolves the problem of starvation. This paper simulates and analyzes the performance of VMLFQ scheduler with the other multilevel feedback queue techniques using MatLab.

  9. Exact methods for time constrained routing and related scheduling problems

    DEFF Research Database (Denmark)

    Kohl, Niklas

    1995-01-01

    of customers. In the VRPTW customers must be serviced within a given time period - a so called time window. The objective can be to minimize operating costs (e.g. distance travelled), fixed costs (e.g. the number of vehicles needed) or a combination of these component costs. During the last decade optimization......This dissertation presents a number of optimization methods for the Vehicle Routing Problem with Time Windows (VRPTW). The VRPTW is a generalization of the well known capacity constrained Vehicle Routing Problem (VRP), where a fleet of vehicles based at a central depot must service a set...... of J?rnsten, Madsen and S?rensen (1986), which has been tested computationally by Halse (1992). Both methods decompose the problem into a series of time and capacity constrained shotest path problems. This yields a tight lower bound on the optimal objective, and the dual gap can often be closed...

  10. Fog computing job scheduling optimization based on bees swarm

    Science.gov (United States)

    Bitam, Salim; Zeadally, Sherali; Mellouk, Abdelhamid

    2018-04-01

    Fog computing is a new computing architecture, composed of a set of near-user edge devices called fog nodes, which collaborate together in order to perform computational services such as running applications, storing an important amount of data, and transmitting messages. Fog computing extends cloud computing by deploying digital resources at the premise of mobile users. In this new paradigm, management and operating functions, such as job scheduling aim at providing high-performance, cost-effective services requested by mobile users and executed by fog nodes. We propose a new bio-inspired optimization approach called Bees Life Algorithm (BLA) aimed at addressing the job scheduling problem in the fog computing environment. Our proposed approach is based on the optimized distribution of a set of tasks among all the fog computing nodes. The objective is to find an optimal tradeoff between CPU execution time and allocated memory required by fog computing services established by mobile users. Our empirical performance evaluation results demonstrate that the proposal outperforms the traditional particle swarm optimization and genetic algorithm in terms of CPU execution time and allocated memory.

  11. A real-time Excel-based scheduling solution for nursing staff reallocation.

    Science.gov (United States)

    Tuominen, Outi Anneli; Lundgren-Laine, Heljä; Kauppila, Wiveka; Hupli, Maija; Salanterä, Sanna

    2016-09-30

    Aim This article describes the development and testing of an Excel-based scheduling solution for the flexible allocation and reallocation of nurses to cover sudden, unplanned absences among permanent nursing staff. Method A quasi-experimental, one group, pre- and post-test study design was used ( Box 1 ) with total sampling. Participants (n=17) were selected purposefully by including all ward managers (n=8) and assistant ward managers (n=9) from one university hospital department. The number of sudden absences among the nursing staff was identified during two 4-week data collection periods (pre- and post-test). Results During the use of the paper-based scheduling system, 121 absences were identified; during the use of the Excel-based system, 106 were identified. The main reasons for the use of flexible 'floating' nurses were sick leave (n=66) and workload (n=31). Other reasons (n=29) included patient transfer to another hospital, scheduling errors and the start or end of employment. Conclusion The Excel-based scheduling solution offered better support in obtaining substitute labour inside the organisation, with smaller employment costs. It also reduced the number of tasks ward managers had to carry out during the process of reallocating staff.

  12. Impact of interference on the performance of selection based parallel multiuser scheduling

    KAUST Repository

    Nam, Sungsik

    2012-02-01

    In conventional multiuser parallel scheduling schemes, every scheduled user is interfering with every other scheduled user, which limits the capacity and performance of multiuser systems, and the level of interference becomes substantial as the number of scheduled users increases. Based on the above observations, we investigate the trade-off between the system throughput and the number of scheduled users through the exact analysis of the total average sum rate capacity and the average spectral efficiency. Our analytical results can help the system designer to carefully select the appropriate number of scheduled users to maximize the overall throughput while maintaining an acceptable quality of service under certain channel conditions. © 2012 IEEE.

  13. Multiagent scheduling method with earliness and tardiness objectives in flexible job shops.

    Science.gov (United States)

    Wu, Zuobao; Weng, Michael X

    2005-04-01

    Flexible job-shop scheduling problems are an important extension of the classical job-shop scheduling problems and present additional complexity. Such problems are mainly due to the existence of a considerable amount of overlapping capacities with modern machines. Classical scheduling methods are generally incapable of addressing such capacity overlapping. We propose a multiagent scheduling method with job earliness and tardiness objectives in a flexible job-shop environment. The earliness and tardiness objectives are consistent with the just-in-time production philosophy which has attracted significant attention in both industry and academic community. A new job-routing and sequencing mechanism is proposed. In this mechanism, two kinds of jobs are defined to distinguish jobs with one operation left from jobs with more than one operation left. Different criteria are proposed to route these two kinds of jobs. Job sequencing enables to hold a job that may be completed too early. Two heuristic algorithms for job sequencing are developed to deal with these two kinds of jobs. The computational experiments show that the proposed multiagent scheduling method significantly outperforms the existing scheduling methods in the literature. In addition, the proposed method is quite fast. In fact, the simulation time to find a complete schedule with over 2000 jobs on ten machines is less than 1.5 min.

  14. A Gain-Scheduling PI Control Based on Neural Networks

    Directory of Open Access Journals (Sweden)

    Stefania Tronci

    2017-01-01

    Full Text Available This paper presents a gain-scheduling design technique that relies upon neural models to approximate plant behaviour. The controller design is based on generic model control (GMC formalisms and linearization of the neural model of the process. As a result, a PI controller action is obtained, where the gain depends on the state of the system and is adapted instantaneously on-line. The algorithm is tested on a nonisothermal continuous stirred tank reactor (CSTR, considering both single-input single-output (SISO and multi-input multi-output (MIMO control problems. Simulation results show that the proposed controller provides satisfactory performance during set-point changes and disturbance rejection.

  15. Project Scheduling Heuristics-Based Standard PSO for Task-Resource Assignment in Heterogeneous Grid

    OpenAIRE

    Chen, Ruey-Maw; Wang, Chuin-Mu

    2011-01-01

    The task scheduling problem has been widely studied for assigning resources to tasks in heterogeneous grid environment. Effective task scheduling is an important issue for the performance of grid computing. Meanwhile, the task scheduling problem is an NP-complete problem. Hence, this investigation introduces a named “standard“ particle swarm optimization (PSO) metaheuristic approach to efficiently solve the task scheduling problems in grid. Meanwhile, two promising heuristics based on multimo...

  16. 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.

  17. Hierarchical Scheduling Framework Based on Compositional Analysis Using Uppaal

    DEFF Research Database (Denmark)

    Boudjadar, Jalil; David, Alexandre; Kim, Jin Hyun

    2014-01-01

    This paper introduces a reconfigurable compositional scheduling framework, in which the hierarchical structure, the scheduling policies, the concrete task behavior and the shared resources can all be reconfigured. The behavior of each periodic preemptive task is given as a list of timed actions, ...

  18. Duality-based algorithms for scheduling on unrelated parallel machines

    NARCIS (Netherlands)

    van de Velde, S.L.; van de Velde, S.L.

    1993-01-01

    We consider the following parallel machine scheduling problem. Each of n independent jobs has to be scheduled on one of m unrelated parallel machines. The processing of job J[sub l] on machine Mi requires an uninterrupted period of positive length p[sub lj]. The objective is to find an assignment of

  19. The bases for optimisation of scheduled repairs and tests of safety systems to improve the NPP productive efficiency

    International Nuclear Information System (INIS)

    Bilej, D.V.; Vasil'chenko, S.V.; Vlasenko, N.I.; Vasil'chenko, V.N.; Skalozubov, V.I.

    2004-01-01

    In the frames of risk-informed approaches the paper proposed the theoretical bases for methods of optimisation of scheduled repairs and tests of safety systems at nuclear power plants. The optimisation criterion is the objective risk function minimising. This function depends on the scheduled repairs/tests periodicity and the allowed time to bring the system channel to a state of non-operability. The main optimisation direct is to reduce the repair time with the purpose of enhancement of productive efficiency

  20. The applicability of knowledge-based scheduling to the utilities industry

    International Nuclear Information System (INIS)

    Yoshimoto, G.; Gargan, R. Jr.; Duggan, P.

    1992-01-01

    The Electric Power Research Institute (EPRI), Nuclear Power Division, has identified the three major goals of high technology applications for nuclear power plants. These goals are to enhance power production through increasing power generation efficiency, to increase productivity of the operations, and to reduce the threats to the safety of the plant. Our project responds to the second goal by demonstrating that significant productivity increases can be achieved for outage maintenance operations based on existing knowledge-based scheduling technology. Its use can also mitigate threats to potential safety problems by means of the integration of risk assessment features into the scheduler. The scheduling approach uses advanced techniques enabling the automation of the routine scheduling decision process that previously was handled by people. The process of removing conflicts in scheduling is automated. This is achieved by providing activity representations that allow schedulers to express a variety of different scheduling constraints and by implementing scheduling mechanisms that simulate kinds of processes that humans use to find better solutions from a large number of possible solutions. This approach allows schedulers to express detailed constraints between activities and other activities, resources (material and personnel), and requirements that certain states exist for their execution. Our scheduler has already demonstrated its benefit to improving the shuttle processing flow management at Kennedy Space Center. Knowledge-based scheduling techniques should be examined by utilities industry researchers, developers, operators and management for application to utilities planning problems because of its great cost benefit potential. 4 refs., 4 figs

  1. Comparing Book- and Tablet-Based Picture Activity Schedules: Acquisition and Preference.

    Science.gov (United States)

    Giles, Aimee; Markham, Victoria

    2017-09-01

    Picture activity schedules consist of a sequence of images representing the order of tasks for a person to complete. Although, picture activity schedules have traditionally been presented in a book format, recently picture activity schedules have been evaluated on technological devices such as an iPod™ touch. The present study compared the efficiency of picture activity schedule acquisition on book- and tablet-based modalities. In addition, participant preference for each modality was assessed. Three boys aged below 5 years with a diagnosis of autism participated. Participants were taught to follow the schedules using both modalities. Following mastery of each modality of picture activity schedule, a concurrent-chains preference assessment was conducted to evaluate participant preference for each modality. Differences in acquisition rates across the two modalities were marginal. Preference for book- or tablet-based schedules was idiosyncratic across participants.

  2. Information Flow Scheduling in Concurrent Multi-Product Development Based on DSM

    Science.gov (United States)

    Sun, Qing-Chao; Huang, Wei-Qiang; Jiang, Ying-Jie; Sun, Wei

    2017-09-01

    Multi-product collaborative development is adopted widely in manufacturing enterprise, while the present multi-project planning models don't take technical/data interactions of multiple products into account. To decrease the influence of technical/data interactions on project progresses, the information flow scheduling models based on the extended DSM is presented. Firstly, information dependencies are divided into four types: series, parallel, coupling and similar. Secondly, different types of dependencies are expressed as DSM units, and the extended DSM model is brought forward, described as a block matrix. Furthermore, the information flow scheduling methods is proposed, which involves four types of operations, where partitioning and clustering algorithm are modified from DSM for ensuring progress of high-priority project, merging and converting is the specific computation of the extended DSM. Finally, the information flow scheduling of two machine tools development is analyzed with example, and different project priorities correspond to different task sequences and total coordination cost. The proposed methodology provides a detailed instruction for information flow scheduling in multi-product development, with specially concerning technical/data interactions.

  3. Metaheuristic Based Scheduling Meta-Tasks in Distributed Heterogeneous Computing Systems

    Directory of Open Access Journals (Sweden)

    Hesam Izakian

    2009-07-01

    Full Text Available Scheduling is a key problem in distributed heterogeneous computing systems in order to benefit from the large computing capacity of such systems and is an NP-complete problem. In this paper, we present a metaheuristic technique, namely the Particle Swarm Optimization (PSO algorithm, for this problem. PSO is a population-based search algorithm based on the simulation of the social behavior of bird flocking and fish schooling. Particles fly in problem search space to find optimal or near-optimal solutions. The scheduler aims at minimizing makespan, which is the time when finishes the latest task. Experimental studies show that the proposed method is more efficient and surpasses those of reported PSO and GA approaches for this problem.

  4. A risk-based approach to scheduling audits.

    Science.gov (United States)

    Rönninger, Stephan; Holmes, Malcolm

    2009-01-01

    The manufacture and supply of pharmaceutical products can be a very complex operation. Companies may purchase a wide variety of materials, from active pharmaceutical ingredients to packaging materials, from "in company" suppliers or from third parties. They may also purchase or contract a number of services such as analysis, data management, audit, among others. It is very important that these materials and services are of the requisite quality in order that patient safety and company reputation are adequately protected. Such quality requirements are ongoing throughout the product life cycle. In recent years, assurance of quality has been derived via audit of the supplier or service provider and by using periodic audits, for example, annually or at least once every 5 years. In the past, companies may have used an audit only for what they considered to be "key" materials or services and used testing on receipt, for example, as their quality assurance measure for "less important" supplies. Such approaches changed as a result of pressure from both internal sources and regulators to the time-driven audit for all suppliers and service providers. Companies recognised that eventually they would be responsible for the quality of the supplied product or service and audit, although providing only a "snapshot in time" seemed a convenient way of demonstrating that they were meeting their obligations. Problems, however, still occur with the supplied product or service and will usually be more frequent from certain suppliers. Additionally, some third-party suppliers will no longer accept routine audits from individual companies, as the overall audit load can exceed one external audit per working day. Consequently a different model is needed for assessing supplier quality. This paper presents a risk-based approach to creating an audit plan and for scheduling the frequency and depth of such audits. The approach is based on the principles and process of the Quality Risk Management

  5. Online Dynamic Balance Technology for High Speed Spindle Based on Gain Parameter Adaption and Scheduling Control

    Directory of Open Access Journals (Sweden)

    Shihai Zhang

    2018-06-01

    Full Text Available Unbalance vibration is one of the main vibration forms of a high speed machine tool spindle. The overlarge unbalance vibration will have some adverse effects on the working life of the spindle system and the surface quality of the work-piece. In order to reduce the unbalance of a high speed spindle system, a pneumatic online dynamic balance device and its control system are presented in the paper. To improve the balance accuracy and adaptation of the balance system, the gain parameter adaption and scheduling control method are proposed first, and then the different balance effects of the influence coefficient method and the gain scheduling control method are compared through many dynamic balance experiments of the high speed spindle. The experimental results indicate that the gain parameters can be changed timely according to the transformation of the speed and kinetic parameters of the spindle system. The balance accuracy can be improved for a high speed spindle with time-varying characteristics, based on the adaptive gain scheduling control method.

  6. Condition-based maintenance at both scheduled and unscheduled opportunities

    NARCIS (Netherlands)

    Kalosi, S.; Kapodistria, S.; Resing, J.A.C.

    2016-01-01

    Motivated by original equipment manufacturer (OEM) service and maintenance practices we consider a single component subject to replacements at failure instances and two types of preventive maintenance opportunities: scheduled, which occur due to periodic system reviews of the equipment, and

  7. DLTAP: A Network-efficient Scheduling Method for Distributed Deep Learning Workload in Containerized Cluster Environment

    OpenAIRE

    Qiao Wei; Li Ying; Wu Zhong-Hai

    2017-01-01

    Deep neural networks (DNNs) have recently yielded strong results on a range of applications. Training these DNNs using a cluster of commodity machines is a promising approach since training is time consuming and compute-intensive. Furthermore, putting DNN tasks into containers of clusters would enable broader and easier deployment of DNN-based algorithms. Toward this end, this paper addresses the problem of scheduling DNN tasks in the containerized cluster environment. Efficiently scheduling ...

  8. Residential Consumption Scheduling Based on Dynamic User Profiling

    Science.gov (United States)

    Mangiatordi, Federica; Pallotti, Emiliano; Del Vecchio, Paolo; Capodiferro, Licia

    Deployment of household appliances and of electric vehicles raises the electricity demand in the residential areas and the impact of the building's electrical power. The variations of electricity consumption across the day, may affect both the design of the electrical generation facilities and the electricity bill, mainly when a dynamic pricing is applied. This paper focuses on an energy management system able to control the day-ahead electricity demand in a residential area, taking into account both the variability of the energy production costs and the profiling of the users. The user's behavior is dynamically profiled on the basis of the tasks performed during the previous days and of the tasks foreseen for the current day. Depending on the size and on the flexibility in time of the user tasks, home inhabitants are grouped in, one over N, energy profiles, using a k-means algorithm. For a fixed energy generation cost, each energy profile is associated to a different hourly energy cost. The goal is to identify any bad user profile and to make it pay a highest bill. A bad profile example is when a user applies a lot of consumption tasks and low flexibility in task reallocation time. The proposed energy management system automatically schedules the tasks, solving a multi-objective optimization problem based on an MPSO strategy. The goals, when identifying bad users profiles, are to reduce the peak to average ratio in energy demand, and to minimize the energy costs, promoting virtuous behaviors.

  9. An Event-driven, Value-based, Pull Systems Engineering Scheduling Approach

    Science.gov (United States)

    2012-03-01

    combining a services approach to systems engineering with a kanban -based scheduling system. It provides the basis for validating the approach with...agent-based simulations. Keywords-systems engineering; systems engineering process; lean; kanban ; process simulation I. INTRODUCTION AND BACKGROUND...approaches [8], [9], we are investigating the use of flow-based pull scheduling techniques ( kanban systems) in a rapid response development

  10. Crop-Specific Grafting Methods, Rootstocks and Scheduling-Tomato

    Science.gov (United States)

    Grafting has gained popularity as a method to manage plant diseases previously controlled by soil fumigation with methyl bromide. Some of the most significant soilborne pest problems for which resistant rootstocks may be beneficial include root-knot nematodes, Verticillium wilt, and southern blight....

  11. An UAV scheduling and planning method for post-disaster survey

    Science.gov (United States)

    Li, G. Q.; Zhou, X. G.; Yin, J.; Xiao, Q. Y.

    2014-11-01

    Annually, the extreme climate and special geological environments lead to frequent natural disasters, e.g., earthquakes, floods, etc. The disasters often bring serious casualties and enormous economic losses. Post-disaster surveying is very important for disaster relief and assessment. As the Unmanned Aerial Vehicle (UAV) remote sensing with the advantage of high efficiency, high precision, high flexibility, and low cost, it is widely used in emergency surveying in recent years. As the UAVs used in emergency surveying cannot stop and wait for the happening of the disaster, when the disaster happens the UAVs usually are working at everywhere. In order to improve the emergency surveying efficiency, it is needed to track the UAVs and assign the emergency surveying task for each selected UAV. Therefore, a UAV tracking and scheduling method for post-disaster survey is presented in this paper. In this method, Global Positioning System (GPS), and GSM network are used to track the UAVs; an emergency tracking UAV information database is built in advance by registration, the database at least includes the following information, e.g., the ID of the UAVs, the communication number of the UAVs; when catastrophe happens, the real time location of all UAVs in the database will be gotten using emergency tracking method at first, then the traffic cost time for all UAVs to the disaster region will be calculated based on the UAVs' the real time location and the road network using the nearest services analysis algorithm; the disaster region is subdivided to several emergency surveying regions based on DEM, area, and the population distribution map; the emergency surveying regions are assigned to the appropriated UAV according to shortest cost time rule. The UAVs tracking and scheduling prototype is implemented using SQLServer2008, ArcEnginge 10.1 SDK, Visual Studio 2010 C#, Android, SMS Modem, and Google Maps API.

  12. Scheduling of head-sensitive cascaded hydro systems : a comparison based on numerical simulation results

    Energy Technology Data Exchange (ETDEWEB)

    Catalao, J.P.S.; Mariano, S.J.P.S. [Beira Interior Univ., Covilha (Portugal). Dept. of Electromechanical Engineering; Mendes, V.M.F. [Superior Engineering Inst. of Lisbon, Lisbon (Portugal). Dept. of Electrical Engineering and Automation; Ferreira, L.A.F.M. [Technical Univ. of Lisbon, Superior Technical Inst., Lisbon (Portugal). Dept. of Electrical Engineering and Computers

    2008-07-01

    The electric power sector in Portugal and Spain has shifted from a traditional monopoly to a deregulated, competitive energy market. As such, hydroelectric facilities face the optimal challenge of how to make a profit by managing water resources without compromising future potential profit. As such, hydro scheduling is a key activity for hydroelectric power utilities because of its significant economic impact. It involves the optimal management of water inflows and storage in reservoirs. This paper considered the problem of short-term hydro scheduling, concerning head-sensitive cascaded reservoirs, and the algorithmic aspects of its solution. The authors proposed and compared optimization methods based on dynamic programming, and linear and nonlinear network programming. The comparison revealed a negligible extra computational effort in a realistic cascaded hydro system where the head depended on the stored water volume. 17 refs., 3 tabs., 7 figs.

  13. Research on a scheduling mechanism in a complex system based on TOC

    International Nuclear Information System (INIS)

    Wen, Zhang; Ya-Ming, Zhang; Jinbo, Chen; Kaijun, Leng

    2016-01-01

    Under the condition where there is no seasonal demand fluctuation, short life cycle product supply chain should confront the market environment such as the decreasing of product value, the launch of substitutes and the appearance of competitors’ similar products, and the supply chain will become a very complex system. In this paper, the authors consider a TOC-based scheduling mechanism in this complex supply chain system. under the constant total production cost, it is more important to improve the availability of the wanted product in order to enhance the overall supply chain competitiveness so to obtain more effective output(profit rate) for the supply chain in a long period. Especially we try to apply the SDBR concept into a schedule mechanism in a particular supply chain system, and use numerical analysis to test the efficiency of the proposed method.

  14. Scheduling of head-sensitive cascaded hydro systems : a comparison based on numerical simulation results

    International Nuclear Information System (INIS)

    Catalao, J.P.S.; Mariano, S.J.P.S.; Mendes, V.M.F.; Ferreira, L.A.F.M.

    2008-01-01

    The electric power sector in Portugal and Spain has shifted from a traditional monopoly to a deregulated, competitive energy market. As such, hydroelectric facilities face the optimal challenge of how to make a profit by managing water resources without compromising future potential profit. As such, hydro scheduling is a key activity for hydroelectric power utilities because of its significant economic impact. It involves the optimal management of water inflows and storage in reservoirs. This paper considered the problem of short-term hydro scheduling, concerning head-sensitive cascaded reservoirs, and the algorithmic aspects of its solution. The authors proposed and compared optimization methods based on dynamic programming, and linear and nonlinear network programming. The comparison revealed a negligible extra computational effort in a realistic cascaded hydro system where the head depended on the stored water volume. 17 refs., 3 tabs., 7 figs

  15. Prediction Based Proactive Thermal Virtual Machine Scheduling in Green Clouds

    Science.gov (United States)

    Kinger, Supriya; Kumar, Rajesh; Sharma, Anju

    2014-01-01

    Cloud computing has rapidly emerged as a widely accepted computing paradigm, but the research on Cloud computing is still at an early stage. Cloud computing provides many advanced features but it still has some shortcomings such as relatively high operating cost and environmental hazards like increasing carbon footprints. These hazards can be reduced up to some extent by efficient scheduling of Cloud resources. Working temperature on which a machine is currently running can be taken as a criterion for Virtual Machine (VM) scheduling. This paper proposes a new proactive technique that considers current and maximum threshold temperature of Server Machines (SMs) before making scheduling decisions with the help of a temperature predictor, so that maximum temperature is never reached. Different workload scenarios have been taken into consideration. The results obtained show that the proposed system is better than existing systems of VM scheduling, which does not consider current temperature of nodes before making scheduling decisions. Thus, a reduction in need of cooling systems for a Cloud environment has been obtained and validated. PMID:24737962

  16. Prediction Based Proactive Thermal Virtual Machine Scheduling in Green Clouds

    Directory of Open Access Journals (Sweden)

    Supriya Kinger

    2014-01-01

    Full Text Available Cloud computing has rapidly emerged as a widely accepted computing paradigm, but the research on Cloud computing is still at an early stage. Cloud computing provides many advanced features but it still has some shortcomings such as relatively high operating cost and environmental hazards like increasing carbon footprints. These hazards can be reduced up to some extent by efficient scheduling of Cloud resources. Working temperature on which a machine is currently running can be taken as a criterion for Virtual Machine (VM scheduling. This paper proposes a new proactive technique that considers current and maximum threshold temperature of Server Machines (SMs before making scheduling decisions with the help of a temperature predictor, so that maximum temperature is never reached. Different workload scenarios have been taken into consideration. The results obtained show that the proposed system is better than existing systems of VM scheduling, which does not consider current temperature of nodes before making scheduling decisions. Thus, a reduction in need of cooling systems for a Cloud environment has been obtained and validated.

  17. Prediction based proactive thermal virtual machine scheduling in green clouds.

    Science.gov (United States)

    Kinger, Supriya; Kumar, Rajesh; Sharma, Anju

    2014-01-01

    Cloud computing has rapidly emerged as a widely accepted computing paradigm, but the research on Cloud computing is still at an early stage. Cloud computing provides many advanced features but it still has some shortcomings such as relatively high operating cost and environmental hazards like increasing carbon footprints. These hazards can be reduced up to some extent by efficient scheduling of Cloud resources. Working temperature on which a machine is currently running can be taken as a criterion for Virtual Machine (VM) scheduling. This paper proposes a new proactive technique that considers current and maximum threshold temperature of Server Machines (SMs) before making scheduling decisions with the help of a temperature predictor, so that maximum temperature is never reached. Different workload scenarios have been taken into consideration. The results obtained show that the proposed system is better than existing systems of VM scheduling, which does not consider current temperature of nodes before making scheduling decisions. Thus, a reduction in need of cooling systems for a Cloud environment has been obtained and validated.

  18. Short-term hydro-thermal scheduling using particle swarm optimization method

    International Nuclear Information System (INIS)

    Yu, Binghui; Yuan, Xiaohui; Wang, Jinwen

    2007-01-01

    The approaches based on different particle swarm optimization (PSO) techniques are applied to solve the short-term hydro-thermal scheduling problem. In the proposed methods, many constraints of the hydro-thermal system, such as power balance, water balance, reservoir volume limits and the operation limits of hydro and thermal plants, are considered. The feasibility of the proposed algorithm is demonstrated through an example system, and the results are compared with the results of a genetic algorithm and evolutionary programming approaches. The experimental results show that all the PSO algorithms have the ability to achieve nearly global solutions, but a local version of PSO with inertia weight appears to be the best amongst all the PSOs in terms of high quality solution

  19. A Simple Method for Dynamic Scheduling in a Heterogeneous Computing System

    OpenAIRE

    Žumer, Viljem; Brest, Janez

    2002-01-01

    A simple method for the dynamic scheduling on a heterogeneous computing system is proposed in this paper. It was implemented to minimize the parallel program execution time. The proposed method decomposes the program workload into computationally homogeneous subtasks, which may be of the different size, depending on the current load of each machine in a heterogeneous computing system.

  20. Adaptive Priority-Based Downlink Scheduling for WiMAX Networks

    OpenAIRE

    Wu, Shih-Jung; Huang, Shih-Yi; Huang, Kuo-Feng

    2012-01-01

    Supporting quality of service (QoS) guarantees for diverse multimedia services are the primary concerns for WiMAX (IEEE 802.16) networks. A scheduling scheme that satisfies QoS requirements has become more important for wireless communications. We propose a downlink scheduling scheme called adaptive priority-based downlink scheduling (APDS) for providing QoS guarantees in IEEE 802.16 networks. APDS comprises two major components: priority assignment and resource allocation. Different service-...

  1. Opportunistic splitting for scheduling using a score-based approach

    KAUST Repository

    Rashid, Faraan; Nam, Haewoon; Alouini, Mohamed-Slim

    2012-01-01

    to the centralized scheduler. The users find the best among themselves while requiring just a ternary feedback from the common receiver at the end of each mini-slot. The original splitting algorithm is modified to handle users with asymmetric channel conditions. We

  2. Simulation-based Advance Patient Scheduling of Operating Theatres

    DEFF Research Database (Denmark)

    Andersen, Anders Reenberg; Stidsen, Thomas Jacob Riis; Nielsen, Bo Friis

    2017-01-01

    Daily scheduling of surgical operations is a complicated and recurrent problem in the literature on health care optimization. In this study, we present an often overlooked approach to this problem that incorporates a rolling and overlapping planning horizon. The basis of our modeling approach is ...

  3. Resource management and scheduling policy based on grid for AIoT

    Science.gov (United States)

    Zou, Yiqin; Quan, Li

    2017-07-01

    This paper has a research on resource management and scheduling policy based on grid technology for Agricultural Internet of Things (AIoT). Facing the situation of a variety of complex and heterogeneous agricultural resources in AIoT, it is difficult to represent them in a unified way. But from an abstract perspective, there are some common models which can express their characteristics and features. Based on this, we proposed a high-level model called Agricultural Resource Hierarchy Model (ARHM), which can be used for modeling various resources. It introduces the agricultural resource modeling method based on this model. Compared with traditional application-oriented three-layer model, ARHM can hide the differences of different applications and make all applications have a unified interface layer and be implemented without distinction. Furthermore, it proposes a Web Service Resource Framework (WSRF)-based resource management method and the encapsulation structure for it. Finally, it focuses on the discussion of multi-agent-based AG resource scheduler, which is a collaborative service provider pattern in multiple agricultural production domains.

  4. Taking the lag out of jet lag through model-based schedule design.

    Science.gov (United States)

    Dean, Dennis A; Forger, Daniel B; Klerman, Elizabeth B

    2009-06-01

    Travel across multiple time zones results in desynchronization of environmental time cues and the sleep-wake schedule from their normal phase relationships with the endogenous circadian system. Circadian misalignment can result in poor neurobehavioral performance, decreased sleep efficiency, and inappropriately timed physiological signals including gastrointestinal activity and hormone release. Frequent and repeated transmeridian travel is associated with long-term cognitive deficits, and rodents experimentally exposed to repeated schedule shifts have increased death rates. One approach to reduce the short-term circadian, sleep-wake, and performance problems is to use mathematical models of the circadian pacemaker to design countermeasures that rapidly shift the circadian pacemaker to align with the new schedule. In this paper, the use of mathematical models to design sleep-wake and countermeasure schedules for improved performance is demonstrated. We present an approach to designing interventions that combines an algorithm for optimal placement of countermeasures with a novel mode of schedule representation. With these methods, rapid circadian resynchrony and the resulting improvement in neurobehavioral performance can be quickly achieved even after moderate to large shifts in the sleep-wake schedule. The key schedule design inputs are endogenous circadian period length, desired sleep-wake schedule, length of intervention, background light level, and countermeasure strength. The new schedule representation facilitates schedule design, simulation studies, and experiment design and significantly decreases the amount of time to design an appropriate intervention. The method presented in this paper has direct implications for designing jet lag, shift-work, and non-24-hour schedules, including scheduling for extreme environments, such as in space, undersea, or in polar regions.

  5. Taking the lag out of jet lag through model-based schedule design.

    Directory of Open Access Journals (Sweden)

    Dennis A Dean

    2009-06-01

    Full Text Available Travel across multiple time zones results in desynchronization of environmental time cues and the sleep-wake schedule from their normal phase relationships with the endogenous circadian system. Circadian misalignment can result in poor neurobehavioral performance, decreased sleep efficiency, and inappropriately timed physiological signals including gastrointestinal activity and hormone release. Frequent and repeated transmeridian travel is associated with long-term cognitive deficits, and rodents experimentally exposed to repeated schedule shifts have increased death rates. One approach to reduce the short-term circadian, sleep-wake, and performance problems is to use mathematical models of the circadian pacemaker to design countermeasures that rapidly shift the circadian pacemaker to align with the new schedule. In this paper, the use of mathematical models to design sleep-wake and countermeasure schedules for improved performance is demonstrated. We present an approach to designing interventions that combines an algorithm for optimal placement of countermeasures with a novel mode of schedule representation. With these methods, rapid circadian resynchrony and the resulting improvement in neurobehavioral performance can be quickly achieved even after moderate to large shifts in the sleep-wake schedule. The key schedule design inputs are endogenous circadian period length, desired sleep-wake schedule, length of intervention, background light level, and countermeasure strength. The new schedule representation facilitates schedule design, simulation studies, and experiment design and significantly decreases the amount of time to design an appropriate intervention. The method presented in this paper has direct implications for designing jet lag, shift-work, and non-24-hour schedules, including scheduling for extreme environments, such as in space, undersea, or in polar regions.

  6. Borda application of selection planning scheduling method in dock engineering consultants in Central Sulawesi province Indonesia

    Directory of Open Access Journals (Sweden)

    Siti Fatimah

    2015-04-01

    Full Text Available The aim of this paper to find out the planning scheduling method that used in dock engineering consultants as a project supervisor dock. This research use qualitative approach to find the most preferred method by engineering consultants, this research was explorative that test and find out the most preferred method. This research showed that dock engineering consultants in Palu City, Central Sulawesi most preferred curve-s method than method such as CPM, PERT, PDM, and Bar Chart. This research can help further research to determine differences and similarities the project planning scheduling method and being basic for The New Dock Engineering Consultans. This research looking for the most preferred method with limited respondents dock engineering consultans in Palu City, Central Sulawesi.

  7. Research on information models for the construction schedule management based on the IFC standard

    Directory of Open Access Journals (Sweden)

    Weirui Xue

    2015-05-01

    Full Text Available Purpose: The purpose of this article is to study the description and extension of the Industry Foundation Classes (IFC standard in construction schedule management, which achieves the information exchange and sharing among the different information systems and stakeholders, and facilitates the collaborative construction in the construction projects. Design/methodology/approach: The schedule information processing and coordination are difficult in the complex construction project. Building Information Modeling (BIM provides the platform for exchanging and sharing information among information systems and stakeholders based on the IFC standard. Through analyzing the schedule plan, implementing, check and control, the information flow in the schedule management is reflected based on the IDEF. According to the IFC4, the information model for the schedule management is established, which not only includes the each aspect of the schedule management, but also includes the cost management, the resource management, the quality management and the risk management. Findings: The information requirement for the construction schedule management can be summarized into three aspects: the schedule plan information, the implementing information and the check and control information. The three aspects can be described through the existing and extended entities of IFC4, and the information models are established. Originality/value: The main contribution of the article is to establish the construction schedule management information model, which achieves the information exchange and share in the construction project, and facilitates the development of the application software to meet the requirements of the construction project.

  8. A Genetic Algorithm-based Heuristic for Part-Feeding Mobile Robot Scheduling Problem

    DEFF Research Database (Denmark)

    Dang, Vinh Quang; Nielsen, Izabela Ewa; Bocewicz, Grzegorz

    2012-01-01

    This present study deals with the problem of sequencing feeding tasks of a single mobile robot with manipulation arm which is able to provide parts or components for feeders of machines in a manufacturing cell. The mobile robot has to be scheduled in order to keep machines within the cell producing...... products without any shortage of parts. A method based on the characteristics of feeders and inspired by the (s, Q) inventory system, is thus applied to define time windows for feeding tasks of the robot. The performance criterion is to minimize total traveling time of the robot in a given planning horizon...

  9. 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.

    2012-01-01

    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. PMID:23564979

  10. 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)

  11. Profit-based conventional resource scheduling with renewable energy penetration

    Science.gov (United States)

    Reddy, K. Srikanth; Panwar, Lokesh Kumar; Kumar, Rajesh; Panigrahi, B. K.

    2017-08-01

    Technological breakthroughs in renewable energy technologies (RETs) enabled them to attain grid parity thereby making them potential contenders for existing conventional resources. To examine the market participation of RETs, this paper formulates a scheduling problem accommodating energy market participation of wind- and solar-independent power producers (IPPs) treating both conventional and RETs as identical entities. Furthermore, constraints pertaining to penetration and curtailments of RETs are restructured. Additionally, an appropriate objective function for profit incurred by conventional resource IPPs through reserve market participation as a function of renewable energy curtailment is also proposed. The proposed concept is simulated with a test system comprising 10 conventional generation units in conjunction with solar photovoltaic (SPV) and wind energy generators (WEG). The simulation results indicate that renewable energy integration and its curtailment limits influence the market participation or scheduling strategies of conventional resources in both energy and reserve markets. Furthermore, load and reliability parameters are also affected.

  12. An efficient schedule based data aggregation using node mobility for wireless sensor network

    DEFF Research Database (Denmark)

    Dnyaneshwar, Mantri; Pawar, Pranav M.; Prasad, Neeli R.

    2014-01-01

    In the Wireless Sensor Networks, (WSNs) a key challenge is to schedule the activities of the mobile node for improvement in throughput, energy consumption and delay. This paper proposes efficient schedule based data aggregation algorithm using node mobility (SDNM). It considers the cluster...

  13. Model-based schedulability analysis of safety critical hard real-time Java programs

    DEFF Research Database (Denmark)

    Bøgholm, Thomas; Kragh-Hansen, Henrik; Olsen, Petur

    2008-01-01

    verifiable by the Uppaal model checker [23]. Schedulability analysis is reduced to a simple reachability question, checking for deadlock freedom. Model-based schedulability analysis has been developed by Amnell et al. [2], but has so far only been applied to high level specifications, not actual...

  14. Scheduled power tracking control of the wind-storage hybrid system based on the reinforcement learning theory

    Science.gov (United States)

    Li, Ze

    2017-09-01

    In allusion to the intermittency and uncertainty of the wind electricity, energy storage and wind generator are combined into a hybrid system to improve the controllability of the output power. A scheduled power tracking control method is proposed based on the reinforcement learning theory and Q-learning algorithm. In this method, the state space of the environment is formed with two key factors, i.e. the state of charge of the energy storage and the difference value between the actual wind power and scheduled power, the feasible action is the output power of the energy storage, and the corresponding immediate rewarding function is designed to reflect the rationality of the control action. By interacting with the environment and learning from the immediate reward, the optimal control strategy is gradually formed. After that, it could be applied to the scheduled power tracking control of the hybrid system. Finally, the rationality and validity of the method are verified through simulation examples.

  15. Heuristics methods for the flow shop scheduling problem with separated setup times

    Directory of Open Access Journals (Sweden)

    Marcelo Seido Nagano

    2012-06-01

    Full Text Available This paper deals with the permutation flow shop scheduling problem with separated machine setup times. As a result of an investigation on the problem characteristics, four heuristics methods are proposed with procedures of the construction sequencing solution by an analogy with the asymmetric traveling salesman problem with the objective of minimizing makespan. Experimental results show that one of the new heuristics methods proposed provide high quality solutions in comparisons with the evaluated methods considered in the literature.

  16. HOLD MODE BASED DYNAMIC PRIORITY LOAD ADAPTIVE INTERPICONET SCHEDULING FOR BLUETOOTH SCATTERNETS

    Directory of Open Access Journals (Sweden)

    G.S. Mahalakshmi

    2011-09-01

    Full Text Available Scheduling in piconets has emerged as a challenging research area. Interpiconet scheduling focuses on when a bridge is switched among various piconets and how a bridge node communicates with the masters in different piconets. This paper proposes an interpiconet scheduling algorithm named, hold mode based dynamic traffic priority load adaptive scheduling. The bridges are adaptively switched between the piconets according to various traffic loads. The main goal is to maximize the utilization of the bridge by reducing the bridge switch wastes, utilize intelligent decision making algorithm, resolve conflict between the masters, and allow negotiation for bridge utilization in HDPLIS using bridge failure-bridge repair procedure . The Hold mode - dynamic traffic - priority based - load adaptive scheduling reduces the number of bridge switch wastes and hence increases the efficiency of the bridge which results in increased performance of the system.

  17. T-L Plane Abstraction-Based Energy-Efficient Real-Time Scheduling for Multi-Core Wireless Sensors

    Directory of Open Access Journals (Sweden)

    Youngmin Kim

    2016-07-01

    Full Text Available Energy efficiency is considered as a critical requirement for wireless sensor networks. As more wireless sensor nodes are equipped with multi-cores, there are emerging needs for energy-efficient real-time scheduling algorithms. The T-L plane-based scheme is known to be an optimal global scheduling technique for periodic real-time tasks on multi-cores. Unfortunately, there has been a scarcity of studies on extending T-L plane-based scheduling algorithms to exploit energy-saving techniques. In this paper, we propose a new T-L plane-based algorithm enabling energy-efficient real-time scheduling on multi-core sensor nodes with dynamic power management (DPM. Our approach addresses the overhead of processor mode transitions and reduces fragmentations of the idle time, which are inherent in T-L plane-based algorithms. Our experimental results show the effectiveness of the proposed algorithm compared to other energy-aware scheduling methods on T-L plane abstraction.

  18. 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.

  19. Advances in mixed-integer programming methods for chemical production scheduling.

    Science.gov (United States)

    Velez, Sara; Maravelias, Christos T

    2014-01-01

    The goal of this paper is to critically review advances in the area of chemical production scheduling over the past three decades and then present two recently proposed solution methods that have led to dramatic computational enhancements. First, we present a general framework and problem classification and discuss modeling and solution methods with an emphasis on mixed-integer programming (MIP) techniques. Second, we present two solution methods: (a) a constraint propagation algorithm that allows us to compute parameters that are then used to tighten MIP scheduling models and (b) a reformulation that introduces new variables, thus leading to effective branching. We also present computational results and an example illustrating how these methods are implemented, as well as the resulting enhancements. We close with a discussion of open research challenges and future research directions.

  20. Drug scheduling of cancer chemotherapy based on natural actor-critic approach.

    Science.gov (United States)

    Ahn, Inkyung; Park, Jooyoung

    2011-11-01

    Recently, reinforcement learning methods have drawn significant interests in the area of artificial intelligence, and have been successfully applied to various decision-making problems. In this paper, we study the applicability of the NAC (natural actor-critic) approach, a state-of-the-art reinforcement learning method, to the drug scheduling of cancer chemotherapy for an ODE (ordinary differential equation)-based tumor growth model. ODE-based cancer dynamics modeling is an active research area, and many different mathematical models have been proposed. Among these, we use the model proposed by de Pillis and Radunskaya (2003), which considers the growth of tumor cells and their interaction with normal cells and immune cells. The NAC approach is applied to this ODE model with the goal of minimizing the tumor cell population and the drug amount while maintaining the adequate population levels of normal cells and immune cells. In the framework of the NAC approach, the drug dose is regarded as the control input, and the reward signal is defined as a function of the control input and the cell populations of tumor cells, normal cells, and immune cells. According to the control policy found by the NAC approach, effective drug scheduling in cancer chemotherapy for the considered scenarios has turned out to be close to the strategy of continuing drug injection from the beginning until an appropriate time. Also, simulation results showed that the NAC approach can yield better performance than conventional pulsed chemotherapy. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

  1. Flexible job-shop scheduling based on genetic algorithm and simulation validation

    Directory of Open Access Journals (Sweden)

    Zhou Erming

    2017-01-01

    Full Text Available This paper selects flexible job-shop scheduling problem as the research object, and Constructs mathematical model aimed at minimizing the maximum makespan. Taking the transmission reverse gear production line of a transmission corporation as an example, genetic algorithm is applied for flexible jobshop scheduling problem to get the specific optimal scheduling results with MATLAB. DELMIA/QUEST based on 3D discrete event simulation is applied to construct the physical model of the production workshop. On the basis of the optimal scheduling results, the logical link of the physical model for the production workshop is established, besides, importing the appropriate process parameters to make virtual simulation on the production workshop. Finally, through analyzing the simulated results, it shows that the scheduling results are effective and reasonable.

  2. Project Scheduling Heuristics-Based Standard PSO for Task-Resource Assignment in Heterogeneous Grid

    Directory of Open Access Journals (Sweden)

    Ruey-Maw Chen

    2011-01-01

    Full Text Available The task scheduling problem has been widely studied for assigning resources to tasks in heterogeneous grid environment. Effective task scheduling is an important issue for the performance of grid computing. Meanwhile, the task scheduling problem is an NP-complete problem. Hence, this investigation introduces a named “standard“ particle swarm optimization (PSO metaheuristic approach to efficiently solve the task scheduling problems in grid. Meanwhile, two promising heuristics based on multimode project scheduling are proposed to help in solving interesting scheduling problems. They are the best performance resource heuristic and the latest finish time heuristic. These two heuristics applied to the PSO scheme are for speeding up the search of the particle and improving the capability of finding a sound schedule. Moreover, both global communication topology and local ring communication topology are also investigated for efficient study of proposed scheme. Simulation results demonstrate that the proposed approach in this investigation can successfully solve the task-resource assignment problems in grid computing and similar scheduling problems.

  3. A Novel Assembly Line Scheduling Algorithm Based on CE-PSO

    Directory of Open Access Journals (Sweden)

    Xiaomei Hu

    2015-01-01

    Full Text Available With the widespread application of assembly line in enterprises, assembly line scheduling is an important problem in the production since it directly affects the productivity of the whole manufacturing system. The mathematical model of assembly line scheduling problem is put forward and key data are confirmed. A double objective optimization model based on equipment utilization and delivery time loss is built, and optimization solution strategy is described. Based on the idea of solution strategy, assembly line scheduling algorithm based on CE-PSO is proposed to overcome the shortcomings of the standard PSO. Through the simulation experiments of two examples, the validity of the assembly line scheduling algorithm based on CE-PSO is proved.

  4. A Scheduling Algorithm for Cloud Computing System Based on the Driver of Dynamic Essential Path.

    Science.gov (United States)

    Xie, Zhiqiang; Shao, Xia; Xin, Yu

    2016-01-01

    To solve the problem of task scheduling in the cloud computing system, this paper proposes a scheduling algorithm for cloud computing based on the driver of dynamic essential path (DDEP). This algorithm applies a predecessor-task layer priority strategy to solve the problem of constraint relations among task nodes. The strategy assigns different priority values to every task node based on the scheduling order of task node as affected by the constraint relations among task nodes, and the task node list is generated by the different priority value. To address the scheduling order problem in which task nodes have the same priority value, the dynamic essential long path strategy is proposed. This strategy computes the dynamic essential path of the pre-scheduling task nodes based on the actual computation cost and communication cost of task node in the scheduling process. The task node that has the longest dynamic essential path is scheduled first as the completion time of task graph is indirectly influenced by the finishing time of task nodes in the longest dynamic essential path. Finally, we demonstrate the proposed algorithm via simulation experiments using Matlab tools. The experimental results indicate that the proposed algorithm can effectively reduce the task Makespan in most cases and meet a high quality performance objective.

  5. Entity’s Irregular Demand Scheduling of the Wholesale Electricity Market based on the Forecast of Hourly Price Ratios

    Directory of Open Access Journals (Sweden)

    O. V. Russkov

    2015-01-01

    Full Text Available The article considers a hot issue to forecast electric power demand amounts and prices for the entities of wholesale electricity market (WEM, which are in capacity of a large user with production technology requirements prevailing over hourly energy planning ones. An electric power demand of such entities is on irregular schedule. The article analyses mathematical models, currently applied to forecast demand amounts and prices. It describes limits of time-series models and fundamental ones in case of hourly forecasting an irregular demand schedule of the electricity market entity. The features of electricity trading at WEM are carefully analysed. Factors that influence on irregularity of demand schedule of the metallurgical plant are shown. The article proposes method for the qualitative forecast of market price ratios as a tool to reduce a dependence on the accuracy of forecasting an irregular schedule of demand. It describes the differences between the offered method and the similar ones considered in research studies and scholarly works. The correlation between price ratios and relaxation in the requirements for the forecast accuracy of the electric power consumption is analysed. The efficiency function of forecast method is derived. The article puts an increased focus on description of the mathematical model based on the method of qualitative forecast. It shows main model parameters and restrictions the electricity market imposes on them. The model prototype is described as a programme module. Methods to assess an effectiveness of the proposed forecast model are examined. The positive test results of the model using JSC «Volzhsky Pipe Plant» data are given. A conclusion is drawn concerning the possibility to decrease dependence on the forecast accuracy of irregular schedule of entity’s demand at WEM. The effective trading tool has been found for the entities of irregular demand schedule at WEM. The tool application allows minimizing cost

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

    Energy Technology Data Exchange (ETDEWEB)

    Lu, Songfeng; Sun, Chengfu; Lu, Zhengding [School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan 430074 (China)

    2010-03-15

    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. (author)

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

    Energy Technology Data Exchange (ETDEWEB)

    Lu Songfeng [School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan 430074 (China); Sun Chengfu, E-mail: ajason_369@sina.co [School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan 430074 (China); Lu Zhengding [School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan 430074 (China)

    2010-03-15

    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.

  8. 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.

  9. Study on Cloud Computing Resource Scheduling Strategy Based on the Ant Colony Optimization Algorithm

    OpenAIRE

    Lingna He; Qingshui Li; Linan Zhu

    2012-01-01

    In order to replace the traditional Internet software usage patterns and enterprise management mode, this paper proposes a new business calculation mode- cloud computing, resources scheduling strategy is the key technology in cloud computing, Based on the study of cloud computing system structure and the mode of operation, The key research for cloud computing the process of the work scheduling and resource allocation problems based on ant colony algorithm , Detailed analysis and design of the...

  10. 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.

  11. 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.

  12. Ship Block Transportation Scheduling Problem Based on Greedy Algorithm

    Directory of Open Access Journals (Sweden)

    Chong Wang

    2016-05-01

    Full Text Available Ship block transportation problems are crucial issues to address in reducing the construction cost and improving the productivity of shipyards. Shipyards aim to maximize the workload balance of transporters with time constraint such that all blocks should be transported during the planning horizon. This process leads to three types of penalty time: empty transporter travel time, delay time, and tardy time. This study aims to minimize the sum of the penalty time. First, this study presents the problem of ship block transportation with the generalization of the block transportation restriction on the multi-type transporter. Second, the problem is transformed into the classical traveling salesman problem and assignment problem through a reasonable model simplification and by adding a virtual node to the proposed directed graph. Then, a heuristic algorithm based on greedy algorithm is proposed to assign blocks to available transporters and sequencing blocks for each transporter simultaneously. Finally, the numerical experiment method is used to validate the model, and its result shows that the proposed algorithm is effective in realizing the efficient use of the transporters in shipyards. Numerical simulation results demonstrate the promising application of the proposed method to efficiently improve the utilization of transporters and to reduce the cost of ship block logistics for shipyards.

  13. 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

  14. 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.

  15. Efficient Hybrid Genetic Based Multi Dimensional Host Load Aware Algorithm for Scheduling and Optimization of Virtual Machines

    OpenAIRE

    Thiruvenkadam, T; Karthikeyani, V

    2014-01-01

    Mapping the virtual machines to the physical machines cluster is called the VM placement. Placing the VM in the appropriate host is necessary for ensuring the effective resource utilization and minimizing the datacenter cost as well as power. Here we present an efficient hybrid genetic based host load aware algorithm for scheduling and optimization of virtual machines in a cluster of Physical hosts. We developed the algorithm based on two different methods, first initial VM packing is done by...

  16. Real-time-service-based Distributed Scheduling Scheme for IEEE 802.16j Networks

    OpenAIRE

    Kuo-Feng Huang; Shih-Jung Wu

    2013-01-01

    Supporting Quality of Service (QoS) guarantees for diverse multimedia services is the primary concern for IEEE802.16j networks. A scheduling scheme that satisfies the QoS requirements has become more important for wireless communications. We proposed an adaptive nontransparent-based distributed scheduling scheme (ANDS) for IEEE 802.16j networks. ANDS comprises three major components: Priority Assignment, Resource Allocation, Preserved Bandwidth Adjustment. Different service-type connections p...

  17. Comparing three scheduling methods using BIM models in the Last Planner System

    Directory of Open Access Journals (Sweden)

    Brioso Xavier

    2017-12-01

    Full Text Available This article presents strategies for teaching scheduling methods such as takt-time, flowlines, and point-to-point precedence relations (PTPPRs using build­ing information modeling (BIM models in the Last Planner System. This article is the extended version of the article entitled “Teaching Takt-Time, Flowline and Point-to-point Precedence Relations: A Peruvian Case Study,” which has been published in Procedia Engineering (Vol. 196, 2017, pages 666-673. A case study is conducted in final year students of civil engineering at the Pontifical Catholic University of Peru. The mock-up project is an educational building that has high repetitive processes in the struc­tural works phase. First, traditional tools such as Excel spreadsheets and 2D drawings were used to teach produc­tion system design with takt-time, flowlines, and PTPPR. Second, 3D and 4D models with Revit 2016 and Navis­works 2016 were used to integrate the previous schedules with a BIM model and to identify its strengths and weak­nesses. Finally, Vico Office was used for the automation of schedules and comparison of the methods in 4D and 5D. This article describes the lectures, workshops, and simu­lations employed, as well as the feedback from students and researchers. The success of the teaching strategy is reflected in the survey responses from students and the final perceptions of the construction management tools presented.

  18. Culture belief based multi-objective hybrid differential evolutionary algorithm in short term hydrothermal scheduling

    International Nuclear Information System (INIS)

    Zhang Huifeng; Zhou Jianzhong; Zhang Yongchuan; Lu Youlin; Wang Yongqiang

    2013-01-01

    Highlights: ► Culture belief is integrated into multi-objective differential evolution. ► Chaotic sequence is imported to improve evolutionary population diversity. ► The priority of convergence rate is proved in solving hydrothermal problem. ► The results show the quality and potential of proposed algorithm. - Abstract: A culture belief based multi-objective hybrid differential evolution (CB-MOHDE) is presented to solve short term hydrothermal optimal scheduling with economic emission (SHOSEE) problem. This problem is formulated for compromising thermal cost and emission issue while considering its complicated non-linear constraints with non-smooth and non-convex characteristics. The proposed algorithm integrates a modified multi-objective differential evolutionary algorithm into the computation model of culture algorithm (CA) as well as some communication protocols between population space and belief space, three knowledge structures in belief space are redefined according to these problem-solving characteristics, and in the differential evolution a chaotic factor is embedded into mutation operator for avoiding the premature convergence by enlarging the search scale when the search trajectory reaches local optima. Furthermore, a new heuristic constraint-handling technique is utilized to handle those complex equality and inequality constraints of SHOSEE problem. After the application on hydrothermal scheduling system, the efficiency and stability of the proposed CB-MOHDE is verified by its more desirable results in comparison to other method established recently, and the simulation results also reveal that CB-MOHDE can be a promising alternative for solving SHOSEE.

  19. Power Transmission Scheduling for Generators in a Deregulated Environment Based on a Game-Theoretic Approach

    Directory of Open Access Journals (Sweden)

    Bingtuan Gao

    2015-12-01

    Full Text Available In a deregulated environment of the power market, in order to lower their energy price and guarantee the stability of the power network, appropriate transmission lines have to be considered for electricity generators to sell their energy to the end users. This paper proposes a game-theoretic power transmission scheduling for multiple generators to lower their wheeling cost. Based on the embedded cost method, a wheeling cost model consisting of congestion cost, cost of losses and cost of transmission capacity is presented. By assuming each generator behaves in a selfish and rational way, the competition among the multiple generators is formulated as a non-cooperative game, where the players are the generators and the strategies are their daily schedules of power transmission. We will prove that there exists at least one pure-strategy Nash equilibrium of the formulated power transmission game. Moreover, a distributed algorithm will be provided to realize the optimization in terms of minimizing the wheeling cost. Finally, simulations were performed and discussed to verify the feasibility and effectiveness of the proposed non-cooperative game approach for the generators in a deregulated environment.

  20. Day-ahead resource scheduling of a renewable energy based virtual power plant

    International Nuclear Information System (INIS)

    Zamani, Ali Ghahgharaee; Zakariazadeh, Alireza; Jadid, Shahram

    2016-01-01

    Highlights: • Simultaneous energy and reserve scheduling of a VPP. • Aggregate uncertainties of electricity prices, renewable generation and load demand. • Develop a stochastic scheduling model using the point estimate method. - Abstract: The evolution of energy markets is accelerating in the direction of a greater reliance upon distributed energy resources (DERs). To manage this increasing two-way complexity, virtual power plants (VPPs) are being deployed today all over the world. In this paper, a probabilistic model for optimal day ahead scheduling of electrical and thermal energy resources in a VPP is proposed where participation of energy storage systems and demand response programs (DRPs) are also taken into account. In the proposed model, energy and reserve is simultaneously scheduled considering the uncertainties of market prices, electrical demand and intermittent renewable power generation. The Point Estimate Method (PEM) is applied in order to model the uncertainties of VPP’s scheduling problem. Moreover, the optimal reserve scheduling of VPP is presented which efficiently decreases VPP’s risk facing the unexpected fluctuations of uncertain parameters at the power delivery time. The results demonstrated that implementation of demand response programs (DRPs) would decrease total operation costs of VPP as well as its dependency on the upstream network.

  1. Processing time tolerance-based ACO algorithm for solving job-shop scheduling problem

    Science.gov (United States)

    Luo, Yabo; Waden, Yongo P.

    2017-06-01

    Ordinarily, Job Shop Scheduling Problem (JSSP) is known as NP-hard problem which has uncertainty and complexity that cannot be handled by a linear method. Thus, currently studies on JSSP are concentrated mainly on applying different methods of improving the heuristics for optimizing the JSSP. However, there still exist many problems for efficient optimization in the JSSP, namely, low efficiency and poor reliability, which can easily trap the optimization process of JSSP into local optima. Therefore, to solve this problem, a study on Ant Colony Optimization (ACO) algorithm combined with constraint handling tactics is carried out in this paper. Further, the problem is subdivided into three parts: (1) Analysis of processing time tolerance-based constraint features in the JSSP which is performed by the constraint satisfying model; (2) Satisfying the constraints by considering the consistency technology and the constraint spreading algorithm in order to improve the performance of ACO algorithm. Hence, the JSSP model based on the improved ACO algorithm is constructed; (3) The effectiveness of the proposed method based on reliability and efficiency is shown through comparative experiments which are performed on benchmark problems. Consequently, the results obtained by the proposed method are better, and the applied technique can be used in optimizing JSSP.

  2. Wireless-Uplinks-Based Energy-Efficient Scheduling in Mobile Cloud Computing

    Directory of Open Access Journals (Sweden)

    Xing Liu

    2015-01-01

    Full Text Available Mobile cloud computing (MCC combines cloud computing and mobile internet to improve the computational capabilities of resource-constrained mobile devices (MDs. In MCC, mobile users could not only improve the computational capability of MDs but also save operation consumption by offloading the mobile applications to the cloud. However, MCC faces the problem of energy efficiency because of time-varying channels when the offloading is being executed. In this paper, we address the issue of energy-efficient scheduling for wireless uplink in MCC. By introducing Lyapunov optimization, we first propose a scheduling algorithm that can dynamically choose channel to transmit data based on queue backlog and channel statistics. Then, we show that the proposed scheduling algorithm can make a tradeoff between queue backlog and energy consumption in a channel-aware MCC system. Simulation results show that the proposed scheduling algorithm can reduce the time average energy consumption for offloading compared to the existing algorithm.

  3. Enhanced round robin CPU scheduling with burst time based time quantum

    Science.gov (United States)

    Indusree, J. R.; Prabadevi, B.

    2017-11-01

    Process scheduling is a very important functionality of Operating system. The main-known process-scheduling algorithms are First Come First Serve (FCFS) algorithm, Round Robin (RR) algorithm, Priority scheduling algorithm and Shortest Job First (SJF) algorithm. Compared to its peers, Round Robin (RR) algorithm has the advantage that it gives fair share of CPU to the processes which are already in the ready-queue. The effectiveness of the RR algorithm greatly depends on chosen time quantum value. Through this research paper, we are proposing an enhanced algorithm called Enhanced Round Robin with Burst-time based Time Quantum (ERRBTQ) process scheduling algorithm which calculates time quantum as per the burst-time of processes already in ready queue. The experimental results and analysis of ERRBTQ algorithm clearly indicates the improved performance when compared with conventional RR and its variants.

  4. 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.

  5. Decentralized Job Scheduling in the Cloud Based on a Spatially Generalized Prisoner’s Dilemma Game

    Directory of Open Access Journals (Sweden)

    Gąsior Jakub

    2015-12-01

    Full Text Available We present in this paper a novel distributed solution to a security-aware job scheduling problem in cloud computing infrastructures. We assume that the assignment of the available resources is governed exclusively by the specialized brokers assigned to individual users submitting their jobs to the system. The goal of this scheme is allocating a limited quantity of resources to a specific number of jobs minimizing their execution failure probability and total completion time. Our approach is based on the Pareto dominance relationship and implemented at an individual user level. To select the best scheduling strategies from the resulting Pareto frontiers and construct a global scheduling solution, we developed a decision-making mechanism based on the game-theoretic model of Spatial Prisoner’s Dilemma, realized by selfish agents operating in the two-dimensional cellular automata space. Their behavior is conditioned by the objectives of the various entities involved in the scheduling process and driven towards a Nash equilibrium solution by the employed social welfare criteria. The performance of the scheduler applied is verified by a number of numerical experiments. The related results show the effectiveness and scalability of the scheme in the presence of a large number of jobs and resources involved in the scheduling process.

  6. Project scheduling method with time using MRP system – A case study: Construction project in Libya

    Directory of Open Access Journals (Sweden)

    Abdallah Ali Imetieg

    2015-04-01

    Full Text Available Materials Requirements and Planning (MRP is a system of production planning and inventory control, which is used to manage manufacturing processes. Most MRP systems are software-based and are used to ensure that the materials are available for production, that the products are available for delivery to customers, that the lowest possible material and product level is maintained in store, as well as to plan delivery schedules and purchasing activities. Upon completion of scheduling, begins the process of follow-up, which includes the achievement of the project goals in terms of quantity, quality and costs in accordance with deadlines. MRP system was applied to project of 5000 housing units in Solug area, which is close to Benghazi city, Libya, with the aim to provide necessary cash flow to pay dues on time without delay to all involved project sub-contractors and material suppliers, to ensure the smooth flow of operations, as well as to diminish costs by reduction of temporary storages and rented areas. There is a correlation between time and cost of each activity. If the required time is shorter than the scheduled time of the certain activity, it would demand more resources, which further leads to the increase in direct costs of the given activity. Therefore, the output of MRP is important since commands are issued through planning in order to launch the suggested orders with the required quantities and within the limited time period.

  7. PERFORMANCE ANALYSIS BETWEEN EXPLICIT SCHEDULING AND IMPLICIT SCHEDULING OF PARALLEL ARRAY-BASED DOMAIN DECOMPOSITION USING OPENMP

    Directory of Open Access Journals (Sweden)

    MOHAMMED FAIZ ABOALMAALY

    2014-10-01

    Full Text Available With the continuous revolution of multicore architecture, several parallel programming platforms have been introduced in order to pave the way for fast and efficient development of parallel algorithms. Back into its categories, parallel computing can be done through two forms: Data-Level Parallelism (DLP or Task-Level Parallelism (TLP. The former can be done by the distribution of data among the available processing elements while the latter is based on executing independent tasks concurrently. Most of the parallel programming platforms have built-in techniques to distribute the data among processors, these techniques are technically known as automatic distribution (scheduling. However, due to their wide range of purposes, variation of data types, amount of distributed data, possibility of extra computational overhead and other hardware-dependent factors, manual distribution could achieve better outcomes in terms of performance when compared to the automatic distribution. In this paper, this assumption is investigated by conducting a comparison between automatic and our newly proposed manual distribution of data among threads in parallel. Empirical results of matrix addition and matrix multiplication show a considerable performance gain when manual distribution is applied against automatic distribution.

  8. Optimization of multi-objective integrated process planning and scheduling problem using a priority based optimization algorithm

    Science.gov (United States)

    Ausaf, Muhammad Farhan; Gao, Liang; Li, Xinyu

    2015-12-01

    For increasing the overall performance of modern manufacturing systems, effective integration of process planning and scheduling functions has been an important area of consideration among researchers. Owing to the complexity of handling process planning and scheduling simultaneously, most of the research work has been limited to solving the integrated process planning and scheduling (IPPS) problem for a single objective function. As there are many conflicting objectives when dealing with process planning and scheduling, real world problems cannot be fully captured considering only a single objective for optimization. Therefore considering multi-objective IPPS (MOIPPS) problem is inevitable. Unfortunately, only a handful of research papers are available on solving MOIPPS problem. In this paper, an optimization algorithm for solving MOIPPS problem is presented. The proposed algorithm uses a set of dispatching rules coupled with priority assignment to optimize the IPPS problem for various objectives like makespan, total machine load, total tardiness, etc. A fixed sized external archive coupled with a crowding distance mechanism is used to store and maintain the non-dominated solutions. To compare the results with other algorithms, a C-matric based method has been used. Instances from four recent papers have been solved to demonstrate the effectiveness of the proposed algorithm. The experimental results show that the proposed method is an efficient approach for solving the MOIPPS problem.

  9. The impact of exposure to shift-based schedules on medical students.

    Science.gov (United States)

    Williams, David A; Kogan, Jennifer R; Hauer, Karen E; Yamashita, Traci; Aagaard, Eva M

    2015-01-01

    With new resident duty-hour regulations, resident work schedules have progressively transitioned towards shift-based systems, sometimes resulting in increased team fragmentation. We hypothesized that exposure to shift-based schedules and subsequent team fragmentation would negatively affect medical student experiences during their third-year internal medicine clerkship. As part of a larger national study on duty-hour reform, 67 of 150 eligible third-year medical students completed surveys about career choice, teaching and supervision, assessment, patient care, well-being, and attractiveness of a career in internal medicine after completing their internal medicine clerkship. Students who rotated to hospitals with shift-based systems were compared to those who did not. Non-demographic variables used a five-point Likert scale. Chi-squared and Fisher's exact tests were used to assess the relationships between exposure to shift-based schedules and student responses. Questions with univariate p ≤ 0.1 were included in multivariable logistic regression models. Thirty-six students (54%) were exposed to shift-based schedules. Students exposed to shift-based schedules were less likely to perceive that their attendings were committed to teaching (odds ratio [OR] 0.35, 95% confidence interval [CI]: 0.13-0.90, p = 0.01) or perceive that residents had sufficient exposure to assess their performance (OR 0.29, 95% CI: 0.09-0.91, p = 0.03). However, those students were more likely to feel their interns were able to observe them at the bedside (OR 1.89, 95% CI: 1.08-3.13, p = 0.02) and had sufficient exposure to assess their performance (OR 3.00, 95% CI: 1.01-8.86, p = 0.05). These findings suggest that shift-based schedules designed in response to duty-hour reform may have important broader implications for the teaching environment.

  10. Thermal Unit Commitment Scheduling Problem in Utility System by Tabu Search Embedded Genetic Algorithm Method

    Directory of Open Access Journals (Sweden)

    C. Christober Asir Rajan

    2008-06-01

    Full Text Available The objective of this paper is to find the generation scheduling such that the total operating cost can be minimized, when subjected to a variety of constraints. This also means that it is desirable to find the optimal unit commitment in the power system for the next H hours. A 66-bus utility power system in India demonstrates the effectiveness of the proposed approach; extensive studies have also been performed for different IEEE test systems consist of 24, 57 and 175 buses. Numerical results are shown comparing the cost solutions and computation time obtained by different intelligence and conventional methods.

  11. Downstream-based Scheduling for Energy Conservation in Green EPONs

    KAUST Repository

    Chen, Shen; Dhaini, Ahmad R.; Ho, Pin-Han; Shihada, Basem; Shen, Gangxiang; Lin, Chih-Hao

    2012-01-01

    the ONU sleep time, it jeopardizes the quality of service (QoS) performance of the network, especially for downstream traffic in case the overlapping is based on the upstream time slot. In this paper, we study the downstream traffic performance in green

  12. Downstream-based Scheduling for Energy Conservation in Green EPONs

    KAUST Repository

    Chen, Shen

    2012-05-01

    Maximizing the optical network unit’s (ONU) sleep time is an effective approach for achieving maximum energy conservation in green Ethernet passive optical networks (EPONs). While overlapping downstream and upstream ONU transmissions can maximize the ONU sleep time, it jeopardizes the quality of service (QoS) performance of the network, especially for downstream traffic in case the overlapping is based on the upstream time slot. In this paper, we study the downstream traffic performance in green EPONs under the limited service discipline and the upstream-based overlapped time window. Specifically, we first derive the expected mean packet delay, and then present a closed-form expression of the ONU sleep time, setting identical upstream/downstream transmission cycle times based on a maximum downstream traffic delay re-quirement. With the proposed system model, we present a novel downstream bandwidth allocation scheme for energy conservation in green EPONs. Simulation results verify the proposed model and highlight the advantages of our scheme over conventional approaches.

  13. Gain Scheduling of PID Controller Based on Fuzzy Systems

    Directory of Open Access Journals (Sweden)

    Singh Sandeep

    2016-01-01

    Full Text Available This paper aims to utilize fuzzy rules and reasoning to determine the controller parameters and the PID controller generates the control signal. The objective of this study is to simulate the proposed scheme on various processes and arrive at results providing better response of the system when compared with best industrial auto-tuning technique: Ziegler-Nichols. The proposed scheme is based upon the Ultimate Gain (Ku and the Period (Tu of the system. The error and rate of change in error gains are tuned manually to get the desired response using LabVIEW. This can also be done with various optimization techniques. A thumb rule for choosing the ranges for Kc, Kd and Ki has been obtained experimentally.

  14. A decomposition heuristics based on multi-bottleneck machines for large-scale job shop scheduling problems

    Directory of Open Access Journals (Sweden)

    Yingni Zhai

    2014-10-01

    Full Text Available Purpose: A decomposition heuristics based on multi-bottleneck machines for large-scale job shop scheduling problems (JSP is proposed.Design/methodology/approach: In the algorithm, a number of sub-problems are constructed by iteratively decomposing the large-scale JSP according to the process route of each job. And then the solution of the large-scale JSP can be obtained by iteratively solving the sub-problems. In order to improve the sub-problems' solving efficiency and the solution quality, a detection method for multi-bottleneck machines based on critical path is proposed. Therewith the unscheduled operations can be decomposed into bottleneck operations and non-bottleneck operations. According to the principle of “Bottleneck leads the performance of the whole manufacturing system” in TOC (Theory Of Constraints, the bottleneck operations are scheduled by genetic algorithm for high solution quality, and the non-bottleneck operations are scheduled by dispatching rules for the improvement of the solving efficiency.Findings: In the process of the sub-problems' construction, partial operations in the previous scheduled sub-problem are divided into the successive sub-problem for re-optimization. This strategy can improve the solution quality of the algorithm. In the process of solving the sub-problems, the strategy that evaluating the chromosome's fitness by predicting the global scheduling objective value can improve the solution quality.Research limitations/implications: In this research, there are some assumptions which reduce the complexity of the large-scale scheduling problem. They are as follows: The processing route of each job is predetermined, and the processing time of each operation is fixed. There is no machine breakdown, and no preemption of the operations is allowed. The assumptions should be considered if the algorithm is used in the actual job shop.Originality/value: The research provides an efficient scheduling method for the

  15. A novel downlink scheduling strategy for traffic communication system based on TD-LTE technology.

    Science.gov (United States)

    Chen, Ting; Zhao, Xiangmo; Gao, Tao; Zhang, Licheng

    2016-01-01

    There are many existing classical scheduling algorithms which can obtain better system throughput and user equality, however, they are not designed for traffic transportation environment, which cannot consider whether the transmission performance of various information flows could meet comprehensive requirements of traffic safety and delay tolerance. This paper proposes a novel downlink scheduling strategy for traffic communication system based on TD-LTE technology, which can perform two classification mappings for various information flows in the eNodeB: firstly, associate every information flow packet with traffic safety importance weight according to its relevance to the traffic safety; secondly, associate every traffic information flow with service type importance weight according to its quality of service (QoS) requirements. Once the connection is established, at every scheduling moment, scheduler would decide the scheduling order of all buffers' head of line packets periodically according to the instant value of scheduling importance weight function, which calculated by the proposed algorithm. From different scenario simulations, it can be verified that the proposed algorithm can provide superior differentiated transmission service and reliable QoS guarantee to information flows with different traffic safety levels and service types, which is more suitable for traffic transportation environment compared with the existing popularity PF algorithm. With the limited wireless resource, information flow closed related to traffic safety will always obtain priority scheduling right timely, which can help the passengers' journey more safe. Moreover, the proposed algorithm cannot only obtain good flow throughput and user fairness which are almost equal to those of the PF algorithm without significant differences, but also provide better realtime transmission guarantee to realtime information flow.

  16. Optimization-based sale transactions and hydrothermal scheduling

    International Nuclear Information System (INIS)

    Prasannan, B.; Luh, P.B.; Zhang, L.

    1996-01-01

    Selling and purchasing power are important activities for utilities because of potential savings. When a selling utility presents an offer including prices, power levels and durations, a purchasing utility selects power levels and durations within the offered range subject to relevant constraints. The decisionmaking process is complicated because transactions are coupled with system demand and reserve, therefore decisions have to be made in conjunction with the commitment and dispatching of units. Furthermore, transaction decisions have to be made in almost real time in view of the competitiveness of the power market caused by deregulation. In this paper, transactions are analyzed from a selling utility's viewpoint for a system consisting of thermal, hydro and pumped-storage units. To effectively solve the problem, linear sale revenues are approximated by nonlinear functions, and non-profitable options are identified and eliminated from consideration. The multipliers are then updated at the high level by using a modified subgradient method to obtain near optimal solutions quickly. Testing results show that the algorithm produces good sale offers efficiently

  17. Tri-generation based hybrid power plant scheduling for renewable resources rich area with energy storage

    International Nuclear Information System (INIS)

    Pazheri, F.R.

    2015-01-01

    Highlights: • Involves scheduling of the tri-generation based hybrid power plant. • Utilization of renewable energy through energy storage is discussed. • Benefits of the proposed model are illustrated. • Energy efficient and environmental friendly dispatch is analyzed. • Modeled scheduling problem is applicable to any fuel enriched area. - Abstract: Solving power system scheduling is crucial to ensure smooth operations of the electric power industry. Effective utilization of available conventional and renewable energy sources (RES) by tri-generation and with the aid of energy storage facilities (ESF) can ensure clean and energy efficient power generation. Such power generation can play an important role in countries, like Saudi Arabia, where abundant fossil fuels (FF) and renewable energy sources (RES) are available. Hence, effective modeling of such hybrid power systems scheduling is essential in such countries based on the available fuel resources. The intent of this paper is to present a simple model for tri-generation based hybrid power system scheduling for energy resources rich area in presence of ESF, to ensure optimum fuel utilization and minimum pollutant emissions while meeting the power demand. This research points an effective operation strategy which ensure a clean and energy efficient power scheduling by exploiting available energy resources effectively. Hence, it has an important role in current and future power generation. In order to illustrate the benefits of the presented approach a clean and energy efficient hybrid power supply scheme for King Saud University (KSU), Saudi Arabia, is proposed and analyzed here. Results show that the proposed approach is very suitable for KSU since adequate solar power is available during its peak demand periods

  18. The engine maintenance scheduling by using reliability centered maintenance method and the identification of 5S application in PT. XYZ

    Science.gov (United States)

    Sembiring, N.; Panjaitan, N.; Saragih, A. F.

    2018-02-01

    PT. XYZ is a manufacturing company that produces fresh fruit bunches (FFB) to Crude Palm Oil (CPO) and Palm Kernel Oil (PKO). PT. XYZ consists of six work stations: receipt station, sterilizing station, thressing station, pressing station, clarification station, and kernelery station. So far, the company is still implementing corrective maintenance maintenance system for production machines where the machine repair is done after damage occurs. Problems at PT. XYZ is the absence of scheduling engine maintenance in a planned manner resulting in the engine often damaged which can disrupt the smooth production. Another factor that is the problem in this research is the kernel station environment that becomes less convenient for operators such as there are machines and equipment not used in the production area, slippery, muddy, scattered fibers, incomplete use of PPE, and lack of employee discipline. The most commonly damaged machine is in the seed processing station (kernel station) which is cake breaker conveyor machine. The solution of this problem is to propose a schedule plan for maintenance of the machine by using the method of reliability centered maintenance and also the application of 5S. The result of the application of Reliability Centered maintenance method is obtained four components that must be treated scheduled (time directed), namely: for bearing component is 37 days, gearbox component is 97 days, CBC pen component is 35 days and conveyor pedal component is 32 days While after identification the application of 5S obtained the proposed corporate environmental improvement measures in accordance with the principles of 5S where unused goods will be moved from the production area, grouping goods based on their use, determining the procedure of cleaning the production area, conducting inspection in the use of PPE, and making 5S slogans.

  19. Research on Energy-Saving Production Scheduling Based on a Clustering Algorithm for a Forging Enterprise

    Directory of Open Access Journals (Sweden)

    Yifei Tong

    2016-02-01

    Full Text Available Energy efficiency is a buzzword of the 21st century. With the ever growing need for energy efficient and low-carbon production, it is a big challenge for high energy-consumption enterprises to reduce their energy consumption. To this aim, a forging enterprise, DVR (the abbreviation of a forging enterprise, is researched. Firstly, an investigation into the production processes of DVR is given as well as an analysis of forging production. Then, the energy-saving forging scheduling is decomposed into two sub-problems. One is for cutting and machining scheduling, which is similar to traditional machining scheduling. The other one is for forging and heat treatment scheduling. Thirdly, former forging production scheduling is presented and solved based on an improved genetic algorithm. Fourthly, the latter is discussed in detail, followed by proposed dynamic clustering and stacking combination optimization. The proposed stacking optimization requires making the gross weight of forgings as close to the maximum batch capacity as possible. The above research can help reduce the heating times, and increase furnace utilization with high energy efficiency and low carbon emissions.

  20. WGC Based Robust and Gain Scheduling PI Controller Design for Condensing Boilers

    Directory of Open Access Journals (Sweden)

    Cem Onat

    2014-05-01

    Full Text Available This paper addresses the water temperature PI control in condensing domestic boilers. The main challenge of this process under the controller design perspective is the fact that the dynamics of condensing boilers are strongly affected by the demanded water flow rate. First, a robust PI controller based on weighted geometrical center method is designed that stabilizes and achieves good performance for closed-loop system for a wide range of the water flow rate. Then, it is shown that if the water flow rate information is used to update the controller gains, through a technique known as gain scheduled control, the performance can be significantly improved. Important characteristics of these PI design approaches are that the resulting parameters are calculated numerically without using any graphical method or iterative optimization process and that it guarantees the stability of the closed-loop. Significantly, simulation results have demonstrated that the proposed tuning techniques can perform better for set point changes and load disturbance than other available methods in the literature.

  1. Optimal RTP Based Power Scheduling for Residential Load in Smart Grid

    Science.gov (United States)

    Joshi, Hemant I.; Pandya, Vivek J.

    2015-12-01

    To match supply and demand, shifting of load from peak period to off-peak period is one of the effective solutions. Presently flat rate tariff is used in major part of the world. This type of tariff doesn't give incentives to the customers if they use electrical energy during off-peak period. If real time pricing (RTP) tariff is used, consumers can be encouraged to use energy during off-peak period. Due to advancement in information and communication technology, two-way communications is possible between consumers and utility. To implement this technique in smart grid, home energy controller (HEC), smart meters, home area network (HAN) and communication link between consumers and utility are required. HEC interacts automatically by running an algorithm to find optimal energy consumption schedule for each consumer. However, all the consumers are not allowed to shift their load simultaneously during off-peak period to avoid rebound peak condition. Peak to average ratio (PAR) is considered while carrying out minimization problem. Linear programming problem (LPP) method is used for minimization. The simulation results of this work show the effectiveness of the minimization method adopted. The hardware work is in progress and the program based on the method described here will be made to solve real problem.

  2. Generation and Demand Scheduling for a Grid-Connected Hybrid Microgrid Considering Price-based Incentives

    DEFF Research Database (Denmark)

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

    2017-01-01

    Microgrids rely on energy management levels to optimally schedule their components. Conventionally, the research in this field has been focused on the optimal formulation of the generation or the demand side management separately without considering real case scenarios and validated only...... by simulation. This paper presents the power scheduling of a real site microgrid under a price-based demand response program defined in Shanghai, China managing generation and demand simultaneously. The proposed optimization problem aims to minimize operating cost by managing renewable energy sources as well...

  3. A Framework for Uplink Intercell Interference Modeling with Channel-Based Scheduling

    KAUST Repository

    Tabassum, Hina

    2012-12-29

    This paper presents a novel framework for modeling the uplink intercell interference(ICI) in a multiuser cellular network. The proposed framework assists in quantifying the impact of various fading channel models and state-of-the-art scheduling schemes on the uplink ICI. Firstly, we derive a semianalytical expression for the distribution of the location of the scheduled user in a given cell considering a wide range of scheduling schemes. Based on this, we derive the distribution and moment generating function (MGF) of the uplink ICI considering a single interfering cell. Consequently, we determine the MGF of the cumulative ICI observed from all interfering cells and derive explicit MGF expressions for three typical fading models. Finally, we utilize the obtained expressions to evaluate important network performance metrics such as the outage probability, ergodic capacity, and average fairness numerically. Monte-Carlo simulation results are provided to demonstrate the efficacy of the derived analytical expressions.

  4. A genetic algorithm-based job scheduling model for big data analytics.

    Science.gov (United States)

    Lu, Qinghua; Li, Shanshan; Zhang, Weishan; Zhang, Lei

    Big data analytics (BDA) applications are a new category of software applications that process large amounts of data using scalable parallel processing infrastructure to obtain hidden value. Hadoop is the most mature open-source big data analytics framework, which implements the MapReduce programming model to process big data with MapReduce jobs. Big data analytics jobs are often continuous and not mutually separated. The existing work mainly focuses on executing jobs in sequence, which are often inefficient and consume high energy. In this paper, we propose a genetic algorithm-based job scheduling model for big data analytics applications to improve the efficiency of big data analytics. To implement the job scheduling model, we leverage an estimation module to predict the performance of clusters when executing analytics jobs. We have evaluated the proposed job scheduling model in terms of feasibility and accuracy.

  5. Evaluating Visual Activity Schedules as Evidence-Based Practice for Individuals with Autism Spectrum Disorders

    Science.gov (United States)

    Knight, Victoria; Sartini, Emily; Spriggs, Amy D.

    2015-01-01

    A comprehensive review of the literature was conducted for articles published between 1993 and 2013 to evaluate the quality of the Visual Activity Schedules (VAS) literature using current evidence-based criteria developed by Horner et al. (Except Child 71:165-179, 2005). Authors sought to determine whether VAS can be considered an evidence-based…

  6. Examination of the Evidence Base for Using Visual Activity Schedules with Students with Intellectual Disability

    Science.gov (United States)

    Spriggs, Amy D.; Mims, Pamela J.; van Dijk, Wilhelmina; Knight, Victoria F.

    2017-01-01

    We conducted a comprehensive review of the literature to establish the evidence base for using visual activity schedules (VAS) with individuals with intellectual disability. Literature published after 2005 was evaluated for quality using the criteria developed by Horner et al.; a total of 14 studies were included as acceptable. Findings suggest…

  7. A Graph-Based Approach to Action Scheduling in a Parallel Database System

    NARCIS (Netherlands)

    Grefen, P.W.P.J.; Apers, Peter M.G.

    Parallel database machines are meant to obtain high performance in transaction processing, both in terms of response time adn throughput. To obtain high performance, a good scheduling of the execution of the various actions in transactions is crucial. This paper describes a graph-based technique for

  8. Improved irrigation scheduling for pear-jujube trees based on trunk ...

    African Journals Online (AJOL)

    A suitable indicator for scheduling pear-jujube (Ziziphus jujuba Mill.) irrigation in China was developed based on trunk diameter fluctuations (TDF). Parameters derived from TDF responses to variations in soil matrix potential (Ψsoil) were compared under deficit and well irrigation. Maximum daily shrinkage (MDS) increased ...

  9. CP Methods for Scheduling and Routing with Time-Dependent Task Costs

    DEFF Research Database (Denmark)

    Tierney, Kevin; Kelareva, Elena; Kilby, Philip

    2013-01-01

    a cost function, and Mixed Integer Programming (MIP) are often used for solving such problems. However, Constraint Programming (CP), particularly with Lazy Clause Genera- tion (LCG), has been found to be faster than MIP for some scheduling problems with time-varying action costs. In this paper, we...... compare CP and LCG against a solve-and-improve approach for two recently introduced problems in maritime logistics with time-varying action costs: the Liner Shipping Fleet Repositioning Problem (LSFRP) and the Bulk Port Cargo Throughput Optimisation Problem (BPCTOP). We present a novel CP model...... for the LSFRP, which is faster than all previous methods and outperforms a simplified automated planning model without time-varying costs. We show that a LCG solver is faster for solving the BPCTOP than a standard finite domain CP solver with a simplified model. We find that CP and LCG are effective methods...

  10. Manufacturing scheduling systems an integrated view on models, methods and tools

    CERN Document Server

    Framinan, Jose M; Ruiz García, Rubén

    2014-01-01

    The book is devoted to the problem of manufacturing scheduling, which is the efficient allocation of jobs (orders) over machines (resources) in a manufacturing facility. It offers a comprehensive and integrated perspective on the different aspects required to design and implement systems to efficiently and effectively support manufacturing scheduling decisions. Obtaining economic and reliable schedules constitutes the core of excellence in customer service and efficiency in manufacturing operations. Therefore, scheduling forms an area of vital importance for competition in manufacturing companies. However, only a fraction of scheduling research has been translated into practice, due to several reasons. First, the inherent complexity of scheduling has led to an excessively fragmented field in which different sub problems and issues are treated in an independent manner as goals themselves, therefore lacking a unifying view of the scheduling problem. Furthermore, mathematical brilliance and elegance has sometime...

  11. Scheduling of House Development Projects with CPM and PERT Method for Time Efficiency (Case Study: House Type 36)

    Science.gov (United States)

    Kholil, Muhammad; Nurul Alfa, Bonitasari; Hariadi, Madjumsyah

    2018-04-01

    Network planning is one of the management techniques used to plan and control the implementation of a project, which shows the relationship between activities. The objective of this research is to arrange network planning on house construction project on CV. XYZ and to know the role of network planning in increasing the efficiency of time so that can be obtained the optimal project completion period. This research uses descriptive method, where the data collected by direct observation to the company, interview, and literature study. The result of this research is optimal time planning in project work. Based on the results of the research, it can be concluded that the use of the both methods in scheduling of house construction project gives very significant effect on the completion time of the project. The company’s CPM (Critical Path Method) method can complete the project with 131 days, PERT (Program Evaluation Review and Technique) Method takes 136 days. Based on PERT calculation obtained Z = -0.66 or 0,2546 (from normal distribution table), and also obtained the value of probability or probability is 74,54%. This means that the possibility of house construction project activities can be completed on time is high enough. While without using both methods the project completion time takes 173 days. So using the CPM method, the company can save time up to 42 days and has time efficiency by using network planning.

  12. Hybrid LSA-ANN Based Home Energy Management Scheduling Controller for Residential Demand Response Strategy

    Directory of Open Access Journals (Sweden)

    Maytham S. Ahmed

    2016-09-01

    Full Text Available Demand response (DR program can shift peak time load to off-peak time, thereby reducing greenhouse gas emissions and allowing energy conservation. In this study, the home energy management scheduling controller of the residential DR strategy is proposed using the hybrid lightning search algorithm (LSA-based artificial neural network (ANN to predict the optimal ON/OFF status for home appliances. Consequently, the scheduled operation of several appliances is improved in terms of cost savings. In the proposed approach, a set of the most common residential appliances are modeled, and their activation is controlled by the hybrid LSA-ANN based home energy management scheduling controller. Four appliances, namely, air conditioner, water heater, refrigerator, and washing machine (WM, are developed by Matlab/Simulink according to customer preferences and priority of appliances. The ANN controller has to be tuned properly using suitable learning rate value and number of nodes in the hidden layers to schedule the appliances optimally. Given that finding proper ANN tuning parameters is difficult, the LSA optimization is hybridized with ANN to improve the ANN performances by selecting the optimum values of neurons in each hidden layer and learning rate. Therefore, the ON/OFF estimation accuracy by ANN can be improved. Results of the hybrid LSA-ANN are compared with those of hybrid particle swarm optimization (PSO based ANN to validate the developed algorithm. Results show that the hybrid LSA-ANN outperforms the hybrid PSO based ANN. The proposed scheduling algorithm can significantly reduce the peak-hour energy consumption during the DR event by up to 9.7138% considering four appliances per 7-h period.

  13. A derived heuristics based multi-objective optimization procedure for micro-grid scheduling

    Science.gov (United States)

    Li, Xin; Deb, Kalyanmoy; Fang, Yanjun

    2017-06-01

    With the availability of different types of power generators to be used in an electric micro-grid system, their operation scheduling as the load demand changes with time becomes an important task. Besides satisfying load balance constraints and the generator's rated power, several other practicalities, such as limited availability of grid power and restricted ramping of power output from generators, must all be considered during the operation scheduling process, which makes it difficult to decide whether the optimization results are accurate and satisfactory. In solving such complex practical problems, heuristics-based customized optimization algorithms are suggested. However, due to nonlinear and complex interactions of variables, it is difficult to come up with heuristics in such problems off-hand. In this article, a two-step strategy is proposed in which the first task deciphers important heuristics about the problem and the second task utilizes the derived heuristics to solve the original problem in a computationally fast manner. Specifically, the specific operation scheduling is considered from a two-objective (cost and emission) point of view. The first task develops basic and advanced level knowledge bases offline from a series of prior demand-wise optimization runs and then the second task utilizes them to modify optimized solutions in an application scenario. Results on island and grid connected modes and several pragmatic formulations of the micro-grid operation scheduling problem clearly indicate the merit of the proposed two-step procedure.

  14. A priority-based heuristic algorithm (PBHA for optimizing integrated process planning and scheduling problem

    Directory of Open Access Journals (Sweden)

    Muhammad Farhan Ausaf

    2015-12-01

    Full Text Available Process planning and scheduling are two important components of a manufacturing setup. It is important to integrate them to achieve better global optimality and improved system performance. To find optimal solutions for integrated process planning and scheduling (IPPS problem, numerous algorithm-based approaches exist. Most of these approaches try to use existing meta-heuristic algorithms for solving the IPPS problem. Although these approaches have been shown to be effective in optimizing the IPPS problem, there is still room for improvement in terms of quality of solution and algorithm efficiency, especially for more complicated problems. Dispatching rules have been successfully utilized for solving complicated scheduling problems, but haven’t been considered extensively for the IPPS problem. This approach incorporates dispatching rules with the concept of prioritizing jobs, in an algorithm called priority-based heuristic algorithm (PBHA. PBHA tries to establish job and machine priority for selecting operations. Priority assignment and a set of dispatching rules are simultaneously used to generate both the process plans and schedules for all jobs and machines. The algorithm was tested for a series of benchmark problems. The proposed algorithm was able to achieve superior results for most complex problems presented in recent literature while utilizing lesser computational resources.

  15. Machine Maintenance Scheduling with Reliability Engineering Method and Maintenance Value Stream Mapping

    Science.gov (United States)

    Sembiring, N.; Nasution, A. H.

    2018-02-01

    Corrective maintenance i.e replacing or repairing the machine component after machine break down always done in a manufacturing company. It causes the production process must be stopped. Production time will decrease due to the maintenance team must replace or repair the damage machine component. This paper proposes a preventive maintenance’s schedule for a critical component of a critical machine of an crude palm oil and kernel company due to increase maintenance efficiency. The Reliability Engineering & Maintenance Value Stream Mapping is used as a method and a tool to analize the reliability of the component and reduce the wastage in any process by segregating value added and non value added activities.

  16. A comparison of two exact methods for passenger railway rolling stock (re)scheduling

    DEFF Research Database (Denmark)

    Haahr, Jørgen Thorlund; Wagenaar, Joris C.; Veelenturf, Lucas P.

    2016-01-01

    The assignment of rolling stock units to timetable services in passenger railways is an important optimization problem that has been addressed by many papers in different forms. Solution approaches have been proposed for different planning phases: strategic, tactical, operational, and real...... is solved using a column and row generation approach. In this paper, we benchmark the performance of the methods on networks of two countries (Denmark and The Netherlands). We use the approaches to make daily schedules and we test their real time applicability by performing tests with different disruption...... scenarios. The computational experiments demonstrate that both models can be used on both networks and are able to find optimal rolling stock circulations in the different planning phases. Furthermore, the results show that both approaches are sufficiently fast to be used in a real-time setting....

  17. MULTISHAPE TASK SCHEDULING ALGORITHM FOR REAL TIME MICRO-CONTROLLER BASED APPLICATION

    OpenAIRE

    Ankur Jain

    2017-01-01

    Embedded Systems are usually microcontroller-based systems that represent a class of reliable and dependable dedicated computer systems designed for specific purposes. Micro-controllers are used in most electronic devices in an endless variety of ways. Some micro-controller-based embedded systems are required to respond to external events in the shortest possible time and such systems are known as realtime embedded systems. So in multitasking system there is a need of task Scheduling, there a...

  18. The impact of exposure to shift-based schedules on medical students

    Directory of Open Access Journals (Sweden)

    David A. Williams

    2015-06-01

    Full Text Available Background: With new resident duty-hour regulations, resident work schedules have progressively transitioned towards shift-based systems, sometimes resulting in increased team fragmentation. We hypothesized that exposure to shift-based schedules and subsequent team fragmentation would negatively affect medical student experiences during their third-year internal medicine clerkship. Design: As part of a larger national study on duty-hour reform, 67 of 150 eligible third-year medical students completed surveys about career choice, teaching and supervision, assessment, patient care, well-being, and attractiveness of a career in internal medicine after completing their internal medicine clerkship. Students who rotated to hospitals with shift-based systems were compared to those who did not. Non-demographic variables used a five-point Likert scale. Chi-squared and Fisher's exact tests were used to assess the relationships between exposure to shift-based schedules and student responses. Questions with univariate p≤0.1 were included in multivariable logistic regression models. Results: Thirty-six students (54% were exposed to shift-based schedules. Students exposed to shift-based schedules were less likely to perceive that their attendings were committed to teaching (odds ratio [OR] 0.35, 95% confidence interval [CI]: 0.13–0.90, p=0.01 or perceive that residents had sufficient exposure to assess their performance (OR 0.29, 95% CI: 0.09–0.91, p=0.03. However, those students were more likely to feel their interns were able to observe them at the bedside (OR 1.89, 95% CI: 1.08–3.13, p=0.02 and had sufficient exposure to assess their performance (OR 3.00, 95% CI: 1.01–8.86, p=0.05. Conclusions: These findings suggest that shift-based schedules designed in response to duty-hour reform may have important broader implications for the teaching environment.

  19. Stochastic profit-based scheduling of industrial virtual power plant using the best demand response strategy

    International Nuclear Information System (INIS)

    Nosratabadi, Seyyed Mostafa; Hooshmand, Rahmat-Allah; Gholipour, Eskandar

    2016-01-01

    Highlights: • VPPs and IVPPs are defined for energy management of aggregated generations. • IVPP can manage industrial microgrid containing some relevant load and generation. • A stochastic modeling is proposed to schedule optimal generations in competition market. • Wind generation and day-ahead and spot market prices are considered to be stochastic. • A new DRL program selection scheme is presented in the scheduling procedure. - Abstract: One of the main classified microgrids in a power system is the industrial microgrid. Due to its behaviors and the heavy loads, its energy management is challengeable. Virtual Power Plant (VPP) can be an important concept in managing such problems in this kind of grids. Here, a transmission power system is considered as a Regional Electric Company (REC) and the VPPs comprising Distributed Generation (DG) units and Demand Response Loads (DRLs) are determined in this system. This paper focuses on Industrial VPP (IVPP) and its management. An IVPP can be determined as a management unit comprising generations and loads in an industrial microgrid. Since the scheduling procedure for these units is very important for their participation in a short-term electric market, a stochastic formulation is proposed for power scheduling in VPPs especially in IVPPs in this paper. By introducing the DRL programs and using the proposed modeling, the operator can select the best DRL program for each VPP in a scheduling procedure. In this regard, a suitable approach is presented to determine the proposed formulation and its solution in a Mixed Integer Non-Linear Programming (MINLP). To validate the performance of the proposed method, the IEEE Reliability Test System (IEEE-RTS) is considered to apply the method on it, while some challenging aspects are presented.

  20. Load Balancing Integrated Least Slack Time-Based Appliance Scheduling for Smart Home Energy Management

    Science.gov (United States)

    Silva, Bhagya Nathali; Khan, Murad; Han, Kijun

    2018-01-01

    The emergence of smart devices and smart appliances has highly favored the realization of the smart home concept. Modern smart home systems handle a wide range of user requirements. Energy management and energy conservation are in the spotlight when deploying sophisticated smart homes. However, the performance of energy management systems is highly influenced by user behaviors and adopted energy management approaches. Appliance scheduling is widely accepted as an effective mechanism to manage domestic energy consumption. Hence, we propose a smart home energy management system that reduces unnecessary energy consumption by integrating an automated switching off system with load balancing and appliance scheduling algorithm. The load balancing scheme acts according to defined constraints such that the cumulative energy consumption of the household is managed below the defined maximum threshold. The scheduling of appliances adheres to the least slack time (LST) algorithm while considering user comfort during scheduling. The performance of the proposed scheme has been evaluated against an existing energy management scheme through computer simulation. The simulation results have revealed a significant improvement gained through the proposed LST-based energy management scheme in terms of cost of energy, along with reduced domestic energy consumption facilitated by an automated switching off mechanism. PMID:29495346

  1. Compositional schedulability analysis of real-time actor-based systems.

    Science.gov (United States)

    Jaghoori, Mohammad Mahdi; de Boer, Frank; Longuet, Delphine; Chothia, Tom; Sirjani, Marjan

    2017-01-01

    We present an extension of the actor model with real-time, including deadlines associated with messages, and explicit application-level scheduling policies, e.g.,"earliest deadline first" which can be associated with individual actors. Schedulability analysis in this setting amounts to checking whether, given a scheduling policy for each actor, every task is processed within its designated deadline. To check schedulability, we introduce a compositional automata-theoretic approach, based on maximal use of model checking combined with testing. Behavioral interfaces define what an actor expects from the environment, and the deadlines for messages given these assumptions. We use model checking to verify that actors match their behavioral interfaces. We extend timed automata refinement with the notion of deadlines and use it to define compatibility of actor environments with the behavioral interfaces. Model checking of compatibility is computationally hard, so we propose a special testing process. We show that the analyses are decidable and automate the process using the Uppaal model checker.

  2. Load Balancing Integrated Least Slack Time-Based Appliance Scheduling for Smart Home Energy Management

    Directory of Open Access Journals (Sweden)

    Bhagya Nathali Silva

    2018-02-01

    Full Text Available The emergence of smart devices and smart appliances has highly favored the realization of the smart home concept. Modern smart home systems handle a wide range of user requirements. Energy management and energy conservation are in the spotlight when deploying sophisticated smart homes. However, the performance of energy management systems is highly influenced by user behaviors and adopted energy management approaches. Appliance scheduling is widely accepted as an effective mechanism to manage domestic energy consumption. Hence, we propose a smart home energy management system that reduces unnecessary energy consumption by integrating an automated switching off system with load balancing and appliance scheduling algorithm. The load balancing scheme acts according to defined constraints such that the cumulative energy consumption of the household is managed below the defined maximum threshold. The scheduling of appliances adheres to the least slack time (LST algorithm while considering user comfort during scheduling. The performance of the proposed scheme has been evaluated against an existing energy management scheme through computer simulation. The simulation results have revealed a significant improvement gained through the proposed LST-based energy management scheme in terms of cost of energy, along with reduced domestic energy consumption facilitated by an automated switching off mechanism.

  3. Load Balancing Integrated Least Slack Time-Based Appliance Scheduling for Smart Home Energy Management.

    Science.gov (United States)

    Silva, Bhagya Nathali; Khan, Murad; Han, Kijun

    2018-02-25

    The emergence of smart devices and smart appliances has highly favored the realization of the smart home concept. Modern smart home systems handle a wide range of user requirements. Energy management and energy conservation are in the spotlight when deploying sophisticated smart homes. However, the performance of energy management systems is highly influenced by user behaviors and adopted energy management approaches. Appliance scheduling is widely accepted as an effective mechanism to manage domestic energy consumption. Hence, we propose a smart home energy management system that reduces unnecessary energy consumption by integrating an automated switching off system with load balancing and appliance scheduling algorithm. The load balancing scheme acts according to defined constraints such that the cumulative energy consumption of the household is managed below the defined maximum threshold. The scheduling of appliances adheres to the least slack time (LST) algorithm while considering user comfort during scheduling. The performance of the proposed scheme has been evaluated against an existing energy management scheme through computer simulation. The simulation results have revealed a significant improvement gained through the proposed LST-based energy management scheme in terms of cost of energy, along with reduced domestic energy consumption facilitated by an automated switching off mechanism.

  4. Proportional fair scheduling algorithm based on traffic in satellite communication system

    Science.gov (United States)

    Pan, Cheng-Sheng; Sui, Shi-Long; Liu, Chun-ling; Shi, Yu-Xin

    2018-02-01

    In the satellite communication network system, in order to solve the problem of low system capacity and user fairness in multi-user access to satellite communication network in the downlink, combined with the characteristics of user data service, an algorithm study on throughput capacity and user fairness scheduling is proposed - Proportional Fairness Algorithm Based on Traffic(B-PF). The algorithm is improved on the basis of the proportional fairness algorithm in the wireless communication system, taking into account the user channel condition and caching traffic information. The user outgoing traffic is considered as the adjustment factor of the scheduling priority and presents the concept of traffic satisfaction. Firstly,the algorithm calculates the priority of the user according to the scheduling algorithm and dispatches the users with the highest priority. Secondly, when a scheduled user is the business satisfied user, the system dispatches the next priority user. The simulation results show that compared with the PF algorithm, B-PF can improve the system throughput, the business satisfaction and fairness.

  5. A Decision Support System Based on Genetic Algorithm (Case Study: Scheduling in Supply Chain

    Directory of Open Access Journals (Sweden)

    Mohammad Ali Beheheshtinia

    2016-10-01

    Full Text Available Nowadays, the application of effective and efficient decisions on complex issues require the use of decision support systems. This Paper provided a decision support system based on the genetic algorithm for production and transportation scheduling problem in a supply chain. It is assumed that there are number of orders that should be produced by suppliers and should be transported to the plant by a transportation fleet. The aim is to assign orders to the suppliers, specify the order of their production, allocate processed orders to the vehicles for transport and to arrange them in a way that minimizes the total delivery time. It has been shown that the complexity of the problem was related to Np-hard and there was no possibility of using accurate methods to solve the problem in a reasonable time. So, the genetic algorithm was used in this paper to solve the problem. By using this decision support system, a new approach to supply chain management was proposed. The analysis of the approach proposed in this study compared to the conventional approaches by the decision support system indicated the preference of our proposed approach

  6. Nonstandard Work Schedules, Couple Desynchronization, and Parent-Child Interaction : A Mixed-Methods Analysis

    NARCIS (Netherlands)

    Taeht, Kadri; Mills, Melinda

    Many children live in households where either one or both parents work nonstandard schedules in the evening, night, or weekend. This study tests two competing hypotheses of whether nonstandard schedules result in lower levels of parent-child interaction or in more time with children. Using the first

  7. A review of scheduling problem and resolution methods in flexible flow shop

    Directory of Open Access Journals (Sweden)

    Tian-Soon Lee

    2019-01-01

    Full Text Available The Flexible flow shop (FFS is defined as a multi-stage flow shops with multiple parallel machines. FFS scheduling problem is a complex combinatorial problem which has been intensively studied in many real world industries. This review paper gives a comprehensive exploration review on the FFS scheduling problem and guides the reader by considering and understanding different environmental assumptions, system constraints and objective functions for future research works. The published papers are classified into two categories. First is the FFS system characteristics and constraints including the problem differences and limitation defined by different studies. Second, the scheduling performances evaluation are elaborated and categorized into time, job and multi related objectives. In addition, the resolution approaches that have been used to solve FFS scheduling problems are discussed. This paper gives a comprehensive guide for the reader with respect to future research work on the FFS scheduling problem.

  8. Hypergraph+: An Improved Hypergraph-Based Task-Scheduling Algorithm for Massive Spatial Data Processing on Master-Slave Platforms

    Directory of Open Access Journals (Sweden)

    Bo Cheng

    2016-08-01

    Full Text Available Spatial data processing often requires massive datasets, and the task/data scheduling efficiency of these applications has an impact on the overall processing performance. Among the existing scheduling strategies, hypergraph-based algorithms capture the data sharing pattern in a global way and significantly reduce total communication volume. Due to heterogeneous processing platforms, however, single hypergraph partitioning for later scheduling may be not optimal. Moreover, these scheduling algorithms neglect the overlap between task execution and data transfer that could further decrease execution time. In order to address these problems, an extended hypergraph-based task-scheduling algorithm, named Hypergraph+, is proposed for massive spatial data processing. Hypergraph+ improves upon current hypergraph scheduling algorithms in two ways: (1 It takes platform heterogeneity into consideration offering a metric function to evaluate the partitioning quality in order to derive the best task/file schedule; and (2 It can maximize the overlap between communication and computation. The GridSim toolkit was used to evaluate Hypergraph+ in an IDW spatial interpolation application on heterogeneous master-slave platforms. Experiments illustrate that the proposed Hypergraph+ algorithm achieves on average a 43% smaller makespan than the original hypergraph scheduling algorithm but still preserves high scheduling efficiency.

  9. A Bayesian matching pursuit based scheduling algorithm for feedback reduction in MIMO broadcast channels

    KAUST Repository

    Shibli, Hussain J.

    2013-06-01

    Opportunistic schedulers rely on the feedback of all users in order to schedule a set of users with favorable channel conditions. While the downlink channels can be easily estimated at all user terminals via a single broadcast, several key challenges are faced during uplink transmission. First of all, the statistics of the noisy and fading feedback channels are unknown at the base station (BS) and channel training is usually required from all users. Secondly, the amount of network resources (air-time) required for feedback transmission grows linearly with the number of users. In this paper, we tackle the above challenges and propose a Bayesian based scheduling algorithm that 1) reduces the air-time required to identify the strong users, and 2) is agnostic to the statistics of the feedback channels and utilizes the a priori statistics of the additive noise to identify the strong users. Numerical results show that the proposed algorithm reduces the feedback air-time while improving detection in the presence of fading and noisy channels when compared to recent compressed sensing based algorithms. Furthermore, the proposed algorithm achieves a sum-rate throughput close to that obtained by noiseless dedicated feedback systems. © 2013 IEEE.

  10. Effects of gain-scheduling methods in a classical wind turbine controller on wind turbine aeroservoelastic modes and loads

    DEFF Research Database (Denmark)

    Tibaldi, Carlo; Henriksen, Lars Christian; Hansen, Morten Hartvig

    2014-01-01

    The eects of dierent gain-scheduling methods for a classical wind turbine controller, operating in full load region, on the wind turbine aeroservoelastic modes and loads are investigated in this work. The dierent techniques are derived looking at the physical problem to take into account the chan......The eects of dierent gain-scheduling methods for a classical wind turbine controller, operating in full load region, on the wind turbine aeroservoelastic modes and loads are investigated in this work. The dierent techniques are derived looking at the physical problem to take into account...

  11. COMPARISON BETWEEN MIXED INTEGER PROGRAMMING WITH HEURISTIC METHOD FOR JOB SHOP SCHEDULING WITH SEPARABLE SEQUENCE-DEPENDENT SETUPS

    Directory of Open Access Journals (Sweden)

    I Gede Agus Widyadana

    2001-01-01

    Full Text Available The decisions to choose appropriate tools for solving industrial problems are not just tools that achieve optimal solution only but it should consider computation time too. One of industrial problems that still difficult to achieve both criteria is scheduling problem. This paper discuss comparison between mixed integer programming which result optimal solution and heuristic method to solve job shop scheduling problem with separable sequence-dependent setup. The problems are generated and the result shows that the heuristic methods still cannot satisfy optimal solution.

  12. A Hyper-Heuristic Ensemble Method for Static Job-Shop Scheduling.

    Science.gov (United States)

    Hart, Emma; Sim, Kevin

    2016-01-01

    We describe a new hyper-heuristic method NELLI-GP for solving job-shop scheduling problems (JSSP) that evolves an ensemble of heuristics. The ensemble adopts a divide-and-conquer approach in which each heuristic solves a unique subset of the instance set considered. NELLI-GP extends an existing ensemble method called NELLI by introducing a novel heuristic generator that evolves heuristics composed of linear sequences of dispatching rules: each rule is represented using a tree structure and is itself evolved. Following a training period, the ensemble is shown to outperform both existing dispatching rules and a standard genetic programming algorithm on a large set of new test instances. In addition, it obtains superior results on a set of 210 benchmark problems from the literature when compared to two state-of-the-art hyper-heuristic approaches. Further analysis of the relationship between heuristics in the evolved ensemble and the instances each solves provides new insights into features that might describe similar instances.

  13. Null Space Based Preemptive Scheduling For Joint URLLC and eMBB Traffic in 5G Networks

    DEFF Research Database (Denmark)

    Abdul-Mawgood Ali Ali Esswie, Ali; Pedersen, Klaus

    2018-01-01

    In this paper, we propose a null-space-based preemptive scheduling framework for cross-objective optimization to always guarantee robust URLLC performance, while extracting the maximum possible eMBB capacity. The proposed scheduler perpetually grants incoming URLLC traffic a higher priority for i...

  14. Weighted-Bit-Flipping-Based Sequential Scheduling Decoding Algorithms for LDPC Codes

    Directory of Open Access Journals (Sweden)

    Qing Zhu

    2013-01-01

    Full Text Available Low-density parity-check (LDPC codes can be applied in a lot of different scenarios such as video broadcasting and satellite communications. LDPC codes are commonly decoded by an iterative algorithm called belief propagation (BP over the corresponding Tanner graph. The original BP updates all the variable-nodes simultaneously, followed by all the check-nodes simultaneously as well. We propose a sequential scheduling algorithm based on weighted bit-flipping (WBF algorithm for the sake of improving the convergence speed. Notoriously, WBF is a low-complexity and simple algorithm. We combine it with BP to obtain advantages of these two algorithms. Flipping function used in WBF is borrowed to determine the priority of scheduling. Simulation results show that it can provide a good tradeoff between FER performance and computation complexity for short-length LDPC codes.

  15. Cloud computing task scheduling strategy based on differential evolution and ant colony optimization

    Science.gov (United States)

    Ge, Junwei; Cai, Yu; Fang, Yiqiu

    2018-05-01

    This paper proposes a task scheduling strategy DEACO based on the combination of Differential Evolution (DE) and Ant Colony Optimization (ACO), aiming at the single problem of optimization objective in cloud computing task scheduling, this paper combines the shortest task completion time, cost and load balancing. DEACO uses the solution of the DE to initialize the initial pheromone of ACO, reduces the time of collecting the pheromone in ACO in the early, and improves the pheromone updating rule through the load factor. The proposed algorithm is simulated on cloudsim, and compared with the min-min and ACO. The experimental results show that DEACO is more superior in terms of time, cost, and load.

  16. A Simulated Annealing-Based Heuristic Algorithm for Job Shop Scheduling to Minimize Lateness

    Directory of Open Access Journals (Sweden)

    Rui Zhang

    2013-04-01

    Full Text Available A decomposition-based optimization algorithm is proposed for solving large job shop scheduling problems with the objective of minimizing the maximum lateness. First, we use the constraint propagation theory to derive the orientation of a portion of disjunctive arcs. Then we use a simulated annealing algorithm to find a decomposition policy which satisfies the maximum number of oriented disjunctive arcs. Subsequently, each subproblem (corresponding to a subset of operations as determined by the decomposition policy is successively solved with a simulated annealing algorithm, which leads to a feasible solution to the original job shop scheduling problem. Computational experiments are carried out for adapted benchmark problems, and the results show the proposed algorithm is effective and efficient in terms of solution quality and time performance.

  17. Rolling scheduling of electric power system with wind power based on improved NNIA algorithm

    Science.gov (United States)

    Xu, Q. S.; Luo, C. J.; Yang, D. J.; Fan, Y. H.; Sang, Z. X.; Lei, H.

    2017-11-01

    This paper puts forth a rolling modification strategy for day-ahead scheduling of electric power system with wind power, which takes the operation cost increment of unit and curtailed wind power of power grid as double modification functions. Additionally, an improved Nondominated Neighbor Immune Algorithm (NNIA) is proposed for solution. The proposed rolling scheduling model has further improved the operation cost of system in the intra-day generation process, enhanced the system’s accommodation capacity of wind power, and modified the key transmission section power flow in a rolling manner to satisfy the security constraint of power grid. The improved NNIA algorithm has defined an antibody preference relation model based on equal incremental rate, regulation deviation constraints and maximum & minimum technical outputs of units. The model can noticeably guide the direction of antibody evolution, and significantly speed up the process of algorithm convergence to final solution, and enhance the local search capability.

  18. HOROPLAN: computer-assisted nurse scheduling using constraint-based programming.

    Science.gov (United States)

    Darmoni, S J; Fajner, A; Mahé, N; Leforestier, A; Vondracek, M; Stelian, O; Baldenweck, M

    1995-01-01

    Nurse scheduling is a difficult and time consuming task. The schedule has to determine the day to day shift assignments of each nurse for a specified period of time in a way that satisfies the given requirements as much as possible, taking into account the wishes of nurses as closely as possible. This paper presents a constraint-based, artificial intelligence approach by describing a prototype implementation developed with the Charme language and the first results of its use in the Rouen University Hospital. Horoplan implements a non-cyclical constraint-based scheduling, using some heuristics. Four levels of constraints were defined to give a maximum of flexibility: French level (e.g. number of worked hours in a year), hospital level (e.g. specific day-off), department level (e.g. specific shift) and care unit level (e.g. specific pattern for week-ends). Some constraints must always be verified and can not be overruled and some constraints can be overruled at a certain cost. Rescheduling is possible at any time specially in case of an unscheduled absence.

  19. Action dependent heuristic dynamic programming based residential energy scheduling with home energy inter-exchange

    International Nuclear Information System (INIS)

    Xu, Yancai; Liu, Derong; Wei, Qinglai

    2015-01-01

    Highlights: • The algorithm is developed in the two-household energy management environment. • We develop the absent energy penalty cost for the first time. • The algorithm has ability to keep adapting in real-time operations. • Its application can lower total costs and achieve better load balancing. - Abstract: Residential energy scheduling is a hot topic nowadays in the background of energy saving and environmental protection worldwide. To achieve this objective, a new residential energy scheduling algorithm is developed for energy management, based on action dependent heuristic dynamic programming. The algorithm works under the circumstance of residential real-time pricing and two adjacent housing units with energy inter-exchange, which can reduce the overall cost and enhance renewable energy efficiency after long-term operation. It is designed to obtain the optimal control policy to manage the directions and amounts of electricity energy flux. The algorithm’s architecture is mainly constructed based on neural networks, denoting the learned characteristics in the linkage of layers. To get close to real situations, many constraints such as maximum charging/discharging power of batteries are taken into account. The absent energy penalty cost is developed for the first time as a part of the performance index function. When the environment changes, the residential energy scheduling algorithm gains new features and keeps adapting in real-time operations. Simulation results show that the developed algorithm is beneficial to energy conversation

  20. An Entropy-Based Upper Bound Methodology for Robust Predictive Multi-Mode RCPSP Schedules

    Directory of Open Access Journals (Sweden)

    Angela Hsiang-Ling Chen

    2014-09-01

    Full Text Available Projects are an important part of our activities and regardless of their magnitude, scheduling is at the very core of every project. In an ideal world makespan minimization, which is the most commonly sought objective, would give us an advantage. However, every time we execute a project we have to deal with uncertainty; part of it coming from known sources and part remaining unknown until it affects us. For this reason, it is much more practical to focus on making our schedules robust, capable of handling uncertainty, and even to determine a range in which the project could be completed. In this paper we focus on an approach to determine such a range for the Multi-mode Resource Constrained Project Scheduling Problem (MRCPSP, a widely researched, NP-complete problem, but without adding any subjective considerations to its estimation. We do this by using a concept well known in the domain of thermodynamics, entropy and a three-stage approach. First we use Artificial Bee Colony (ABC—an effective and powerful meta-heuristic—to determine a schedule with minimized makespan which serves as a lower bound. The second stage defines buffer times and creates an upper bound makespan using an entropy function, with the advantage over other methods that it only considers elements which are inherent to the schedule itself and does not introduce any subjectivity to the buffer time generation. In the last stage, we use the ABC algorithm with an objective function that seeks to maximize robustness while staying within the makespan boundaries defined previously and in some cases even below the lower boundary. We evaluate our approach with two different benchmarks sets: when using the PSPLIB for the MRCPSP benchmark set, the computational results indicate that it is possible to generate robust schedules which generally result in an increase of less than 10% of the best known solutions while increasing the robustness in at least 20% for practically every

  1. An Effective Scheduling-Based RFID Reader Collision Avoidance Model and Its Resource Allocation via Artificial Immune Network

    Directory of Open Access Journals (Sweden)

    Shanjin Wang

    2016-01-01

    Full Text Available Radio frequency identification, that is, RFID, is one of important technologies in Internet of Things. Reader collision does impair the tag identification efficiency of an RFID system. Many developed methods, for example, the scheduling-based series, that are used to avoid RFID reader collision, have been developed. For scheduling-based methods, communication resources, that is, time slots, channels, and power, are optimally assigned to readers. In this case, reader collision avoidance is equivalent to an optimization problem related to resource allocation. However, the existing methods neglect the overlap between the interrogation regions of readers, which reduces the tag identification rate (TIR. To resolve this shortage, this paper attempts to build a reader-to-reader collision avoidance model considering the interrogation region overlaps (R2RCAM-IRO. In addition, an artificial immune network for resource allocation (RA-IRO-aiNet is designed to optimize the proposed model. For comparison, some comparative numerical simulations are arranged. The simulation results show that the proposed R2RCAM-IRO is an effective model where TIR is improved significantly. And especially in the application of reader-to-reader collision avoidance, the proposed RA-IRO-aiNet outperforms GA, opt-aiNet, and PSO in the total coverage area of readers.

  2. Distributed project scheduling at NASA: Requirements for manual protocols and computer-based support

    Science.gov (United States)

    Richards, Stephen F.

    1992-01-01

    The increasing complexity of space operations and the inclusion of interorganizational and international groups in the planning and control of space missions lead to requirements for greater communication, coordination, and cooperation among mission schedulers. These schedulers must jointly allocate scarce shared resources among the various operational and mission oriented activities while adhering to all constraints. This scheduling environment is complicated by such factors as the presence of varying perspectives and conflicting objectives among the schedulers, the need for different schedulers to work in parallel, and limited communication among schedulers. Smooth interaction among schedulers requires the use of protocols that govern such issues as resource sharing, authority to update the schedule, and communication of updates. This paper addresses the development and characteristics of such protocols and their use in a distributed scheduling environment that incorporates computer-aided scheduling tools. An example problem is drawn from the domain of Space Shuttle mission planning.

  3. Power generation scheduling. A free market based procedure with reserve constraints included

    International Nuclear Information System (INIS)

    Huse, Einar Staale

    1998-01-01

    This thesis deals with the short-term scheduling of electric power generation in a competitive market. This involves determination of start-ups and shut-downs, and production levels of all units in all hours of the optimization period, considering unit characteristics and system restrictions. The unit characteristics and restrictions handled are minimum and maximum production levels, fuel cost function, start-up costs, minimum up time and minimum down time. The system restrictions handled are power balance (supply equals demand in all hours) and spinning reserve requirement. The thesis has two main contributions: (1) A new organization of an hourly electric power market that simultaneously sets the price of both energy and reserve power is proposed. A power exchange is used as a trading place for electricity. Its responsibility is to balance supply and demand bids and to secure enough spinning reserve. Routines for bidding and market clearing are developed. (2) A computer programme that simulates the proposed electricity market has been implemented. The program can also be used as a new method for solving the single owner generation scheduling problem. Simulations show that the performance of the program is excellent. Simulations also show that it is possible to obtain efficient schedules through the proposed electricity market. 37 refs., 20 figs., 15 tabs

  4. Power generation scheduling. A free market based procedure with reserve constraints included

    Energy Technology Data Exchange (ETDEWEB)

    Huse, Einar Staale

    1999-12-31

    This thesis deals with the short-term scheduling of electric power generation in a competitive market. This involves determination of start-ups and shut-downs, and production levels of all units in all hours of the optimization period, considering unit characteristics and system restrictions. The unit characteristics and restrictions handled are minimum and maximum production levels, fuel cost function, start-up costs, minimum up time and minimum down time. The system restrictions handled are power balance (supply equals demand in all hours) and spinning reserve requirement. The thesis has two main contributions: (1) A new organization of an hourly electric power market that simultaneously sets the price of both energy and reserve power is proposed. A power exchange is used as a trading place for electricity. Its responsibility is to balance supply and demand bids and to secure enough spinning reserve. Routines for bidding and market clearing are developed. (2) A computer programme that simulates the proposed electricity market has been implemented. The program can also be used as a new method for solving the single owner generation scheduling problem. Simulations show that the performance of the program is excellent. Simulations also show that it is possible to obtain efficient schedules through the proposed electricity market. 37 refs., 20 figs., 15 tabs.

  5. Power generation scheduling. A free market based procedure with reserve constraints included

    Energy Technology Data Exchange (ETDEWEB)

    Huse, Einar Staale

    1998-12-31

    This thesis deals with the short-term scheduling of electric power generation in a competitive market. This involves determination of start-ups and shut-downs, and production levels of all units in all hours of the optimization period, considering unit characteristics and system restrictions. The unit characteristics and restrictions handled are minimum and maximum production levels, fuel cost function, start-up costs, minimum up time and minimum down time. The system restrictions handled are power balance (supply equals demand in all hours) and spinning reserve requirement. The thesis has two main contributions: (1) A new organization of an hourly electric power market that simultaneously sets the price of both energy and reserve power is proposed. A power exchange is used as a trading place for electricity. Its responsibility is to balance supply and demand bids and to secure enough spinning reserve. Routines for bidding and market clearing are developed. (2) A computer programme that simulates the proposed electricity market has been implemented. The program can also be used as a new method for solving the single owner generation scheduling problem. Simulations show that the performance of the program is excellent. Simulations also show that it is possible to obtain efficient schedules through the proposed electricity market. 37 refs., 20 figs., 15 tabs.

  6. Ensuring the Reliable Operation of the Power Grid: State-Based and Distributed Approaches to Scheduling Energy and Contingency Reserves

    Science.gov (United States)

    Prada, Jose Fernando

    Keeping a contingency reserve in power systems is necessary to preserve the security of real-time operations. This work studies two different approaches to the optimal allocation of energy and reserves in the day-ahead generation scheduling process. Part I presents a stochastic security-constrained unit commitment model to co-optimize energy and the locational reserves required to respond to a set of uncertain generation contingencies, using a novel state-based formulation. The model is applied in an offer-based electricity market to allocate contingency reserves throughout the power grid, in order to comply with the N-1 security criterion under transmission congestion. The objective is to minimize expected dispatch and reserve costs, together with post contingency corrective redispatch costs, modeling the probability of generation failure and associated post contingency states. The characteristics of the scheduling problem are exploited to formulate a computationally efficient method, consistent with established operational practices. We simulated the distribution of locational contingency reserves on the IEEE RTS96 system and compared the results with the conventional deterministic method. We found that assigning locational spinning reserves can guarantee an N-1 secure dispatch accounting for transmission congestion at a reasonable extra cost. The simulations also showed little value of allocating downward reserves but sizable operating savings from co-optimizing locational nonspinning reserves. Overall, the results indicate the computational tractability of the proposed method. Part II presents a distributed generation scheduling model to optimally allocate energy and spinning reserves among competing generators in a day-ahead market. The model is based on the coordination between individual generators and a market entity. The proposed method uses forecasting, augmented pricing and locational signals to induce efficient commitment of generators based on firm

  7. Threshold Based Opportunistic Scheduling of Secondary Users in Underlay Cognitive Radio Networks

    KAUST Repository

    Song, Yao

    2011-12-01

    In underlay cognitive radio networks, secondary users can share the spectrum with primary users as long as the interference caused by the secondary users to primary users is below a certain predetermined threshold. It is reasonable to assume that there is always a large pool of secondary users trying to access the channel, which can be occupied by only one secondary user at a given time. As a result, a multi-user scheduling problem arises among the secondary users. In this thesis, by manipulating basic schemes based on selective multi-user diversity, normalized thresholding, transmission power control, and opportunistic round robin, we propose and analyze eight scheduling schemes of secondary users in an underlay cognitive radio set-up. The system performance of these schemes is quantified by using various performance metrics such as the average system capacity, normalized average feedback load, scheduling outage probability, and system fairness of access. In our proposed schemes, the best user out of all the secondary users in the system is picked to transmit at each given time slot in order to maximize the average system capacity. Two thresholds are used in the two rounds of the selection process to determine the best user. The first threshold is raised by the power constraint from the primary user. The second threshold, which can be adjusted by us, is introduced to reduce the feedback load. The overall system performance is therefore dependent on the choice of these two thresholds and the number of users in the system given the channel conditions for all the users. In this thesis, by deriving analytical formulas and presenting numerical examples, we try to provide insights of the relationship between the performance metrics and the involved parameters including two selection thresholds and the number of active users in the system, in an effort to maximize the average system capacity as well as satisfy the requirements of scheduling outage probability and

  8. Economic-environmental active and reactive power scheduling of modern distribution systems in presence of wind generations: A distribution market-based approach

    International Nuclear Information System (INIS)

    Samimi, Abouzar; Kazemi, Ahad; Siano, Pierluigi

    2015-01-01

    Highlights: • A new market-based approach is proposed to schedule active and reactive powers. • Multi-component reactive power bidding structures for DERs is introduced. • A new economical/environmental operational scheduling method is proposed. • At distribution level, a reactive power market is developed in presence of DERs. - Abstract: Distribution System Operator (DSO) is responsible for active and reactive power scheduling in a distribution system. DSO purchases its active and reactive power requirements from Distributed Energy Resources (DERs) as well as the wholesale electricity market. In this paper, a new economical/environmental operational scheduling method based on sequential day-ahead active and reactive power markets at distribution level is proposed to dispatch active and reactive powers in distribution systems with high penetration of DERs. In the proposed model, after day-ahead active power market was cleared the participants submit their reactive power bids and then the reactive power market will be settled. At distribution level, developing a Var market, in which DERs like synchronous machine-based Distributed Generation (DG) units and Wind Turbines (WTs) could offer their reactive power prices, DERs are motivated to actively participate in the Volt/VAr Control (VVC) problem. To achieve this purpose, based on the capability curves of considered DERs, innovative multi-component reactive power bidding structures for DERs are introduced. Moreover, the effect of reactive power market clearing on the active power scheduling is explicitly considered into the proposed model by rescheduling of active power by usage of energy-balance service bids. On the other hand, environmental concerns that arise from the operation of fossil fuel fired electric generators are included in the proposed model by employing CO_2 emission penalty cost. The suggested reactive power market is cleared through a mixed-integer nonlinear optimization program. The

  9. Instant Childhood Immunization Schedule

    Science.gov (United States)

    ... Recommendations Why Immunize? Vaccines: The Basics Instant Childhood Immunization Schedule Recommend on Facebook Tweet Share Compartir Get ... date. See Disclaimer for additional details. Based on Immunization Schedule for Children 0 through 6 Years of ...

  10. Self-Adaptive Operator Scheduling using the Religion-Based EA

    DEFF Research Database (Denmark)

    Thomsen, Rene; Krink, Thiemo

    2002-01-01

    of their application is determined by a constant parameter, such as a fixed mutation rate. However, recent studies have shown that the optimal usage of a variation operator changes during the EA run. In this study, we combined the idea of self-adaptive mutation operator scheduling with the Religion-Based EA (RBEA......), which is an agent model with spatially structured and variable sized subpopulations (religions). In our new model (OSRBEA), we used a selection of different operators, such that each operator type was applied within one specific subpopulation only. Our results indicate that the optimal choice...

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

    Science.gov (United States)

    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.

  12. 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.

  13. 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.

  14. Mapping of Primary Instructional Methods and Teaching Techniques for Regularly Scheduled, Formal Teaching Sessions in an Anesthesia Residency Program.

    Science.gov (United States)

    Vested Madsen, Matias; Macario, Alex; Yamamoto, Satoshi; Tanaka, Pedro

    2016-06-01

    In this study, we examined the regularly scheduled, formal teaching sessions in a single anesthesiology residency program to (1) map the most common primary instructional methods, (2) map the use of 10 known teaching techniques, and (3) assess if residents scored sessions that incorporated active learning as higher quality than sessions with little or no verbal interaction between teacher and learner. A modified Delphi process was used to identify useful teaching techniques. A representative sample of each of the formal teaching session types was mapped, and residents anonymously completed a 5-question written survey rating the session. The most common primary instructional methods were computer slides-based classroom lectures (66%), workshops (15%), simulations (5%), and journal club (5%). The number of teaching techniques used per formal teaching session averaged 5.31 (SD, 1.92; median, 5; range, 0-9). Clinical applicability (85%) and attention grabbers (85%) were the 2 most common teaching techniques. Thirty-eight percent of the sessions defined learning objectives, and one-third of sessions engaged in active learning. The overall survey response rate equaled 42%, and passive sessions had a mean score of 8.44 (range, 5-10; median, 9; SD, 1.2) compared with a mean score of 8.63 (range, 5-10; median, 9; SD, 1.1) for active sessions (P = 0.63). Slides-based classroom lectures were the most common instructional method, and faculty used an average of 5 known teaching techniques per formal teaching session. The overall education scores of the sessions as rated by the residents were high.

  15. 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.

  16. Effective Task Scheduling and IP Mapping Algorithm for Heterogeneous NoC-Based MPSoC

    Directory of Open Access Journals (Sweden)

    Peng-Fei Yang

    2014-01-01

    Full Text Available Quality of task scheduling is critical to define the network communication efficiency and the performance of the entire NoC- (Network-on-Chip- based MPSoC (multiprocessor System-on-Chip. In this paper, the NoC-based MPSoC design process is favorably divided into two steps, that is, scheduling subtasks to processing elements (PEs of appropriate type and quantity and then mapping these PEs onto the switching nodes of NoC topology. When the task model is improved so that it reflects better the real intertask relations, optimized particle swarm optimization (PSO is utilized to achieve the first step with expected less task running and transfer cost as well as the least task execution time. By referring to the topology of NoC and the resultant communication diagram of the first step, the second step is done with the minimal expected network transmission delay as well as less resource consumption and even power consumption. The comparative experiments have shown the preferable resource and power consumption of the algorithm when it is actually adopted in a system design.

  17. An Agent-Based Solution Framework for Inter-Block Yard Crane Scheduling Problems

    Directory of Open Access Journals (Sweden)

    Omor Sharif

    2012-06-01

    Full Text Available The efficiency of yard operations is critical to the overall productivity of a container terminal because the yard serves as the interface between the landside and waterside operations. Most container terminals use yard cranes to transfer containers between the yard and trucks (both external and internal. To facilitate vessel operations, an efficient work schedule for the yard cranes is necessary given varying work volumes among yard blocks with different planning periods. This paper investigated an agent-based approach to assign and relocate yard cranes among yard blocks based on the forecasted work volumes. The goal of our study is to reduce the work volume that remains incomplete at the end of a planning period. We offered several preference functions for yard cranes and blocks which are modeled as agents. These preference functions are designed to find effective schedules for yard cranes. In addition, we examined various rules for the initial assignment of yard cranes to blocks. Our analysis demonstrated that our model can effectively and efficiently reduce the percentage of incomplete work volume for any real-world sized problem.

  18. Stochastic User Equilibrium Assignment in Schedule-Based Transit Networks with Capacity Constraints

    Directory of Open Access Journals (Sweden)

    Wangtu Xu

    2012-01-01

    Full Text Available This paper proposes a stochastic user equilibrium (SUE assignment model for a schedule-based transit network with capacity constraint. We consider a situation in which passengers do not have the full knowledge about the condition of the network and select paths that minimize a generalized cost function encompassing five components: (1 ride time, which is composed of in-vehicle and waiting times, (2 overload delay, (3 fare, (4 transfer constraints, and (5 departure time difference. We split passenger demands among connections which are the space-time paths between OD pairs of the network. All transit vehicles have a fixed capacity and operate according to some preset timetables. When the capacity constraint of the transit line segment is reached, we show that the Lagrange multipliers of the mathematical programming problem are equivalent to the equilibrium passenger overload delay in the congested transit network. The proposed model can simultaneously predict how passengers choose their transit vehicles to minimize their travel costs and estimate the associated costs in a schedule-based congested transit network. A numerical example is used to illustrate the performance of the proposed model.

  19. A QoS-Based Dynamic Queue Length Scheduling Algorithm in Multiantenna Heterogeneous Systems

    Directory of Open Access Journals (Sweden)

    Verikoukis Christos

    2010-01-01

    Full Text Available The use of real-time delay-sensitive applications in wireless systems has significantly grown during the last years. Therefore the designers of wireless systems have faced a challenging issue to guarantee the required Quality of Service (QoS. On the other hand, the recent advances and the extensive use of multiple antennas have already been included in several commercial standards, where the multibeam opportunistic transmission beamforming strategies have been proposed to improve the performance of the wireless systems. A cross-layer-based dynamically tuned queue length scheduler is presented in this paper, for the Downlink of multiuser and multiantenna WLAN systems with heterogeneous traffic requirements. To align with modern wireless systems transmission strategies, an opportunistic scheduling algorithm is employed, while a priority to the different traffic classes is applied. A tradeoff between the maximization of the throughput of the system and the guarantee of the maximum allowed delay is obtained. Therefore, the length of the queue is dynamically adjusted to select the appropriate conditions based on the operator requirements.

  20. A multipopulation PSO based memetic algorithm for permutation flow shop scheduling.

    Science.gov (United States)

    Liu, Ruochen; Ma, Chenlin; Ma, Wenping; Li, Yangyang

    2013-01-01

    The permutation flow shop scheduling problem (PFSSP) is part of production scheduling, which belongs to the hardest combinatorial optimization problem. In this paper, a multipopulation particle swarm optimization (PSO) based memetic algorithm (MPSOMA) is proposed in this paper. In the proposed algorithm, the whole particle swarm population is divided into three subpopulations in which each particle evolves itself by the standard PSO and then updates each subpopulation by using different local search schemes such as variable neighborhood search (VNS) and individual improvement scheme (IIS). Then, the best particle of each subpopulation is selected to construct a probabilistic model by using estimation of distribution algorithm (EDA) and three particles are sampled from the probabilistic model to update the worst individual in each subpopulation. The best particle in the entire particle swarm is used to update the global optimal solution. The proposed MPSOMA is compared with two recently proposed algorithms, namely, PSO based memetic algorithm (PSOMA) and hybrid particle swarm optimization with estimation of distribution algorithm (PSOEDA), on 29 well-known PFFSPs taken from OR-library, and the experimental results show that it is an effective approach for the PFFSP.

  1. A Multipopulation PSO Based Memetic Algorithm for Permutation Flow Shop Scheduling

    Directory of Open Access Journals (Sweden)

    Ruochen Liu

    2013-01-01

    Full Text Available The permutation flow shop scheduling problem (PFSSP is part of production scheduling, which belongs to the hardest combinatorial optimization problem. In this paper, a multipopulation particle swarm optimization (PSO based memetic algorithm (MPSOMA is proposed in this paper. In the proposed algorithm, the whole particle swarm population is divided into three subpopulations in which each particle evolves itself by the standard PSO and then updates each subpopulation by using different local search schemes such as variable neighborhood search (VNS and individual improvement scheme (IIS. Then, the best particle of each subpopulation is selected to construct a probabilistic model by using estimation of distribution algorithm (EDA and three particles are sampled from the probabilistic model to update the worst individual in each subpopulation. The best particle in the entire particle swarm is used to update the global optimal solution. The proposed MPSOMA is compared with two recently proposed algorithms, namely, PSO based memetic algorithm (PSOMA and hybrid particle swarm optimization with estimation of distribution algorithm (PSOEDA, on 29 well-known PFFSPs taken from OR-library, and the experimental results show that it is an effective approach for the PFFSP.

  2. Energy-saving scheme based on downstream packet scheduling in ethernet passive optical networks

    Science.gov (United States)

    Zhang, Lincong; Liu, Yejun; Guo, Lei; Gong, Xiaoxue

    2013-03-01

    With increasing network sizes, the energy consumption of Passive Optical Networks (PONs) has grown significantly. Therefore, it is important to design effective energy-saving schemes in PONs. Generally, energy-saving schemes have focused on sleeping the low-loaded Optical Network Units (ONUs), which tends to bring large packet delays. Further, the traditional ONU sleep modes are not capable of sleeping the transmitter and receiver independently, though they are not required to transmit or receive packets. Clearly, this approach contributes to wasted energy. Thus, in this paper, we propose an Energy-Saving scheme that is based on downstream Packet Scheduling (ESPS) in Ethernet PON (EPON). First, we design both an algorithm and a rule for downstream packet scheduling at the inter- and intra-ONU levels, respectively, to reduce the downstream packet delay. After that, we propose a hybrid sleep mode that contains not only ONU deep sleep mode but also independent sleep modes for the transmitter and the receiver. This ensures that the energy consumed by the ONUs is minimal. To realize the hybrid sleep mode, a modified GATE control message is designed that involves 10 time points for sleep processes. In ESPS, the 10 time points are calculated according to the allocated bandwidths in both the upstream and the downstream. The simulation results show that ESPS outperforms traditional Upstream Centric Scheduling (UCS) scheme in terms of energy consumption and the average delay for both real-time and non-real-time packets downstream. The simulation results also show that the average energy consumption of each ONU in larger-sized networks is less than that in smaller-sized networks; hence, our ESPS is better suited for larger-sized networks.

  3. Medium-dose-rate brachytherapy of cancer of the cervix: preliminary results of a prospectively designed schedule based on the linear-quadratic model

    International Nuclear Information System (INIS)

    Leborgne, Felix; Fowler, Jack F.; Leborgne, Jose H.; Zubizarreta, Eduardo; Curochquin, Rene

    1999-01-01

    Purpose: To compare results and complications of our previous low-dose-rate (LDR) brachytherapy schedule for early-stage cancer of the cervix, with a prospectively designed medium-dose-rate (MDR) schedule, based on the linear-quadratic model (LQ). Methods and Materials: A combination of brachytherapy, external beam pelvic and parametrial irradiation was used in 102 consecutive Stage Ib-IIb LDR treated patients (1986-1990) and 42 equally staged MDR treated patients (1994-1996). The planned MDR schedule consisted of three insertions on three treatment days with six 8-Gy brachytherapy fractions to Point A, two on each treatment day with an interfraction interval of 6 hours, plus 18 Gy external whole pelvic dose, and followed by additional parametrial irradiation. The calculated biologically effective dose (BED) for tumor was 90 Gy 10 and for rectum below 125 Gy 3 . Results: In practice the MDR brachytherapy schedule achieved a tumor BED of 86 Gy 10 and a rectal BED of 101 Gy 3 . The latter was better than originally planned due to a reduction from 85% to 77% in the percentage of the mean dose to the rectum in relation to Point A. The mean overall treatment time was 10 days shorter for MDR in comparison with LDR. The 3-year actuarial central control for LDR and MDR was 97% and 98% (p = NS), respectively. The Grades 2 and 3 late complications (scale 0 to 3) were 1% and 2.4%, respectively for LDR (3-year) and MDR (2-year). Conclusions: LQ is a reliable tool for designing new schedules with altered fractionation and dose rates. The MDR schedule has proven to be an equivalent treatment schedule compared with LDR, with an additional advantage of having a shorter overall treatment time. The mean rectal BED Gy 3 was lower than expected

  4. An on-time power-aware scheduling scheme for medical sensor SoC-based WBAN systems.

    Science.gov (United States)

    Hwang, Tae-Ho; Kim, Dong-Sun; Kim, Jung-Guk

    2012-12-27

    The focus of many leading technologies in the field of medical sensor systems is on low power consumption and robust data transmission. For example, the implantable cardioverter-defibrillator (ICD), which is used to maintain the heart in a healthy state, requires a reliable wireless communication scheme with an extremely low duty-cycle, high bit rate, and energy-efficient media access protocols. Because such devices must be sustained for over 5 years without access to battery replacement, they must be designed to have extremely low power consumption in sleep mode. Here, an on-time, energy-efficient scheduling scheme is proposed that performs power adjustments to minimize the sleep-mode current. The novelty of this scheduler is that it increases the determinacy of power adjustment and the predictability of scheduling by employing non-pre-emptible dual priority scheduling. This predictable scheduling also guarantees the punctuality of important periodic tasks based on their serialization, by using their worst case execution time) and the power consumption optimization. The scheduler was embedded into a system on chip (SoC) developed to support the wireless body area network-a wakeup-radio and wakeup-timer for implantable medical devices. This scheduling system is validated by the experimental results of its performance when used with life-time extensions of ICD devices.

  5. An On-Time Power-Aware Scheduling Scheme for Medical Sensor SoC-Based WBAN Systems

    Science.gov (United States)

    Hwang, Tae-Ho; Kim, Dong-Sun; Kim, Jung-Guk

    2013-01-01

    The focus of many leading technologies in the field of medical sensor systems is on low power consumption and robust data transmission. For example, the implantable cardioverter-defibrillator (ICD), which is used to maintain the heart in a healthy state, requires a reliable wireless communication scheme with an extremely low duty-cycle, high bit rate, and energy-efficient media access protocols. Because such devices must be sustained for over 5 years without access to battery replacement, they must be designed to have extremely low power consumption in sleep mode. Here, an on-time, energy-efficient scheduling scheme is proposed that performs power adjustments to minimize the sleep-mode current. The novelty of this scheduler is that it increases the determinacy of power adjustment and the predictability of scheduling by employing non-pre-emptible dual priority scheduling. This predictable scheduling also guarantees the punctuality of important periodic tasks based on their serialization, by using their worst case execution time) and the power consumption optimization. The scheduler was embedded into a system on chip (SoC) developed to support the wireless body area network—a wakeup-radio and wakeup-timer for implantable medical devices. This scheduling system is validated by the experimental results of its performance when used with life-time extensions of ICD devices. PMID:23271602

  6. An On-Time Power-Aware Scheduling Scheme for Medical Sensor SoC-Based WBAN Systems

    Directory of Open Access Journals (Sweden)

    Jung-Guk Kim

    2012-12-01

    Full Text Available The focus of many leading technologies in the field of medical sensor systems is on low power consumption and robust data transmission. For example, the implantable cardioverter-defibrillator (ICD, which is used to maintain the heart in a healthy state, requires a reliable wireless communication scheme with an extremely low duty-cycle, high bit rate, and energy-efficient media access protocols. Because such devices must be sustained for over 5 years without access to battery replacement, they must be designed to have extremely low power consumption in sleep mode. Here, an on-time, energy-efficient scheduling scheme is proposed that performs power adjustments to minimize the sleep-mode current. The novelty of this scheduler is that it increases the determinacy of power adjustment and the predictability of scheduling by employing non-pre-emptible dual priority scheduling. This predictable scheduling also guarantees the punctuality of important periodic tasks based on their serialization, by using their worst case execution time and the power consumption optimization. The scheduler was embedded into a system on chip (SoC developed to support the wireless body area network—a wakeup-radio and wakeup-timer for implantable medical devices. This scheduling system is validated by the experimental results of its performance when used with life-time extensions of ICD devices.

  7. A simple rule based model for scheduling farm management operations in SWAT

    Science.gov (United States)

    Schürz, Christoph; Mehdi, Bano; Schulz, Karsten

    2016-04-01

    For many interdisciplinary questions at the watershed scale, the Soil and Water Assessment Tool (SWAT; Arnold et al., 1998) has become an accepted and widely used tool. Despite its flexibility, the model is highly demanding when it comes to input data. At SWAT's core the water balance and the modeled nutrient cycles are plant growth driven (implemented with the EPIC crop growth model). Therefore, land use and crop data with high spatial and thematic resolution, as well as detailed information on cultivation and farm management practices are required. For many applications of the model however, these data are unavailable. In order to meet these requirements, SWAT offers the option to trigger scheduled farm management operations by applying the Potential Heat Unit (PHU) concept. The PHU concept solely takes into account the accumulation of daily mean temperature for management scheduling. Hence, it contradicts several farming strategies that take place in reality; such as: i) Planting and harvesting dates are set much too early or too late, as the PHU concept is strongly sensitivity to inter-annual temperature fluctuations; ii) The timing of fertilizer application, in SWAT this often occurs simultaneously on the same date in in each field; iii) and can also coincide with precipitation events. Particularly, the latter two can lead to strong peaks in modeled nutrient loads. To cope with these shortcomings we propose a simple rule based model (RBM) to schedule management operations according to realistic farmer management practices in SWAT. The RBM involves simple strategies requiring only data that are input into the SWAT model initially, such as temperature and precipitation data. The user provides boundaries of time periods for operation schedules to take place for all crops in the model. These data are readily available from the literature or from crop variety trials. The RBM applies the dates by complying with the following rules: i) Operations scheduled in the

  8. A Novel Energy Efficient Topology Control Scheme Based on a Coverage-Preserving and Sleep Scheduling Model for Sensor Networks

    OpenAIRE

    Shi, Binbin; Wei, Wei; Wang, Yihuai; Shu, Wanneng

    2016-01-01

    In high-density sensor networks, scheduling some sensor nodes to be in the sleep mode while other sensor nodes remain active for monitoring or forwarding packets is an effective control scheme to conserve energy. In this paper, a Coverage-Preserving Control Scheduling Scheme (CPCSS) based on a cloud model and redundancy degree in sensor networks is proposed. Firstly, the normal cloud model is adopted for calculating the similarity degree between the sensor nodes in terms of their historical d...

  9. Multi-layer service function chaining scheduling based on auxiliary graph in IP over optical network

    Science.gov (United States)

    Li, Yixuan; Li, Hui; Liu, Yuze; Ji, Yuefeng

    2017-10-01

    Software Defined Optical Network (SDON) can be considered as extension of Software Defined Network (SDN) in optical networks. SDON offers a unified control plane and makes optical network an intelligent transport network with dynamic flexibility and service adaptability. For this reason, a comprehensive optical transmission service, able to achieve service differentiation all the way down to the optical transport layer, can be provided to service function chaining (SFC). IP over optical network, as a promising networking architecture to interconnect data centers, is the most widely used scenarios of SFC. In this paper, we offer a flexible and dynamic resource allocation method for diverse SFC service requests in the IP over optical network. To do so, we firstly propose the concept of optical service function (OSF) and a multi-layer SFC model. OSF represents the comprehensive optical transmission service (e.g., multicast, low latency, quality of service, etc.), which can be achieved in multi-layer SFC model. OSF can also be considered as a special SF. Secondly, we design a resource allocation algorithm, which we call OSF-oriented optical service scheduling algorithm. It is able to address multi-layer SFC optical service scheduling and provide comprehensive optical transmission service, while meeting multiple optical transmission requirements (e.g., bandwidth, latency, availability). Moreover, the algorithm exploits the concept of Auxiliary Graph. Finally, we compare our algorithm with the Baseline algorithm in simulation. And simulation results show that our algorithm achieves superior performance than Baseline algorithm in low traffic load condition.

  10. A Reputation-based Distributed District Scheduling Algorithm for Smart Grids

    Directory of Open Access Journals (Sweden)

    D. Borra

    2015-05-01

    Full Text Available In this paper we develop and test a distributed algorithm providing Energy Consumption Schedules (ECS in smart grids for a residential district. The goal is to achieve a given aggregate load prole. The NP-hard constrained optimization problem reduces to a distributed unconstrained formulation by means of Lagrangian Relaxation technique, and a meta-heuristic algorithm based on a Quantum inspired Particle Swarm with Levy flights. A centralized iterative reputation-reward mechanism is proposed for end-users to cooperate to avoid power peaks and reduce global overload, based on random distributions simulating human behaviors and penalties on the eective ECS diering from the suggested ECS. Numerical results show the protocols eectiveness.

  11. A novel integrated condition-based maintenance and stochastic flexible job shop scheduling problem

    DEFF Research Database (Denmark)

    Rahmati, Seyed Habib A.; Ahmadi, Abbas; Govindan, Kannan

    2018-01-01

    the level of the system optimization. By means of this equipment, managers can benefit from a condition-based maintenance (CBM) for monitoring and managing their system. The chief aim of the paper is to develop a stochastic maintenance problem based on CBM activities engaged with a complex applied......Integrated consideration of production planning and maintenance processes is a real world assumption. Specifically, by improving the monitoring equipment such as various sensors or product-embedded information devices in recent years, joint assessment of these processes is inevitable for enhancing...... production problem called flexible job shop scheduling problem (FJSP). This integrated problem considers two maintenance scenarios in terms of corrective maintenance (CM) and preventive maintenance (PM). The activation of scenario is done by monitoring the degradation condition of the system and comparing...

  12. Broadcast Scheduling Strategy Based on the Priority of Real- Time Data in a Mobile Environment

    Institute of Scientific and Technical Information of China (English)

    Yang Jin-cai; Liu Yun-sheng

    2003-01-01

    Data broadcast is an important data dissemina-tion approach in mobile environment. On broadcast channel,scalability and efficiency of data transmission are satisfied. In a mobile environment, there exists a kind of real-time data-base application in which both the transactions and data can have their timing constraints and priorities of different levels.In order to meet the requirement of real-time data dissemina-ting and retrieving, a broadcast scheduling strategy HPF-ED F(Highest Priority First with Earlier Deadline and Frequen-cy) is proposed under the BoD (Broadcast on Demand) mod-el. Using the strategy, data items are scheduled according to their priority the transaction imposed on them or system set for them. The strategy also considers other characteristics ofdata items such as deadline and popularity of data. The exten-sive simulation experiments have been conducted to evaluate the performance of the proposed algorithm. Results show that it can achieve excellent performance compared with existing strategies.

  13. An Enhanced Method for Scheduling Observations of Large Sky Error Regions for Finding Optical Counterparts to Transients

    Energy Technology Data Exchange (ETDEWEB)

    Rana, Javed; Singhal, Akshat; Gadre, Bhooshan; Bhalerao, Varun; Bose, Sukanta, E-mail: javed@iucaa.in [Inter-University Centre for Astronomy and Astrophysics, Post Bag 4, Ganeshkhind, Pune 411 007 (India)

    2017-04-01

    The discovery and subsequent study of optical counterparts to transient sources is crucial for their complete astrophysical understanding. Various gamma-ray burst (GRB) detectors, and more notably the ground-based gravitational wave detectors, typically have large uncertainties in the sky positions of detected sources. Searching these large sky regions spanning hundreds of square degrees is a formidable challenge for most ground-based optical telescopes, which can usually image less than tens of square degrees of the sky in a single night. We present algorithms for better scheduling of such follow-up observations in order to maximize the probability of imaging the optical counterpart, based on the all-sky probability distribution of the source position. We incorporate realistic observing constraints such as the diurnal cycle, telescope pointing limitations, available observing time, and the rising/setting of the target at the observatory’s location. We use simulations to demonstrate that our proposed algorithms outperform the default greedy observing schedule used by many observatories. Our algorithms are applicable for follow-up of other transient sources with large positional uncertainties, such as Fermi -detected GRBs, and can easily be adapted for scheduling radio or space-based X-ray follow-up.

  14. An Enhanced Feedback-Base Downlink Packet Scheduling Algorithm for Mobile TV in WIMAX Networks

    Directory of Open Access Journals (Sweden)

    Joseph Oyewale

    2013-06-01

    Full Text Available With high speed access network technology like WIMAX, there is the need for efficient management of radio resources where the throughput and Qos requirements for Multicasting Broadcasting Services (MBS for example TV are to be met. An enhanced  feedback-base downlink Packet scheduling algorithm  that can be used in IEEE 802.16d/e networks for mobile TV “one way traffic”(MBS is needed to support many users utilizing multiuser diversity of the  broadband of WIMAX systems where a group of users(good/worst channels share allocated resources (bandwidth. This paper proposes a WIMAX framework feedback-base (like a channel-awareness downlink packet scheduling algorithm for Mobile TV traffics in IEEE806.16, in which network Physical Timing Slots (PSs resource blocks are allocated in a dynamic way to mobile TV subscribers based on the Channel State information (CSI feedback, and then considering users with worst channels with the aim of improving system throughput while system coverage is being guaranteed. The algorithm was examined by changing the PSs bandwidth allocation of the users and different number of users of a cell. Simulation results show our proposed algorithm performed better than other algorithms (blind algorithms in terms of improvement in system throughput performance. /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso

  15. Systematic Evaluation of Stochastic Methods in Power System Scheduling and Dispatch with Renewable Energy

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Yishen [Univ. of Washington, Seattle, WA (United States); Argonne National Lab. (ANL), Argonne, IL (United States); Zhou, Zhi [Argonne National Lab. (ANL), Argonne, IL (United States); Liu, Cong [Argonne National Lab. (ANL), Argonne, IL (United States); Electric Reliability Council of Texas (ERCOT), Austin, TX (United States); Botterud, Audun [Argonne National Lab. (ANL), Argonne, IL (United States)

    2016-08-01

    As more wind power and other renewable resources are being integrated into the electric power grid, the forecast uncertainty brings operational challenges for the power system operators. In this report, different operational strategies for uncertainty management are presented and evaluated. A comprehensive and consistent simulation framework is developed to analyze the performance of different reserve policies and scheduling techniques under uncertainty in wind power. Numerical simulations are conducted on a modified version of the IEEE 118-bus system with a 20% wind penetration level, comparing deterministic, interval, and stochastic unit commitment strategies. The results show that stochastic unit commitment provides a reliable schedule without large increases in operational costs. Moreover, decomposition techniques, such as load shift factor and Benders decomposition, can help in overcoming the computational obstacles to stochastic unit commitment and enable the use of a larger scenario set to represent forecast uncertainty. In contrast, deterministic and interval unit commitment tend to give higher system costs as more reserves are being scheduled to address forecast uncertainty. However, these approaches require a much lower computational effort Choosing a proper lower bound for the forecast uncertainty is important for balancing reliability and system operational cost in deterministic and interval unit commitment. Finally, we find that the introduction of zonal reserve requirements improves reliability, but at the expense of higher operational costs.

  16. Methods to model and predict the ViewRay treatment deliveries to aid patient scheduling and treatment planning.

    Science.gov (United States)

    Liu, Shi; Wu, Yu; Wooten, H Omar; Green, Olga; Archer, Brent; Li, Harold; Yang, Deshan

    2016-03-08

    A software tool is developed, given a new treatment plan, to predict treatment delivery time for radiation therapy (RT) treatments of patients on ViewRay magnetic resonance image-guided radiation therapy (MR-IGRT) delivery system. This tool is necessary for managing patient treatment scheduling in our clinic. The predicted treatment delivery time and the assessment of plan complexities could also be useful to aid treatment planning. A patient's total treatment delivery time, not including time required for localization, is modeled as the sum of four components: 1) the treatment initialization time; 2) the total beam-on time; 3) the gantry rotation time; and 4) the multileaf collimator (MLC) motion time. Each of the four components is predicted separately. The total beam-on time can be calculated using both the planned beam-on time and the decay-corrected dose rate. To predict the remain-ing components, we retrospectively analyzed the patient treatment delivery record files. The initialization time is demonstrated to be random since it depends on the final gantry angle of the previous treatment. Based on modeling the relationships between the gantry rotation angles and the corresponding rotation time, linear regression is applied to predict the gantry rotation time. The MLC motion time is calculated using the leaves delay modeling method and the leaf motion speed. A quantitative analysis was performed to understand the correlation between the total treatment time and the plan complexity. The proposed algorithm is able to predict the ViewRay treatment delivery time with the average prediction error 0.22min or 1.82%, and the maximal prediction error 0.89 min or 7.88%. The analysis has shown the correlation between the plan modulation (PM) factor and the total treatment delivery time, as well as the treatment delivery duty cycle. A possibility has been identified to significantly reduce MLC motion time by optimizing the positions of closed MLC pairs. The accuracy of

  17. QoS Differential Scheduling in Cognitive-Radio-Based Smart Grid Networks: An Adaptive Dynamic Programming Approach.

    Science.gov (United States)

    Yu, Rong; Zhong, Weifeng; Xie, Shengli; Zhang, Yan; Zhang, Yun

    2016-02-01

    As the next-generation power grid, smart grid will be integrated with a variety of novel communication technologies to support the explosive data traffic and the diverse requirements of quality of service (QoS). Cognitive radio (CR), which has the favorable ability to improve the spectrum utilization, provides an efficient and reliable solution for smart grid communications networks. In this paper, we study the QoS differential scheduling problem in the CR-based smart grid communications networks. The scheduler is responsible for managing the spectrum resources and arranging the data transmissions of smart grid users (SGUs). To guarantee the differential QoS, the SGUs are assigned to have different priorities according to their roles and their current situations in the smart grid. Based on the QoS-aware priority policy, the scheduler adjusts the channels allocation to minimize the transmission delay of SGUs. The entire transmission scheduling problem is formulated as a semi-Markov decision process and solved by the methodology of adaptive dynamic programming. A heuristic dynamic programming (HDP) architecture is established for the scheduling problem. By the online network training, the HDP can learn from the activities of primary users and SGUs, and adjust the scheduling decision to achieve the purpose of transmission delay minimization. Simulation results illustrate that the proposed priority policy ensures the low transmission delay of high priority SGUs. In addition, the emergency data transmission delay is also reduced to a significantly low level, guaranteeing the differential QoS in smart grid.

  18. Developing a new method for modifying over-allocated multi-mode resource constraint schedules in the presence of preemptive resources

    Directory of Open Access Journals (Sweden)

    Aidin Delgoshaei

    2016-09-01

    Full Text Available The issue of resource over-allocating is a big concern for project engineers in the process of scheduling project activities. Resource over-allocating is frequently seen after initial scheduling of a project in practice and causes significant amount of efforts to modify the initial schedules. In this research, a new method is developed for modifying over-allocated schedules in a multi-mode resource constrained project scheduling problems (MRCPSPs with positive cash flows (MRCPSP-PCF. The aim is to maximize profit of the MRCPSPs or logically minimizing costs. The proposed method can be used as a macro in Microsoft Office Project® Software to modify resource over-allocated days after scheduling a project. This research considers progress payment method and preemptive resources. The proposed approach maximizes profit by scheduling activities through the resource calendar respecting to the available level of preemptive resources and activity numbers. To examine the performance of the proposed method a number of experiments derived from the literature are solved. The results are then compared with the circumstances where resource constraints are relaxed. The outcomes show that in all studied cases, the proposed algorithm can provide modified schedules with no over-allocated days. Afterward the method is applied to modify a manufacturing project in practice.

  19. Data Model Approach And Markov Chain Based Analysis Of Multi-Level Queue Scheduling

    Directory of Open Access Journals (Sweden)

    Diwakar Shukla

    2010-01-01

    Full Text Available There are many CPU scheduling algorithms inliterature like FIFO, Round Robin, Shortest-Job-First and so on.The Multilevel-Queue-Scheduling is superior to these due to itsbetter management of a variety of processes. In this paper, aMarkov chain model is used for a general setup of Multilevelqueue-scheduling and the scheduler is assumed to performrandom movement on queue over the quantum of time.Performance of scheduling is examined through a rowdependent data model. It is found that with increasing value of αand d, the chance of system going over the waiting state reduces.At some of the interesting combinations of α and d, it diminishesto zero, thereby, provides us some clue regarding better choice ofqueues over others for high priority jobs. It is found that ifqueue priorities are added in the scheduling intelligently thenbetter performance could be obtained. Data model helpschoosing appropriate preferences.

  20. Three hybridization models based on local search scheme for job shop scheduling problem

    Science.gov (United States)

    Balbi Fraga, Tatiana

    2015-05-01

    This work presents three different hybridization models based on the general schema of Local Search Heuristics, named Hybrid Successive Application, Hybrid Neighborhood, and Hybrid Improved Neighborhood. Despite similar approaches might have already been presented in the literature in other contexts, in this work these models are applied to analyzes the solution of the job shop scheduling problem, with the heuristics Taboo Search and Particle Swarm Optimization. Besides, we investigate some aspects that must be considered in order to achieve better solutions than those obtained by the original heuristics. The results demonstrate that the algorithms derived from these three hybrid models are more robust than the original algorithms and able to get better results than those found by the single Taboo Search.

  1. Minimizing tardiness for job shop scheduling under uncertainties

    OpenAIRE

    Yahouni , Zakaria; Mebarki , Nasser; Sari , Zaki

    2016-01-01

    International audience; —Many disturbances can occur during the execution of a manufacturing scheduling process. To cope with this drawback , flexible solutions are proposed based on the offline and the online phase of the schedule. Groups of permutable operations is one of the most studied flexible scheduling methods bringing flexibility as well as quality to a schedule. The online phase of this method is based on a human-machine system allowing to choose in real-time one schedule from a set...

  2. The impact of alternative pricing methods for drugs in California Workers’ Compensation System: Fee-schedule pricing

    Science.gov (United States)

    Wilson, Leslie; Turkistani, Fatema A.; Huang, Wei; Tran, Dang M.; Lin, Tracy Kuo

    2018-01-01

    Introduction California’s Workers’ Compensation System (CAWCS) Department of Industrial Relations questioned the adequacy of the current Medi-Cal fee-schedule pricing and requested analysis of alternatives that maximize price availability and maintain budget neutrality. Objectives To compare CAWCS pharmacy-dispensed (PD) drug prices under alternative fee schedules, and identify combinations of alternative benchmarks that have prices available for the largest percentage of PD drugs and that best reach budget neutrality. Methods Claims transaction-level data (2011–2013) from CAWCS were used to estimate total annual PD pharmaceutical payments. Medi-Cal pricing data was from the Workman’s Compensation Insurance System (WCIS). Average Wholesale Prices (AWP), Wholesale Acquisition Costs (WAC), Direct Prices (DP), Federal Upper Limit (FUL) prices, and National Average Drug Acquisition Costs (NADAC) were from Medi-Span. We matched National Drug Codes (NDCs), pricing dates, and drug quantity for comparisons. We report pharmacy-dispensed (PD) claims frequency, reimbursement matching rate, and paid costs by CAWCS as the reference price against all alternative price benchmarks. Results Of 12,529,977 CAWCS claims for pharmaceutical products 11.6% (1,462,814) were for PD drugs. Prescription drug cost for CAWCS was over $152M; $63.9M, $47.9M, and $40.6M in 2011–2013. Ninety seven percent of these CAWCS PD claims had a Medi-Cal price. Alternative mechanisms provided a price for fewer claims; NADAC 94.23%, AWP 90.94%, FUL 73.11%, WAC 66.98%, and DP 14.33%. Among CAWCS drugs with no Medi-Cal price in PD claims, AWP, WAC, NADAC, DP, and FUL provided prices for 96.7%, 63.14%, 24.82%, 20.83%, and 15.08% of claims. Overall CAWCS paid 100.52% of Medi-Cal, 60% of AWP, 97% of WAC, 309.53% of FUL, 103.83% of DP, and 136.27% of NADAC. Conclusions CAWCS current Medi-Cal fee-schedule price list for PD drugs is more complete than all alternative fee-schedules. However, all

  3. Production Planning and Planting Pattern Scheduling Information System for Horticulture

    Science.gov (United States)

    Vitadiar, Tanhella Zein; Farikhin; Surarso, Bayu

    2018-02-01

    This paper present the production of planning and planting pattern scheduling faced by horticulture farmer using two methods. Fuzzy time series method use to predict demand on based on sales amount, while linear programming is used to assist horticulture farmers in making production planning decisions and determining the schedule of cropping patterns in accordance with demand predictions of the fuzzy time series method, variable use in this paper is size of areas, production advantage, amount of seeds and age of the plants. This research result production planning and planting patterns scheduling information system with the output is recommendations planting schedule, harvest schedule and the number of seeds will be plant.

  4. Energy management strategy based on short-term generation scheduling for a renewable microgrid using a hydrogen storage system

    International Nuclear Information System (INIS)

    Cau, Giorgio; Cocco, Daniele; Petrollese, Mario; Knudsen Kær, Søren; Milan, Christian

    2014-01-01

    Highlights: • Energy management strategy for hybrid stand-alone power plant with hydrogen storage. • Optimal scheduling of storage devices to minimize the utilization costs. • A scenario tree method is used to manage uncertainties of weather and load forecasts. • A reduction of operational costs and energy losses is achieved. - Abstract: This paper presents a novel energy management strategy (EMS) to control an isolated microgrid powered by a photovoltaic array and a wind turbine and equipped with two different energy storage systems: electric batteries and a hydrogen production and storage system. In particular, an optimal scheduling of storage devices is carried out to maximize the benefits of available renewable resources by operating the photovoltaic systems and the wind turbine at their maximum power points and by minimizing the overall utilization costs. Unlike conventional EMS based on the state-of-charge (SOC) of batteries, the proposed EMS takes into account the uncertainty due to the intermittent nature of renewable resources and electricity demand. In particular, the uncertainties are evaluated with a stochastic approach through the construction of different scenarios with corresponding probabilities. The EMS is defined by minimizing the utilization costs of the energy storage equipment. The weather conditions recorded in four different weeks between April and December are used as case studies to test the proposed EMS and the results obtained are compared with a conventional EMS based on the state-of-charge of batteries. The results show a reduction of utilization costs of about 15% in comparison to conventional SOC-based EMS and an increase of the average energy storage efficiency

  5. An effective PSO-based memetic algorithm for flow shop scheduling.

    Science.gov (United States)

    Liu, Bo; Wang, Ling; Jin, Yi-Hui

    2007-02-01

    This paper proposes an effective particle swarm optimization (PSO)-based memetic algorithm (MA) for the permutation flow shop scheduling problem (PFSSP) with the objective to minimize the maximum completion time, which is a typical non-deterministic polynomial-time (NP) hard combinatorial optimization problem. In the proposed PSO-based MA (PSOMA), both PSO-based searching operators and some special local searching operators are designed to balance the exploration and exploitation abilities. In particular, the PSOMA applies the evolutionary searching mechanism of PSO, which is characterized by individual improvement, population cooperation, and competition to effectively perform exploration. On the other hand, the PSOMA utilizes several adaptive local searches to perform exploitation. First, to make PSO suitable for solving PFSSP, a ranked-order value rule based on random key representation is presented to convert the continuous position values of particles to job permutations. Second, to generate an initial swarm with certain quality and diversity, the famous Nawaz-Enscore-Ham (NEH) heuristic is incorporated into the initialization of population. Third, to balance the exploration and exploitation abilities, after the standard PSO-based searching operation, a new local search technique named NEH_1 insertion is probabilistically applied to some good particles selected by using a roulette wheel mechanism with a specified probability. Fourth, to enrich the searching behaviors and to avoid premature convergence, a simulated annealing (SA)-based local search with multiple different neighborhoods is designed and incorporated into the PSOMA. Meanwhile, an effective adaptive meta-Lamarckian learning strategy is employed to decide which neighborhood to be used in SA-based local search. Finally, to further enhance the exploitation ability, a pairwise-based local search is applied after the SA-based search. Simulation results based on benchmarks demonstrate the effectiveness

  6. NASA scheduling technologies

    Science.gov (United States)

    Adair, Jerry R.

    1994-01-01

    This paper is a consolidated report on ten major planning and scheduling systems that have been developed by the National Aeronautics and Space Administration (NASA). A description of each system, its components, and how it could be potentially used in private industry is provided in this paper. The planning and scheduling technology represented by the systems ranges from activity based scheduling employing artificial intelligence (AI) techniques to constraint based, iterative repair scheduling. The space related application domains in which the systems have been deployed vary from Space Shuttle monitoring during launch countdown to long term Hubble Space Telescope (HST) scheduling. This paper also describes any correlation that may exist between the work done on different planning and scheduling systems. Finally, this paper documents the lessons learned from the work and research performed in planning and scheduling technology and describes the areas where future work will be conducted.

  7. A Priority Rule-Based Heuristic for Resource Investment Project Scheduling Problem with Discounted Cash Flows and Tardiness Penalties

    Directory of Open Access Journals (Sweden)

    Amir Abbas Najafi

    2009-01-01

    Full Text Available Resource investment problem with discounted cash flows (RIPDCFs is a class of project scheduling problem. In RIPDCF, the availability levels of the resources are considered decision variables, and the goal is to find a schedule such that the net present value of the project cash flows optimizes. In this paper, we consider a new RIPDCF in which tardiness of project is permitted with defined penalty. We mathematically formulated the problem and developed a heuristic method to solve it. The results of the performance analysis of the proposed method show an effective solution approach to the problem.

  8. A cloud-based electronic medical record for scheduling, tracking, and documenting examinations and treatment of retinopathy of prematurity.

    Science.gov (United States)

    Arnold, Robert W; Jacob, Jack; Matrix, Zinnia

    2012-01-01

    Screening by neonatologists and staging by ophthalmologists is a cost-effective intervention, but inadvertent missed examinations create a high liability. Paper tracking, bedside schedule reminders, and a computer scheduling and reminder program were compared for speed of input and retrospective missed examination rate. A neonatal intensive care unit (NICU) process was then programmed for cloud-based distribution for inpatient and outpatient retinopathy of prematurity monitoring. Over 11 years, 367 premature infants in one NICU were prospectively monitored. The initial paper system missed 11% of potential examinations, the Windows server-based system missed 2%, and the current cloud-based system missed 0% of potential inpatient and outpatient examinations. Computer input of examinations took the same or less time than paper recording. A computer application with a deliberate NICU process improved the proportion of eligible neonates getting their scheduled eye examinations in a timely manner. Copyright 2012, SLACK Incorporated.

  9. Evaluation of Selected Resource Allocation and Scheduling Methods in Heterogeneous Many-Core Processors and Graphics Processing Units

    Directory of Open Access Journals (Sweden)

    Ciznicki Milosz

    2014-12-01

    Full Text Available Heterogeneous many-core computing resources are increasingly popular among users due to their improved performance over homogeneous systems. Many developers have realized that heterogeneous systems, e.g. a combination of a shared memory multi-core CPU machine with massively parallel Graphics Processing Units (GPUs, can provide significant performance opportunities to a wide range of applications. However, the best overall performance can only be achieved if application tasks are efficiently assigned to different types of processor units in time taking into account their specific resource requirements. Additionally, one should note that available heterogeneous resources have been designed as general purpose units, however, with many built-in features accelerating specific application operations. In other words, the same algorithm or application functionality can be implemented as a different task for CPU or GPU. Nevertheless, from the perspective of various evaluation criteria, e.g. the total execution time or energy consumption, we may observe completely different results. Therefore, as tasks can be scheduled and managed in many alternative ways on both many-core CPUs or GPUs and consequently have a huge impact on the overall computing resources performance, there are needs for new and improved resource management techniques. In this paper we discuss results achieved during experimental performance studies of selected task scheduling methods in heterogeneous computing systems. Additionally, we present a new architecture for resource allocation and task scheduling library which provides a generic application programming interface at the operating system level for improving scheduling polices taking into account a diversity of tasks and heterogeneous computing resources characteristics.

  10. Off-site consequences of radiological accidents: methods, costs and schedules for decontamination

    International Nuclear Information System (INIS)

    Tawil, J.J.; Bold, F.C.; Harrer, B.J.; Currie, J.W.

    1985-08-01

    This report documents a data base and a computer program for conducting a decontamination analysis of a large, radiologically contaminated area. The data base, which was compiled largely through interviews with knowledgeable persons both in the public and private sectors, consists of the costs, physical inputs, rates and contaminant removal efficiencies of a large number of decontamination procedures. The computer program utilizes this data base along with information specific to the contaminated site to provide detailed information that includes the least costly method for effectively decontaminating each surface at the site, various types of property losses associated with the contamination, the time at which each subarea within the site should be decontaminated to minimize these property losses, the quantity of various types of labor and equipment necessary to complete the decontamination, dose to radiation workers, the costs for surveying and monitoring activities, and the disposal costs associated with radiological waste generated during cleanup. The program and data base are demonstrated with a decontamination analysis of a hypothetical site. 39 refs., 24 figs., 155 tabs

  11. Off-site consequences of radiological accidents: methods, costs and schedules for decontamination

    Energy Technology Data Exchange (ETDEWEB)

    Tawil, J.J.; Bold, F.C.; Harrer, B.J.; Currie, J.W.

    1985-08-01

    This report documents a data base and a computer program for conducting a decontamination analysis of a large, radiologically contaminated area. The data base, which was compiled largely through interviews with knowledgeable persons both in the public and private sectors, consists of the costs, physical inputs, rates and contaminant removal efficiencies of a large number of decontamination procedures. The computer program utilizes this data base along with information specific to the contaminated site to provide detailed information that includes the least costly method for effectively decontaminating each surface at the site, various types of property losses associated with the contamination, the time at which each subarea within the site should be decontaminated to minimize these property losses, the quantity of various types of labor and equipment necessary to complete the decontamination, dose to radiation workers, the costs for surveying and monitoring activities, and the disposal costs associated with radiological waste generated during cleanup. The program and data base are demonstrated with a decontamination analysis of a hypothetical site. 39 refs., 24 figs., 155 tabs.

  12. Research on the ITOC based scheduling system for ship piping production

    Science.gov (United States)

    Li, Rui; Liu, Yu-Jun; Hamada, Kunihiro

    2010-12-01

    Manufacturing of ship piping systems is one of the major production activities in shipbuilding. The schedule of pipe production has an important impact on the master schedule of shipbuilding. In this research, the ITOC concept was introduced to solve the scheduling problems of a piping factory, and an intelligent scheduling system was developed. The system, in which a product model, an operation model, a factory model, and a knowledge database of piping production were integrated, automated the planning process and production scheduling. Details of the above points were discussed. Moreover, an application of the system in a piping factory, which achieved a higher level of performance as measured by tardiness, lead time, and inventory, was demonstrated.

  13. Cotton Water Use Efficiency under Two Different Deficit Irrigation Scheduling Methods

    Directory of Open Access Journals (Sweden)

    Jeffrey T. Baker

    2015-08-01

    Full Text Available Declines in Ogallala aquifer levels used for irrigation has prompted research to identify methods for optimizing water use efficiency (WUE of cotton (Gossypium hirsutum L. In this experiment, conducted at Lubbock, TX, USA in 2014, our objective was to test two canopy temperature based stress indices, each at two different irrigation trigger set points: the Stress Time (ST method with irrigation triggers set at 5.5 (ST_5.5 and 8.5 h (ST_8.5 and the Crop Water Stress Index (CWSI method with irrigation triggers set at 0.3 (CWSI_0.3 and 0.6 (CWSI_0.6. When these irrigation triggers were exceeded on a given day, the crop was deficit irrigated with 5 mm of water via subsurface drip tape. Also included in the experimental design were a well-watered (WW control irrigated at 110% of potential evapotranspiration and a dry land (DL treatment that relied on rainfall only. Seasonal crop water use ranged from 353 to 625 mm across these six treatments. As expected, cotton lint yield increased with increasing crop water use but lint yield WUE displayed asignificant (p ≤ 0.05 peak near 3.6 to 3.7 kg ha−1 mm−1 for the ST_5.5 and CWSI_0.3 treatments, respectively. Our results suggest that WUE may be optimized in cotton with less water than that needed for maximum lint yield.

  14. Evaluation of different methods of measuring evapotranspiration as a scheduling guide for drip-irrigated cotton

    International Nuclear Information System (INIS)

    Rawitz, E.; Marani, A.; Mahrer, Y.; Berkovich, D.

    1983-01-01

    Evapotranspiration in a drip-irrigated cotton field was estimated by the energy balance method, net radiation, standard evaporation pan, evaporation pan in the field at canopy height, and by the Penman equation, and the results were compared with the soil-water balance based on neutron meter and tensiometer data from seven observation sites. Evapotranspiration according to the soil-water balance was only about 85% of that determined by the energy balance method, and this is attributed to the fact that irrigation laterals were placed every second row, and the soil-water balance was determined in the irrigated rows. The crop also utilized moisture stored from winter rains in the unirrigated inter-row spaces, which was detected by the energy balance method. Actual evapotranspiration (ET) was 96% of potential ET (Penman), and the latter equalled 98% of net radiation energy. The actual ET equalled 90% of free water evaporation from the pan in the field at canopy height, and 88% of net radiation. The high-frequency drip regime maintained ET very close to potential ET, and under these conditions the field-installed evaporation pan, or the net radiometer, are good indicators of crop water use, with the latter being adaptable to computer-controlled irrigation. (author)

  15. Analyzing scheduling in the food-processing industry

    DEFF Research Database (Denmark)

    Akkerman, Renzo; van Donk, Dirk Pieter

    2009-01-01

    Production scheduling has been widely studied in several research areas, resulting in a large number of methods, prescriptions, and approaches. However, the impact on scheduling practice seems relatively low. This is also the case in the food-processing industry, where industry......-specific characteristics induce specific and complex scheduling problems. Based on ideas about decomposition of the scheduling task and the production process, we develop an analysis methodology for scheduling problems in food processing. This combines an analysis of structural (technological) elements of the production...... process with an analysis of the tasks of the scheduler. This helps to understand, describe, and structure scheduling problems in food processing, and forms a basis for improving scheduling and applying methods developed in literature. It also helps in evaluating the organisational structures...

  16. A new intuitionistic fuzzy rule-based decision-making system for an operating system process scheduler.

    Science.gov (United States)

    Butt, Muhammad Arif; Akram, Muhammad

    2016-01-01

    We present a new intuitionistic fuzzy rule-based decision-making system based on intuitionistic fuzzy sets for a process scheduler of a batch operating system. Our proposed intuitionistic fuzzy scheduling algorithm, inputs the nice value and burst time of all available processes in the ready queue, intuitionistically fuzzify the input values, triggers appropriate rules of our intuitionistic fuzzy inference engine and finally calculates the dynamic priority (dp) of all the processes in the ready queue. Once the dp of every process is calculated the ready queue is sorted in decreasing order of dp of every process. The process with maximum dp value is sent to the central processing unit for execution. Finally, we show complete working of our algorithm on two different data sets and give comparisons with some standard non-preemptive process schedulers.

  17. A Hybrid Genetic Algorithm with a Knowledge-Based Operator for Solving the Job Shop Scheduling Problems

    Directory of Open Access Journals (Sweden)

    Hamed Piroozfard

    2016-01-01

    Full Text Available Scheduling is considered as an important topic in production management and combinatorial optimization in which it ubiquitously exists in most of the real-world applications. The attempts of finding optimal or near optimal solutions for the job shop scheduling problems are deemed important, because they are characterized as highly complex and NP-hard problems. This paper describes the development of a hybrid genetic algorithm for solving the nonpreemptive job shop scheduling problems with the objective of minimizing makespan. In order to solve the presented problem more effectively, an operation-based representation was used to enable the construction of feasible schedules. In addition, a new knowledge-based operator was designed based on the problem’s characteristics in order to use machines’ idle times to improve the solution quality, and it was developed in the context of function evaluation. A machine based precedence preserving order-based crossover was proposed to generate the offspring. Furthermore, a simulated annealing based neighborhood search technique was used to improve the local exploitation ability of the algorithm and to increase its population diversity. In order to prove the efficiency and effectiveness of the proposed algorithm, numerous benchmarked instances were collected from the Operations Research Library. Computational results of the proposed hybrid genetic algorithm demonstrate its effectiveness.

  18. 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%.

  19. Constraint based scheduling for the Goddard Space Flight Center distributed Active Archive Center's data archive and distribution system

    Science.gov (United States)

    Short, Nick, Jr.; Bedet, Jean-Jacques; Bodden, Lee; Boddy, Mark; White, Jim; Beane, John

    1994-01-01

    The Goddard Space Flight Center (GSFC) Distributed Active Archive Center (DAAC) has been operational since October 1, 1993. Its mission is to support the Earth Observing System (EOS) by providing rapid access to EOS data and analysis products, and to test Earth Observing System Data and Information System (EOSDIS) design concepts. One of the challenges is to ensure quick and easy retrieval of any data archived within the DAAC's Data Archive and Distributed System (DADS). Over the 15-year life of EOS project, an estimated several Petabytes (10(exp 15)) of data will be permanently stored. Accessing that amount of information is a formidable task that will require innovative approaches. As a precursor of the full EOS system, the GSFC DAAC with a few Terabits of storage, has implemented a prototype of a constraint-based task and resource scheduler to improve the performance of the DADS. This Honeywell Task and Resource Scheduler (HTRS), developed by Honeywell Technology Center in cooperation the Information Science and Technology Branch/935, the Code X Operations Technology Program, and the GSFC DAAC, makes better use of limited resources, prevents backlog of data, provides information about resources bottlenecks and performance characteristics. The prototype which is developed concurrently with the GSFC Version 0 (V0) DADS, models DADS activities such as ingestion and distribution with priority, precedence, resource requirements (disk and network bandwidth) and temporal constraints. HTRS supports schedule updates, insertions, and retrieval of task information via an Application Program Interface (API). The prototype has demonstrated with a few examples, the substantial advantages of using HTRS over scheduling algorithms such as a First In First Out (FIFO) queue. The kernel scheduling engine for HTRS, called Kronos, has been successfully applied to several other domains such as space shuttle mission scheduling, demand flow manufacturing, and avionics communications

  20. A Novel Memetic Algorithm Based on Decomposition for Multiobjective Flexible Job Shop Scheduling Problem

    Directory of Open Access Journals (Sweden)

    Chun Wang

    2017-01-01

    Full Text Available A novel multiobjective memetic algorithm based on decomposition (MOMAD is proposed to solve multiobjective flexible job shop scheduling problem (MOFJSP, which simultaneously minimizes makespan, total workload, and critical workload. Firstly, a population is initialized by employing an integration of different machine assignment and operation sequencing strategies. Secondly, multiobjective memetic algorithm based on decomposition is presented by introducing a local search to MOEA/D. The Tchebycheff approach of MOEA/D converts the three-objective optimization problem to several single-objective optimization subproblems, and the weight vectors are grouped by K-means clustering. Some good individuals corresponding to different weight vectors are selected by the tournament mechanism of a local search. In the experiments, the influence of three different aggregation functions is first studied. Moreover, the effect of the proposed local search is investigated. Finally, MOMAD is compared with eight state-of-the-art algorithms on a series of well-known benchmark instances and the experimental results show that the proposed algorithm outperforms or at least has comparative performance to the other algorithms.

  1. Chaotic Multiobjective Evolutionary Algorithm Based on Decomposition for Test Task Scheduling Problem

    Directory of Open Access Journals (Sweden)

    Hui Lu

    2014-01-01

    Full Text Available Test task scheduling problem (TTSP is a complex optimization problem and has many local optima. In this paper, a hybrid chaotic multiobjective evolutionary algorithm based on decomposition (CMOEA/D is presented to avoid becoming trapped in local optima and to obtain high quality solutions. First, we propose an improving integrated encoding scheme (IES to increase the efficiency. Then ten chaotic maps are applied into the multiobjective evolutionary algorithm based on decomposition (MOEA/D in three phases, that is, initial population and crossover and mutation operators. To identify a good approach for hybrid MOEA/D and chaos and indicate the effectiveness of the improving IES several experiments are performed. The Pareto front and the statistical results demonstrate that different chaotic maps in different phases have different effects for solving the TTSP especially the circle map and ICMIC map. The similarity degree of distribution between chaotic maps and the problem is a very essential factor for the application of chaotic maps. In addition, the experiments of comparisons of CMOEA/D and variable neighborhood MOEA/D (VNM indicate that our algorithm has the best performance in solving the TTSP.

  2. Performance analysis of switch-based multiuser scheduling schemes with adaptive modulation in spectrum sharing systems

    KAUST Repository

    Qaraqe, Marwa

    2014-04-01

    This paper focuses on the development of multiuser access schemes for spectrum sharing systems whereby secondary users are allowed to share the spectrum with primary users under the condition that the interference observed at the primary receiver is below a predetermined threshold. In particular, two scheduling schemes are proposed for selecting a user among those that satisfy the interference constraint and achieve an acceptable signal-to-noise ratio level. The first scheme focuses on optimizing the average spectral efficiency by selecting the user that reports the best channel quality. In order to alleviate the relatively high feedback required by the first scheme, a second scheme based on the concept of switched diversity is proposed, where the base station (BS) scans the secondary users in a sequential manner until a user whose channel quality is above an acceptable predetermined threshold is found. We develop expressions for the statistics of the signal-to-interference and noise ratio as well as the average spectral efficiency, average feedback load, and the delay at the secondary BS. We then present numerical results for the effect of the number of users and the interference constraint on the optimal switching threshold and the system performance and show that our analysis results are in perfect agreement with the numerical results. © 2014 John Wiley & Sons, Ltd.

  3. Attribute-Based Methods

    Science.gov (United States)

    Thomas P. Holmes; Wiktor L. Adamowicz

    2003-01-01

    Stated preference methods of environmental valuation have been used by economists for decades where behavioral data have limitations. The contingent valuation method (Chapter 5) is the oldest stated preference approach, and hundreds of contingent valuation studies have been conducted. More recently, and especially over the last decade, a class of stated preference...

  4. Schedule control in Ling Ao nuclear power project

    International Nuclear Information System (INIS)

    Xie Ahai

    2007-01-01

    Ling Ao Nuclear Power Station (LANP) is first one built up by self-reliance in China with power capacity 990x2 MWe. The results of quality control, schedule control and cost control are satisfactory. The commercial operation days of Unit 1 and Unit 2 were 28th May 2002 and 8th Jan. 2003 respectively, which were 48 days and 66 days in advance of the project schedule. This paper presents the practices of self-reliance schedule control system in LANP. The paper includes 10 sections: schedule control system; targets of schedule control; schedule control at early stage of project; construction schedule; scheduling practice; Point curves; schedule control of design and procurement; a good practice of construction schedule control on site; commissioning and startup schedule; schedule control culture. Three figures are attached. The main contents of the self-reliance schedule control system are as follows: to draw up reasonable schedules and targets; to setup management mechanism and procedures; to organize powerful project management team; to establish close monitoring system; to provide timely progress reports and statistics information. Five kinds of schedule control targets are introduced, i.e. bar-chart schedule; milesones; Point curves; interface management; hydraulic test schedule of auxiliary piping loops; EMR/EMC/EESR issuance schedules. Six levels of bar-chart schedules were adopted in LANP, but the bar-chart schedules were not satisfactory for complicated erection condition on site, even using six levels of schedules. So a kind of Point curves was developed and their advantages are explained. Scheduling method of three elements: activity, duration, logic, which was adopted in LANP, is introduced. The duration of each piping activities in LANP level 2 project schedule was calculated based on the relevant working Point quantities. The analysis and adjustment of Point curves are illustrated, i.e. balance of monthly quantities; possible production in the peakload

  5. 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

    in day-ahead energy market subject to operational constraints and 2) at the same time, to minimize the risk due to uncertainty in price forecast. Therefore, it is a conflicting bi-objective optimization problem which has both binary and continuous optimization variables considered as constrained mixed......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...... integer nonlinear programming. To demonstrate the effectiveness of the proposed method for self-scheduling in a day-ahead energy market, the locational margin price (LMP) forecast uncertainty in PJM electricity market is considered. An adaptive wavelet neural network (AWNN) is used to forecast the day...

  6. Future aircraft networks and schedules

    Science.gov (United States)

    Shu, Yan

    2011-07-01

    Because of the importance of air transportation scheduling, the emergence of small aircraft and the vision of future fuel-efficient aircraft, this thesis has focused on the study of aircraft scheduling and network design involving multiple types of aircraft and flight services. It develops models and solution algorithms for the schedule design problem and analyzes the computational results. First, based on the current development of small aircraft and on-demand flight services, this thesis expands a business model for integrating on-demand flight services with the traditional scheduled flight services. This thesis proposes a three-step approach to the design of aircraft schedules and networks from scratch under the model. In the first step, both a frequency assignment model for scheduled flights that incorporates a passenger path choice model and a frequency assignment model for on-demand flights that incorporates a passenger mode choice model are created. In the second step, a rough fleet assignment model that determines a set of flight legs, each of which is assigned an aircraft type and a rough departure time is constructed. In the third step, a timetable model that determines an exact departure time for each flight leg is developed. Based on the models proposed in the three steps, this thesis creates schedule design instances that involve almost all the major airports and markets in the United States. The instances of the frequency assignment model created in this thesis are large-scale non-convex mixed-integer programming problems, and this dissertation develops an overall network structure and proposes iterative algorithms for solving these instances. The instances of both the rough fleet assignment model and the timetable model created in this thesis are large-scale mixed-integer programming problems, and this dissertation develops subproblem schemes for solving these instances. Based on these solution algorithms, this dissertation also presents

  7. 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.

  8. 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.

  9. A software-based technique enabling composable hierarchical preemptive scheduling for time-triggered applications

    NARCIS (Netherlands)

    Nejad, A.B.; Molnos, A.; Goossens, K.G.W.

    2013-01-01

    Many embedded real-time applications are typically time-triggered and preemptive schedulers are used to execute tasks of such applications. Orthogonally, composable partitioned embedded platforms use preemptive time-division multiplexing mechanism to isolate applications. Existing composable systems

  10. Simulated Annealing Genetic Algorithm Based Schedule Risk Management of IT Outsourcing Project

    Directory of Open Access Journals (Sweden)

    Fuqiang Lu

    2017-01-01

    Full Text Available IT outsourcing is an effective way to enhance the core competitiveness for many enterprises. But the schedule risk of IT outsourcing project may cause enormous economic loss to enterprise. In this paper, the Distributed Decision Making (DDM theory and the principal-agent theory are used to build a model for schedule risk management of IT outsourcing project. In addition, a hybrid algorithm combining simulated annealing (SA and genetic algorithm (GA is designed, namely, simulated annealing genetic algorithm (SAGA. The effect of the proposed model on the schedule risk management problem is analyzed in the simulation experiment. Meanwhile, the simulation results of the three algorithms GA, SA, and SAGA show that SAGA is the most superior one to the other two algorithms in terms of stability and convergence. Consequently, this paper provides the scientific quantitative proposal for the decision maker who needs to manage the schedule risk of IT outsourcing project.

  11. Cloud computing task scheduling strategy based on improved differential evolution algorithm

    Science.gov (United States)

    Ge, Junwei; He, Qian; Fang, Yiqiu

    2017-04-01

    In order to optimize the cloud computing task scheduling scheme, an improved differential evolution algorithm for cloud computing task scheduling is proposed. Firstly, the cloud computing task scheduling model, according to the model of the fitness function, and then used improved optimization calculation of the fitness function of the evolutionary algorithm, according to the evolution of generation of dynamic selection strategy through dynamic mutation strategy to ensure the global and local search ability. The performance test experiment was carried out in the CloudSim simulation platform, the experimental results show that the improved differential evolution algorithm can reduce the cloud computing task execution time and user cost saving, good implementation of the optimal scheduling of cloud computing tasks.

  12. Analytical Evaluation of the Performance of Proportional Fair Scheduling in OFDMA-Based Wireless Systems

    Directory of Open Access Journals (Sweden)

    Mohamed H. Ahmed

    2012-01-01

    Full Text Available This paper provides an analytical evaluation of the performance of proportional fair (PF scheduling in Orthogonal Frequency-Division Multiple Access (OFDMA wireless systems. OFDMA represents a promising multiple access scheme for transmission over wireless channels, as it combines the orthogonal frequency division multiplexing (OFDM modulation and subcarrier allocation. On the other hand, the PF scheduling is an efficient resource allocation scheme with good fairness characteristics. Consequently, OFDMA with PF scheduling represents an attractive solution to deliver high data rate services to multiple users simultaneously with a high degree of fairness. We investigate a two-dimensional (time slot and frequency subcarrier PF scheduling algorithm for OFDMA systems and evaluate its performance analytically and by simulations. We derive approximate closed-form expressions for the average throughput, throughput fairness index, and packet delay. Computer simulations are used for verification. The analytical results agree well with the results from simulations, which show the good accuracy of the analytical expressions.

  13. A Framework for Uplink Intercell Interference Modeling with Channel-Based Scheduling

    KAUST Repository

    Tabassum, Hina; Yilmaz, Ferkan; Dawy, Zaher; Alouini, Mohamed-Slim

    2012-01-01

    This paper presents a novel framework for modeling the uplink intercell interference(ICI) in a multiuser cellular network. The proposed framework assists in quantifying the impact of various fading channel models and state-of-the-art scheduling

  14. Alternative Outpatient Chemotherapy Scheduling Method to Improve Patient Service Quality and Nurse Satisfaction.

    Science.gov (United States)

    Huang, Yu-Li; Bryce, Alan H; Culbertson, Tracy; Connor, Sarah L; Looker, Sherry A; Altman, Kristin M; Collins, James G; Stellner, Winston; McWilliams, Robert R; Moreno-Aspitia, Alvaro; Ailawadhi, Sikander; Mesa, Ruben A

    2018-02-01

    Optimal scheduling and calendar management in an outpatient chemotherapy unit is a complex process that is driven by a need to focus on safety while accommodating a high degree of variability. Primary constraints are infusion times, staffing resources, chair availability, and unit hours. We undertook a process to analyze our existing management models across multiple practice settings in our health care system, then developed a model to optimize safety and efficiency. The model was tested in one of the community chemotherapy units. We assessed staffing violations as measured by nurse-to-patient ratios throughout the workday and at key points during treatment. Staffing violations were tracked before and after the implementation of the new model. The new model reduced staffing violations by nearly 50% and required fewer chairs to treat the same number of patients for the selected clinic day. Actual implementation results indicated that the new model leveled the distribution of patients across the workday with an 18% reduction in maximum chair utilization and a 27% reduction in staffing violations. Subsequently, a positive impact on peak pharmacy workload reduced delays by as much as 35 minutes. Nursing staff satisfaction with the new model was positive. We conclude that the proposed optimization approach with regard to nursing resource assignment and workload balance throughout a day effectively improves patient service quality and staff satisfaction.

  15. Simulation optimization based ant colony algorithm for the uncertain quay crane scheduling problem

    Directory of Open Access Journals (Sweden)

    Naoufal Rouky

    2019-01-01

    Full Text Available This work is devoted to the study of the Uncertain Quay Crane Scheduling Problem (QCSP, where the loading /unloading times of containers and travel time of quay cranes are considered uncertain. The problem is solved with a Simulation Optimization approach which takes advantage of the great possibilities offered by the simulation to model the real details of the problem and the capacity of the optimization to find solutions with good quality. An Ant Colony Optimization (ACO meta-heuristic hybridized with a Variable Neighborhood Descent (VND local search is proposed to determine the assignments of tasks to quay cranes and the sequences of executions of tasks on each crane. Simulation is used inside the optimization algorithm to generate scenarios in agreement with the probabilities of the distributions of the uncertain parameters, thus, we carry out stochastic evaluations of the solutions found by each ant. The proposed optimization algorithm is tested first for the deterministic case on several well-known benchmark instances. Then, in the stochastic case, since no other work studied exactly the same problem with the same assumptions, the Simulation Optimization approach is compared with the deterministic version. The experimental results show that the optimization algorithm is competitive as compared to the existing methods and that the solutions found by the Simulation Optimization approach are more robust than those found by the optimization algorithm.

  16. Recent Research Trends in Genetic Algorithm Based Flexible Job Shop Scheduling Problems

    OpenAIRE

    Amjad, Muhammad Kamal; Butt, Shahid Ikramullah; Kousar, Rubeena; Ahmad, Riaz; Agha, Mujtaba Hassan; Faping, Zhang; Anjum, Naveed; Asgher, Umer

    2018-01-01

    Flexible Job Shop Scheduling Problem (FJSSP) is an extension of the classical Job Shop Scheduling Problem (JSSP). The FJSSP is known to be NP-hard problem with regard to optimization and it is very difficult to find reasonably accurate solutions of the problem instances in a rational time. Extensive research has been carried out in this area especially over the span of the last 20 years in which the hybrid approaches involving Genetic Algorithm (GA) have gained the most popularity. Keeping in...

  17. Enhancement of the grafting efficiency by the new method of fetal liver-bone marrow scheduled transplantation

    International Nuclear Information System (INIS)

    Xiang Yingsong; Yang Rujun; Yang Ping; Cai Jianming; Min Rui

    2000-01-01

    To enhance the grafting efficiency of bone marrow transplantation, lethally Irradiated recipient Kunming mice were transplantation with fetal liver-bone marrow scheduled transplantation. (FL-BMST) The numbers of WBC, nucleated cells were near to normal level 17 d after irradiation in FL-BMST group transplantation with 1 x 10 6 bone marrow cells, the indexes of CFU-E, CFU-GM, CFU-F, CFU-S, were returned to normal; the degree of GVHD in the FL-BMST group was slighter than that in sing bone marrow transplantation group; and the survival rate of mice was 60%, which was significantly higher than that of routine single bone marrow transplantation group. 'Niches' vacated each time could be fully used and be improved, be increased by fetal liver-bone marrow scheduled transplantation, so the homing of stem cells was increased, and the number of transplanted bone marrow cells could be decreased. So this new method was a better method than routine bone singe marrow transplantation

  18. Evaluation of the Terminal Area Precision Scheduling and Spacing System for Performance-Based Navigation Arrivals

    Science.gov (United States)

    Jung, Jaewoo; Swenson, Harry; Thipphavong, Jane; Martin, Lynne Hazel; Chen, Liang; Nguyen, Jimmy

    2013-01-01

    The growth of global demand for air transportation has put increasing strain on the nation's air traffic management system. To relieve this strain, the International Civil Aviation Organization has urged all nations to adopt Performance-Based Navigation (PBN), which can help to reduce air traffic congestion, decrease aviation fuel consumption, and protect the environment. NASA has developed a Terminal Area Precision Scheduling and Spacing (TAPSS) system that can support increased use of PBN during periods of high traffic, while supporting fuel-efficient, continuous descent approaches. In the original development of this system, arrival aircraft are assigned fuel-efficient Area Navigation (RNAV) Standard Terminal Arrival Routes before their initial descent from cruise, with routing defined to a specific runway. The system also determines precise schedules for these aircraft that facilitate continuous descent through the assigned routes. To meet these schedules, controllers are given a set of advisory tools to precisely control aircraft. The TAPSS system has been evaluated in a series of human-in-the-loop (HITL) air traffic simulations during 2010 and 2011. Results indicated increased airport arrival throughput up to 10 over current operations, and maintained fuel-efficient aircraft decent profiles from the initial descent to landing with reduced controller workload. This paper focuses on results from a joint NASA and FAA HITL simulation conducted in 2012. Due to the FAA rollout of the advance terminal area PBN procedures at mid-sized airports first, the TAPSS system was modified to manage arrival aircraft as they entered Terminal Radar Approach Control (TRACON). Dallas-Love Field airport (DAL) was selected by the FAA as a representative mid-sized airport within a constrained TRACON airspace due to the close proximity of a major airport, in this case Dallas-Ft Worth International Airport, one of the busiest in the world. To address this constraint, RNAV routes and

  19. Model predictive control-based scheduler for repetitive discrete event systems with capacity constraints

    Directory of Open Access Journals (Sweden)

    Hiroyuki Goto

    2013-07-01

    Full Text Available A model predictive control-based scheduler for a class of discrete event systems is designed and developed. We focus on repetitive, multiple-input, multiple-output, and directed acyclic graph structured systems on which capacity constraints can be imposed. The target system’s behaviour is described by linear equations in max-plus algebra, referred to as state-space representation. Assuming that the system’s performance can be improved by paying additional cost, we adjust the system parameters and determine control inputs for which the reference output signals can be observed. The main contribution of this research is twofold, 1: For systems with capacity constraints, we derived an output prediction equation as functions of adjustable variables in a recursive form, 2: Regarding the construct for the system’s representation, we improved the structure to accomplish general operations which are essential for adjusting the system parameters. The result of numerical simulation in a later section demonstrates the effectiveness of the developed controller.

  20. Dosage and dose schedule screening of drug combinations in agent-based models reveals hidden synergies

    Directory of Open Access Journals (Sweden)

    Lisa Corina Barros de Andrade e Sousa1

    2016-01-01

    Full Text Available The fungus Candida albicans is the most common causative agent of human fungal infections and better drugs or drug combination strategies are urgently needed. Here, we present an agent-based model of the interplay of C. albicans with the host immune system and with the microflora of the host. We took into account the morphological change of C. albicans from the yeast to hyphae form and its dynamics during infection. The model allowed us to follow the dynamics of fungal growth and morphology, of the immune cells and of microflora in different perturbing situations. We specifically focused on the consequences of microflora reduction following antibiotic treatment. Using the agent-based model, different drug types have been tested for their effectiveness, namely drugs that inhibit cell division and drugs that constrain the yeast-to-hyphae transition. Applied individually, the division drug turned out to successfully decrease hyphae while the transition drug leads to a burst in hyphae after the end of the treatment. To evaluate the effect of different drug combinations, doses, and schedules, we introduced a measure for the return to a healthy state, the infection score. Using this measure, we found that the addition of a transition drug to a division drug treatment can improve the treatment reliability while minimizing treatment duration and drug dosage. In this work we present a theoretical study. Although our model has not been calibrated to quantitative experimental data, the technique of computationally identifying synergistic treatment combinations in an agent based model exemplifies the importance of computational techniques in translational research.

  1. 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.

  2. Solving a multi-objective manufacturing cell scheduling problem with the consideration of warehouses using a simulated annealing based procedure

    Directory of Open Access Journals (Sweden)

    Adrián A. Toncovich

    2019-01-01

    Full Text Available The competition manufacturing companies face has driven the development of novel and efficient methods that enhance the decision making process. In this work, a specific flow shop scheduling problem of practical interest in the industry is presented and formalized using a mathematical programming model. The problem considers a manufacturing system arranged as a work cell that takes into account the transport operations of raw material and final products between the manufacturing cell and warehouses. For solving this problem, we present a multiobjective metaheuristic strategy based on simulated annealing, the Pareto Archived Simulated Annealing (PASA. We tested this strategy on two kinds of benchmark problem sets proposed by the authors. The first group is composed by small-sized problems. On these tests, PASA was able to obtain optimal or near-optimal solutions in significantly short computing times. In order to complete the analysis, we compared these results to the exact Pareto front of the instances obtained with augmented ε-constraint method. Then, we also tested the algorithm in a set of larger problems to evaluate its performance in more extensive search spaces. We performed this assessment through an analysis of the hypervolume metric. Both sets of tests showed the competitiveness of the Pareto Archived Simulated Annealing to efficiently solve this problem and obtain good quality solutions while using reasonable computational resources.

  3. Automated Scheduling Via Artificial Intelligence

    Science.gov (United States)

    Biefeld, Eric W.; Cooper, Lynne P.

    1991-01-01

    Artificial-intelligence software that automates scheduling developed in Operations Mission Planner (OMP) research project. Software used in both generation of new schedules and modification of existing schedules in view of changes in tasks and/or available resources. Approach based on iterative refinement. Although project focused upon scheduling of operations of scientific instruments and other equipment aboard spacecraft, also applicable to such terrestrial problems as scheduling production in factory.

  4. New heating schedule in hydrogen annealing furnace based on process simulation for less energy consumption

    International Nuclear Information System (INIS)

    Saboonchi, Ahmad; Hassanpour, Saeid; Abbasi, Shahram

    2008-01-01

    Cold rolled steel coils are annealed in batch furnaces to obtain desirable mechanical properties. Annealing operations involve heating and cooling cycles which take long due to high weight of the coils under annealing. To reduce annealing time, a simulation code was developed that is capable of evaluating more effective schedules for annealing coils during the heating process. This code is additionally capable of accurate determination of furnace turn-off time for different coil weights and charge dimensions. After studying many heating schedules and considering heat transfer mechanism in the annealing furnace, a new schedule with the most advantages was selected as the new operation conditions in the hydrogen annealing plant. The performance of all the furnaces were adjusted to the new heating schedule after experiments had been carried out to ensure the accuracy of the code and the fitness of the new operation condition. Comparison of similar yield of cold rolled coils over two months revealed that specific energy consumption of furnaces under the new heating schedule decreased by 11%, heating cycle time by 16%, and the hydrogen consumption by 14%

  5. New heating schedule in hydrogen annealing furnace based on process simulation for less energy consumption

    Energy Technology Data Exchange (ETDEWEB)

    Saboonchi, Ahmad [Department of Mechanical Engineering, Isfahan University of Technology, Isfahan 84154 (Iran); Hassanpour, Saeid [Rayan Tahlil Sepahan Co., Isfahan Science and Technology Town, Isfahan 84155 (Iran); Abbasi, Shahram [R and D Department, Mobarakeh Steel Complex, Isfahan (Iran)

    2008-11-15

    Cold rolled steel coils are annealed in batch furnaces to obtain desirable mechanical properties. Annealing operations involve heating and cooling cycles which take long due to high weight of the coils under annealing. To reduce annealing time, a simulation code was developed that is capable of evaluating more effective schedules for annealing coils during the heating process. This code is additionally capable of accurate determination of furnace turn-off time for different coil weights and charge dimensions. After studying many heating schedules and considering heat transfer mechanism in the annealing furnace, a new schedule with the most advantages was selected as the new operation conditions in the hydrogen annealing plant. The performance of all the furnaces were adjusted to the new heating schedule after experiments had been carried out to ensure the accuracy of the code and the fitness of the new operation condition. Comparison of similar yield of cold rolled coils over two months revealed that specific energy consumption of furnaces under the new heating schedule decreased by 11%, heating cycle time by 16%, and the hydrogen consumption by 14%. (author)

  6. Planning Risk-Based SQC Schedules for Bracketed Operation of Continuous Production Analyzers.

    Science.gov (United States)

    Westgard, James O; Bayat, Hassan; Westgard, Sten A

    2018-02-01

    To minimize patient risk, "bracketed" statistical quality control (SQC) is recommended in the new CLSI guidelines for SQC (C24-Ed4). Bracketed SQC requires that a QC event both precedes and follows (brackets) a group of patient samples. In optimizing a QC schedule, the frequency of QC or run size becomes an important planning consideration to maintain quality and also facilitate responsive reporting of results from continuous operation of high production analytic systems. Different plans for optimizing a bracketed SQC schedule were investigated on the basis of Parvin's model for patient risk and CLSI C24-Ed4's recommendations for establishing QC schedules. A Sigma-metric run size nomogram was used to evaluate different QC schedules for processes of different sigma performance. For high Sigma performance, an effective SQC approach is to employ a multistage QC procedure utilizing a "startup" design at the beginning of production and a "monitor" design periodically throughout production. Example QC schedules are illustrated for applications with measurement procedures having 6-σ, 5-σ, and 4-σ performance. Continuous production analyzers that demonstrate high σ performance can be effectively controlled with multistage SQC designs that employ a startup QC event followed by periodic monitoring or bracketing QC events. Such designs can be optimized to minimize the risk of harm to patients. © 2017 American Association for Clinical Chemistry.

  7. A Multi-layer Dynamic Model for Coordination Based Group Decision Making in Water Resource Allocation and Scheduling

    Science.gov (United States)

    Huang, Wei; Zhang, Xingnan; Li, Chenming; Wang, Jianying

    Management of group decision-making is an important issue in water source management development. In order to overcome the defects in lacking of effective communication and cooperation in the existing decision-making models, this paper proposes a multi-layer dynamic model for coordination in water resource allocation and scheduling based group decision making. By introducing the scheme-recognized cooperative satisfaction index and scheme-adjusted rationality index, the proposed model can solve the problem of poor convergence of multi-round decision-making process in water resource allocation and scheduling. Furthermore, the problem about coordination of limited resources-based group decision-making process can be solved based on the effectiveness of distance-based group of conflict resolution. The simulation results show that the proposed model has better convergence than the existing models.

  8. Performance improvement of per-user threshold based multiuser switched scheduling system

    KAUST Repository

    Nam, Haewoon

    2013-01-01

    SUMMARY This letter proposes a multiuser switched scheduling scheme with per-user threshold and post user selection and provides a generic analytical framework for determining the optimal feedback thresholds. The proposed scheme applies an individual feedback threshold for each user rather than a single common threshold for all users to achieve some capacity gain due to the flexibility of threshold selection as well as a lower scheduling outage probability. In addition, since scheduling outage may occur with a non-negligible probability, the proposed scheme employs post user selection in order to further improve the ergodic capacity, where the user with the highest potential for a higher channel quality than other users is selected. Numerical and simulation results show that the capacity gain by post user selection is significant when random sequence is used. Copyright © 2013 The Institute of Electronics, Information and Communication Engineers.

  9. DEVELOPMENT OF GENETIC ALGORITHM-BASED METHODOLOGY FOR SCHEDULING OF MOBILE ROBOTS

    DEFF Research Database (Denmark)

    Dang, Vinh Quang

    problem is to minimize the total traveling time of the single mobile robot and thereby increase its availability. For the second scheduling problem, a fleet of mobile robots is considered together with a set of machines to carry out different types of tasks, e.g. pre-assembly or quality inspection. Some...... problem and finding optimal solutions for each one. However, the formulated mathematical models could only be applicable to small-scale problems in practice due to the significant increase of computation time as the problem size grows. Note that making schedules of mobile robots is part of real-time....... For the first scheduling problem, a single mobile robot is considered to collect and transport container of parts and empty them into machine feeders where needed. A limit on carrying capacity of the single mobile robot and hard time windows of part-feeding tasks are considered. The objective of the first...

  10. Using the method of ideal point to solve dual-objective problem for production scheduling

    Directory of Open Access Journals (Sweden)

    Mariia Marko

    2016-07-01

    Full Text Available In practice, there are often problems, which must simultaneously optimize several criterias. This so-called multi-objective optimization problem. In the article we consider the use of the method ideal point to solve the two-objective optimization problem of production planning. The process of finding solution to the problem consists of a series of steps where using simplex method, we find the ideal point. After that for solving a scalar problems, we use the method of Lagrange multipliers

  11. A Case Study of Line-of-Balance based Schedule Planning and Control System

    OpenAIRE

    Seppänen, Olli; Aalto, Erno

    2005-01-01

    Line-of-Balance is a graphical technique which can be used to plan and manage work flow. It is suit-able for construction projects because of their large degree of repetition. Despite its strengths Line-of-Balance has not gained widespread use in construction industry internationally. However, it has been used as the principal scheduling tool in Finland since 1980s. As a result of two decades of research and use in industry, a comprehensive schedule planning and control system has been develo...

  12. 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.

  13. Multiuser switched diversity scheduling schemes

    KAUST Repository

    Shaqfeh, Mohammad; Alnuweiri, Hussein M.; Alouini, Mohamed-Slim

    2012-01-01

    Multiuser switched-diversity scheduling schemes were recently proposed in order to overcome the heavy feedback requirements of conventional opportunistic scheduling schemes by applying a threshold-based, distributed, and ordered scheduling mechanism. The main idea behind these schemes is that slight reduction in the prospected multiuser diversity gains is an acceptable trade-off for great savings in terms of required channel-state-information feedback messages. In this work, we characterize the achievable rate region of multiuser switched diversity systems and compare it with the rate region of full feedback multiuser diversity systems. We propose also a novel proportional fair multiuser switched-based scheduling scheme and we demonstrate that it can be optimized using a practical and distributed method to obtain the feedback thresholds. We finally demonstrate by numerical examples that switched-diversity scheduling schemes operate within 0.3 bits/sec/Hz from the ultimate network capacity of full feedback systems in Rayleigh fading conditions. © 2012 IEEE.

  14. Sport Tournament Automated Scheduling System

    Directory of Open Access Journals (Sweden)

    Raof R. A. A

    2018-01-01

    Full Text Available The organizer of sport events often facing problems such as wrong calculations of marks and scores, as well as difficult to create a good and reliable schedule. Most of the time, the issues about the level of integrity of committee members and also issues about errors made by human came into the picture. Therefore, the development of sport tournament automated scheduling system is proposed. The system will be able to automatically generate the tournament schedule as well as automatically calculating the scores of each tournament. The problem of scheduling the matches of a round robin and knock-out phase in a sport league are given focus. The problem is defined formally and the computational complexity is being noted. A solution algorithm is presented using a two-step approach. The first step is the creation of a tournament pattern and is based on known graph-theoretic method. The second one is an assignment problem and it is solved using a constraint based depth-first branch and bound procedure that assigns actual teams to numbers in the pattern. As a result, the scheduling process and knock down phase become easy for the tournament organizer and at the same time increasing the level of reliability.

  15. Multiuser switched diversity scheduling schemes

    KAUST Repository

    Shaqfeh, Mohammad

    2012-09-01

    Multiuser switched-diversity scheduling schemes were recently proposed in order to overcome the heavy feedback requirements of conventional opportunistic scheduling schemes by applying a threshold-based, distributed, and ordered scheduling mechanism. The main idea behind these schemes is that slight reduction in the prospected multiuser diversity gains is an acceptable trade-off for great savings in terms of required channel-state-information feedback messages. In this work, we characterize the achievable rate region of multiuser switched diversity systems and compare it with the rate region of full feedback multiuser diversity systems. We propose also a novel proportional fair multiuser switched-based scheduling scheme and we demonstrate that it can be optimized using a practical and distributed method to obtain the feedback thresholds. We finally demonstrate by numerical examples that switched-diversity scheduling schemes operate within 0.3 bits/sec/Hz from the ultimate network capacity of full feedback systems in Rayleigh fading conditions. © 2012 IEEE.

  16. TAGUCHI METHOD FOR THREE-STAGE ASSEMBLY FLOW SHOP SCHEDULING PROBLEM WITH BLOCKING AND SEQUENCE-DEPENDENT SET UP TIMES

    Directory of Open Access Journals (Sweden)

    AREF MALEKI-DARONKOLAEI

    2013-10-01

    Full Text Available This article considers a three-stage assembly flowshop scheduling problem minimizing the weighted sum of mean completion time and makespan with sequence-dependent setup times at the first stage and blocking times between each stage. To tackle such an NP-hard, two meta-heuristic algorithms are presented. The novelty of our approach is to develop a variable neighborhood search algorithm (VNS and a well-known simulated annealing (SA for the problem. Furthermore, to enhance the performance of the (SA, its parameters are optimized by the use of Taguchi method, but to setting parameters of VNS just one parameter has been used without Taguchi. The computational results show that the proposed VNS is better in mean and standard deviation for all sizes of the problem than SA, but on the contrary about CPU Time SA outperforms VNS.

  17. Range Scheduling Aid (RSA)

    Science.gov (United States)

    Logan, J. R.; Pulvermacher, M. K.

    1991-01-01

    Range Scheduling Aid (RSA) is presented in the form of the viewgraphs. The following subject areas are covered: satellite control network; current and new approaches to range scheduling; MITRE tasking; RSA features; RSA display; constraint based analytic capability; RSA architecture; and RSA benefits.

  18. Effectiveness of Time-Based Attention Schedules on Students in Inclusive Classrooms in Turkey

    Science.gov (United States)

    Sazak Pinar, Elif

    2015-01-01

    This study examines the effectiveness of fixed-time (FT) and variable-time (VT) schedules and attention on the problem behaviors and on-task behaviors of students with and without intellectual disabilities in inclusive classrooms in Turkey. Three second-grade students with intellectual disabilities, three students without intellectual…

  19. Load Scheduling in a Cloud Based Massive Video-Storage Environment

    DEFF Research Database (Denmark)

    Bayyapu, Karunakar Reddy; Fischer, Paul

    2015-01-01

    We propose an architecture for a storage system of surveillance videos. Such systems have to handle massive amounts of incoming video streams and relatively few requests for replay. In such a system load (i.e., Write requests) scheduling is essential to guarantee performance. Large-scale data-sto...

  20. Scheduler-Specific Confidentiality for Multi-Threaded Programs and Its Logic-Based Verification

    NARCIS (Netherlands)

    Huisman, Marieke; Ngo, Minh Tri; Beckert, B.; Damiani, F.; Gurov, D.

    2012-01-01

    Observational determinism has been proposed in the literature as a way to ensure condentiality for multi-threaded programs. Intuitively, a program is observationally deterministic if the behavior of the public variables is deterministic, i.e., independent of the private variables and the scheduling

  1. A duty-period-based formulation of the airline crew scheduling problem

    Energy Technology Data Exchange (ETDEWEB)

    Hoffman, K.

    1994-12-31

    We present a new formulation of the airline crew scheduling problem that explicitly considers the duty periods. We suggest an algorithm for solving the formulation by a column generation approach with branch-and-bound. Computational results are reported for a number of test problems.

  2. Schedule Analytics

    Science.gov (United States)

    2016-04-30

    Warfare, Naval Sea Systems Command Acquisition Cycle Time : Defining the Problem David Tate, Institute for Defense Analyses Schedule Analytics Jennifer...research was comprised of the following high- level steps :  Identify and review primary data sources 1...research. However, detailed reviews of the OMB IT Dashboard data revealed that schedule data is highly aggregated. Program start date and program end date

  3. Prediction and optimization methods for electric vehicle charging schedules in the EDISON project

    DEFF Research Database (Denmark)

    Aabrandt, Andreas; Andersen, Peter Bach; Pedersen, Anders Bro

    2012-01-01

    project has been launched to investigate various areas relevant to electric vehicle integration. As part of EDISON an electric vehicle aggregator has been developed to demonstrate smart charging of electric vehicles. The emphasis of this paper is the mathematical methods on which the EDISON aggregator...

  4. Optimal estimation and scheduling in aquifer management using the rapid feedback control method

    Science.gov (United States)

    Ghorbanidehno, Hojat; Kokkinaki, Amalia; Kitanidis, Peter K.; Darve, Eric

    2017-12-01

    Management of water resources systems often involves a large number of parameters, as in the case of large, spatially heterogeneous aquifers, and a large number of "noisy" observations, as in the case of pressure observation in wells. Optimizing the operation of such systems requires both searching among many possible solutions and utilizing new information as it becomes available. However, the computational cost of this task increases rapidly with the size of the problem to the extent that textbook optimization methods are practically impossible to apply. In this paper, we present a new computationally efficient technique as a practical alternative for optimally operating large-scale dynamical systems. The proposed method, which we term Rapid Feedback Controller (RFC), provides a practical approach for combined monitoring, parameter estimation, uncertainty quantification, and optimal control for linear and nonlinear systems with a quadratic cost function. For illustration, we consider the case of a weakly nonlinear uncertain dynamical system with a quadratic objective function, specifically a two-dimensional heterogeneous aquifer management problem. To validate our method, we compare our results with the linear quadratic Gaussian (LQG) method, which is the basic approach for feedback control. We show that the computational cost of the RFC scales only linearly with the number of unknowns, a great improvement compared to the basic LQG control with a computational cost that scales quadratically. We demonstrate that the RFC method can obtain the optimal control values at a greatly reduced computational cost compared to the conventional LQG algorithm with small and controllable losses in the accuracy of the state and parameter estimation.

  5. A demand response modeling for residential consumers in smart grid environment using game theory based energy scheduling algorithm

    Directory of Open Access Journals (Sweden)

    S. Sofana Reka

    2016-06-01

    Full Text Available In this paper, demand response modeling scheme is proposed for residential consumers using game theory algorithm as Generalized Tit for Tat (GTFT Dominant Game based Energy Scheduler. The methodology is established as a work flow domain model between the utility and the user considering the smart grid framework. It exhibits an algorithm which schedules load usage by creating several possible tariffs for consumers such that demand is never raised. This can be done both individually and among multiple users of a community. The uniqueness behind the demand response proposed is that, the tariff is calculated for all hours and the load during the peak hours which can be rescheduled is shifted based on the Peak Average Ratio. To enable the vitality of the work simulation results of a general case of three domestic consumers are modeled extended to a comparative performance and evaluation with other algorithms and inference is analyzed.

  6. Enhanced first-in-first-out-based round-robin multicast scheduling algorithm for input-queued switches

    DEFF Research Database (Denmark)

    Yu, Hao; Ruepp, Sarah Renée; Berger, Michael Stübert

    2011-01-01

    This study focuses on the multicast scheduling for M × N input-queued switches. An enhanced first-in-first-out -based round-robin multicast scheduling algorithm is proposed with a function of searching deeper into queues to reduce the head-of-line (HOL) blocking problem and thereby the multicast...... out on the decision matrix to reduce the number of transmission for each cell. To reduce the HOL blocking problem, a complement matrix is constructed based on the traffic matrix and the decision matrix, and a process of searching deeper into the queues is carried out to find cells that can be sent...... to the idle outputs. Simulation results show that the proposed function of searching deeper into the queues can alleviate the HOL blocking and as a result reduce the multicast latency significantly. Under both balanced and unbalanced multicast traffic, the proposed algorithm is able to maintain a stable...

  7. Algorithm for complete enumeration based on a stroke graph to solve the supply network configuration and operations scheduling problem

    Directory of Open Access Journals (Sweden)

    Julien Maheut

    2013-07-01

    Full Text Available Purpose: The purpose of this paper is to present an algorithm that solves the supply network configuration and operations scheduling problem in a mass customization company that faces alternative operations for one specific tool machine order in a multiplant context. Design/methodology/approach: To achieve this objective, the supply chain network configuration and operations scheduling problem is presented. A model based on stroke graphs allows the design of an algorithm that enumerates all the feasible solutions. The algorithm considers the arrival of a new customized order proposal which has to be inserted into a scheduled program. A selection function is then used to choose the solutions to be simulated in a specific simulation tool implemented in a Decision Support System. Findings and Originality/value: The algorithm itself proves efficient to find all feasible solutions when alternative operations must be considered. The stroke structure is successfully used to schedule operations when considering more than one manufacturing and supply option in each step. Research limitations/implications: This paper includes only the algorithm structure for a one-by-one, sequenced introduction of new products into the list of units to be manufactured. Therefore, the lotsizing process is done on a lot-per-lot basis. Moreover, the validation analysis is done through a case study and no generalization can be done without risk. Practical implications: The result of this research would help stakeholders to determine all the feasible and practical solutions for their problem. It would also allow to assessing the total costs and delivery times of each solution. Moreover, the Decision Support System proves useful to assess alternative solutions. Originality/value: This research offers a simple algorithm that helps solve the supply network configuration problem and, simultaneously, the scheduling problem by considering alternative operations. The proposed system

  8. Design and Evaluation of the User-Adapted Program Scheduling system based on Bayesian Network and Constraint Satisfaction

    Science.gov (United States)

    Iwasaki, Hirotoshi; Sega, Shinichiro; Hiraishi, Hironori; Mizoguchi, Fumio

    In recent years, lots of music content can be stored in mobile computing devices, such as a portable digital music player and a car navigation system. Moreover, various information content like news or traffic information can be acquired always anywhere by a cellular communication and a wireless LAN. However, usability issues arise from the simple interfaces of mobile computing devices. Moreover, retrieving and selecting such content poses safety issues, especially while driving. Thus, it is important for the mobile system to recommend content automatically adapted to user's preference and situation. In this paper, we present the user-adapted program scheduling that generates sequences of content (Program) suiting user's preference and situation based on the Bayesian network and the Constraint Satisfaction Problem (CSP) technique. We also describe the design and evaluation of its realization system, the Personal Program Producer (P3). First, preference such as a genre ratio of content in a program is learned as a Bayesian network model using simple operations such as a skip behavior. A model including each content tends to become large-scale. In order to make it small, we present the model separation method that carries out losslessly compression of the model. Using the model, probabilistic distributions of preference to generate constraints are inferred. Finally satisfying the constraints, a program is produced. This kind of CSP has an issue of which the number of variables is not fixedness. In order to make it variable, we propose a method using metavariables. To evaluate the above methods, we applied them to P3 on a car navigation system. User evaluations helped us clarify that the P3 can produce the program that a user prefers and adapt it to the user.

  9. Methods in Logic Based Control

    DEFF Research Database (Denmark)

    Christensen, Georg Kronborg

    1999-01-01

    Desing and theory of Logic Based Control systems.Boolean Algebra, Karnaugh Map, Quine McClusky's algorithm. Sequential control design. Logic Based Control Method, Cascade Control Method. Implementation techniques: relay, pneumatic, TTL/CMOS,PAL and PLC- and Soft_PLC implementation. PLC...

  10. Activity based costing (ABC Method

    Directory of Open Access Journals (Sweden)

    Prof. Ph.D. Saveta Tudorache

    2008-05-01

    Full Text Available In the present paper the need and advantages are presented of using the Activity BasedCosting method, need arising from the need of solving the information pertinence issue. This issue has occurreddue to the limitation of classic methods in this field, limitation also reflected by the disadvantages ofsuch classic methods in establishing complete costs.

  11. Broadcast Scheduling Strategy Based on the Priority of Real.Time Data in a Mobile Environment

    Institute of Scientific and Technical Information of China (English)

    YangJin-cait; LiuYun-sheng

    2003-01-01

    Data broadcast is an important data dissemination approach in mobile environment. On broadcast channel,scalability and efficiency of data transmission are satisfied. In a mobile environment, there exists a kind of real-time database application in which both the transactions and data can have their timing constraints and priorities of different levels.In order to meet the requirement of real-time data disseminaring and retrieving, a broadcast scheduling strategy HPF-ED F (Highest Priority First with Earlier Deadline and Frequency) is proposed under the BoD (Broadcast on Demand) model. Using the strategy, data items are scheduled according to their priority the transaction imposed on them or system set for them. The strategy also considers other characteristics of data items such as deadline and popularity of data. The extensive simulation experiments have been conducted to evaluate the performance of the proposed algorithm. Results show that it can achieve excellent performance compared with existing strategies.

  12. Recent Research Trends in Genetic Algorithm Based Flexible Job Shop Scheduling Problems

    Directory of Open Access Journals (Sweden)

    Muhammad Kamal Amjad

    2018-01-01

    Full Text Available Flexible Job Shop Scheduling Problem (FJSSP is an extension of the classical Job Shop Scheduling Problem (JSSP. The FJSSP is known to be NP-hard problem with regard to optimization and it is very difficult to find reasonably accurate solutions of the problem instances in a rational time. Extensive research has been carried out in this area especially over the span of the last 20 years in which the hybrid approaches involving Genetic Algorithm (GA have gained the most popularity. Keeping in view this aspect, this article presents a comprehensive literature review of the FJSSPs solved using the GA. The survey is further extended by the inclusion of the hybrid GA (hGA techniques used in the solution of the problem. This review will give readers an insight into use of certain parameters in their future research along with future research directions.

  13. Synthesis of Communication Schedules for TTEthernet-Based Mixed-Criticality Systems

    DEFF Research Database (Denmark)

    Tamas-Selicean, Domitian; Pop, Paul; Steiner, Wilfried

    2012-01-01

    In this paper we are interested in safety-critical distributed systems, composed of heterogeneous processing elements interconnected using the TTEthernet protocol. We address hard real-time mixed-criticality applications, which may have different criticality levels, and we focus on the optimization...... be integrated onto the same architecture only if there is enough spatial and temporal separation among them. TTEthernet offers spatial separation for mixed-criticality messages through the concept of virtual links, and temporal separation, enforced through schedule tables for TT messages and bandwidth...... allocation for RC messages. Given the set of mixed-criticality messages in the system and the topology of the virtual links on which the messages are transmitted, we are interested to synthesize offline the static schedules for the TT messages, such that the deadlines for the TT and RC messages are satisfied...

  14. High-Speed Train Stop-Schedule Optimization Based on Passenger Travel Convenience

    OpenAIRE

    Dingjun Chen; Shaoquan Ni; Chang’an Xu; Hongxia Lv; Simin Wang

    2016-01-01

    The stop-schedules for passenger trains are important to the operation planning of high-speed trains, and they decide the quality of passenger service and the transportation efficiency. This paper analyzes the specific manifestation of passenger travel convenience and proposes the concepts of interstation accessibility and degree of accessibility. In consideration of both the economic benefits of railway corporations and the travel convenience of passengers, a multitarget optimization model i...

  15. Load Balancing Integrated Least Slack Time-Based Appliance Scheduling for Smart Home Energy Management

    OpenAIRE

    Bhagya Nathali Silva; Murad Khan; Kijun Han

    2018-01-01

    The emergence of smart devices and smart appliances has highly favored the realization of the smart home concept. Modern smart home systems handle a wide range of user requirements. Energy management and energy conservation are in the spotlight when deploying sophisticated smart homes. However, the performance of energy management systems is highly influenced by user behaviors and adopted energy management approaches. Appliance scheduling is widely accepted as an effective mechanism to manage...

  16. Asymptotic analysis of SPTA-based algorithms for no-wait flow shop scheduling problem with release dates.

    Science.gov (United States)

    Ren, Tao; Zhang, Chuan; Lin, Lin; Guo, Meiting; Xie, Xionghang

    2014-01-01

    We address the scheduling problem for a no-wait flow shop to optimize total completion time with release dates. With the tool of asymptotic analysis, we prove that the objective values of two SPTA-based algorithms converge to the optimal value for sufficiently large-sized problems. To further enhance the performance of the SPTA-based algorithms, an improvement scheme based on local search is provided for moderate scale problems. New lower bound is presented for evaluating the asymptotic optimality of the algorithms. Numerical simulations demonstrate the effectiveness of the proposed algorithms.

  17. Asymptotic Analysis of SPTA-Based Algorithms for No-Wait Flow Shop Scheduling Problem with Release Dates

    Directory of Open Access Journals (Sweden)

    Tao Ren

    2014-01-01

    Full Text Available We address the scheduling problem for a no-wait flow shop to optimize total completion time with release dates. With the tool of asymptotic analysis, we prove that the objective values of two SPTA-based algorithms converge to the optimal value for sufficiently large-sized problems. To further enhance the performance of the SPTA-based algorithms, an improvement scheme based on local search is provided for moderate scale problems. New lower bound is presented for evaluating the asymptotic optimality of the algorithms. Numerical simulations demonstrate the effectiveness of the proposed algorithms.

  18. Shuffled Frog Leaping Algorithm for Preemptive Project Scheduling Problems with Resource Vacations Based on Patterson Set

    Directory of Open Access Journals (Sweden)

    Yi Han

    2013-01-01

    Full Text Available This paper presents a shuffled frog leaping algorithm (SFLA for the single-mode resource-constrained project scheduling problem where activities can be divided into equant units and interrupted during processing. Each activity consumes 0–3 types of resources which are renewable and temporarily not available due to resource vacations in each period. The presence of scarce resources and precedence relations between activities makes project scheduling a difficult and important task in project management. A recent popular metaheuristic shuffled frog leaping algorithm, which is enlightened by the predatory habit of frog group in a small pond, is adopted to investigate the project makespan improvement on Patterson benchmark sets which is composed of different small and medium size projects. Computational results demonstrate the effectiveness and efficiency of SFLA in reducing project makespan and minimizing activity splitting number within an average CPU runtime, 0.521 second. This paper exposes all the scheduling sequences for each project and shows that of the 23 best known solutions have been improved.

  19. Clinical Laboratory Fee Schedule

    Data.gov (United States)

    U.S. Department of Health & Human Services — Outpatient clinical laboratory services are paid based on a fee schedule in accordance with Section 1833(h) of the Social Security Act. The clinical laboratory fee...

  20. An Interference-Aware Traffic-Priority-Based Link Scheduling Algorithm for Interference Mitigation in Multiple Wireless Body Area Networks

    Directory of Open Access Journals (Sweden)

    Thien T. T. Le

    2016-12-01

    Full Text Available Currently, wireless body area networks (WBANs are effectively used for health monitoring services. However, in cases where WBANs are densely deployed, interference among WBANs can cause serious degradation of network performance and reliability. Inter-WBAN interference can be reduced by scheduling the communication links of interfering WBANs. In this paper, we propose an interference-aware traffic-priority-based link scheduling (ITLS algorithm to overcome inter-WBAN interference in densely deployed WBANs. First, we model a network with multiple WBANs as an interference graph where node-level interference and traffic priority are taken into account. Second, we formulate link scheduling for multiple WBANs as an optimization model where the objective is to maximize the throughput of the entire network while ensuring the traffic priority of sensor nodes. Finally, we propose the ITLS algorithm for multiple WBANs on the basis of the optimization model. High spatial reuse is also achieved in the proposed ITLS algorithm. The proposed ITLS achieves high spatial reuse while considering traffic priority, packet length, and the number of interfered sensor nodes. Our simulation results show that the proposed ITLS significantly increases spatial reuse and network throughput with lower delay by mitigating inter-WBAN interference.

  1. 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.

  2. Clustering and Genetic Algorithm Based Hybrid Flowshop Scheduling with Multiple Operations

    Directory of Open Access Journals (Sweden)

    Yingfeng Zhang

    2014-01-01

    Full Text Available This research is motivated by a flowshop scheduling problem of our collaborative manufacturing company for aeronautic products. The heat-treatment stage (HTS and precision forging stage (PFS of the case are selected as a two-stage hybrid flowshop system. In HTS, there are four parallel machines and each machine can process a batch of jobs simultaneously. In PFS, there are two machines. Each machine can install any module of the four modules for processing the workpeices with different sizes. The problem is characterized by many constraints, such as batching operation, blocking environment, and setup time and working time limitations of modules, and so forth. In order to deal with the above special characteristics, the clustering and genetic algorithm is used to calculate the good solution for the two-stage hybrid flowshop problem. The clustering is used to group the jobs according to the processing ranges of the different modules of PFS. The genetic algorithm is used to schedule the optimal sequence of the grouped jobs for the HTS and PFS. Finally, a case study is used to demonstrate the efficiency and effectiveness of the designed genetic algorithm.

  3. Cooperative Scheduling of Imaging Observation Tasks for High-Altitude Airships Based on Propagation Algorithm

    Directory of Open Access Journals (Sweden)

    He Chuan

    2012-01-01

    Full Text Available The cooperative scheduling problem on high-altitude airships for imaging observation tasks is discussed. A constraint programming model is established by analyzing the main constraints, which takes the maximum task benefit and the minimum cruising distance as two optimization objectives. The cooperative scheduling problem of high-altitude airships is converted into a main problem and a subproblem by adopting hierarchy architecture. The solution to the main problem can construct the preliminary matching between tasks and observation resource in order to reduce the search space of the original problem. Furthermore, the solution to the sub-problem can detect the key nodes that each airship needs to fly through in sequence, so as to get the cruising path. Firstly, the task set is divided by using k-core neighborhood growth cluster algorithm (K-NGCA. Then, a novel swarm intelligence algorithm named propagation algorithm (PA is combined with the key node search algorithm (KNSA to optimize the cruising path of each airship and determine the execution time interval of each task. Meanwhile, this paper also provides the realization approach of the above algorithm and especially makes a detailed introduction on the encoding rules, search models, and propagation mechanism of the PA. Finally, the application results and comparison analysis show the proposed models and algorithms are effective and feasible.

  4. 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.

  5. Research on Arrival/Departure Scheduling of Flights on Multirunways Based on Genetic Algorithm

    Directory of Open Access Journals (Sweden)

    Hang Zhou

    2014-01-01

    Full Text Available Aiming at the phenomenon of a large number of flight delays in the terminal area makes a reasonable scheduling for the approach and departure flights, which will minimize flight delay losses and improve runway utilization. This paper considered factors such as operating conditions and safety interval of multi runways; the maximum throughput and minimum flight delay losses as well as robustness were taken as objective functions; the model of optimization scheduling of approach and departure flights was established. Finally, the genetic algorithm was introduced to solve the model. The results showed that, in the program whose advance is not counted as a loss, its runway throughput is improved by 18.4%, the delay losses are reduced by 85.8%, and the robustness is increased by 20% compared with the results of FCFS (first come first served algorithm, while, compared with the program whose advance is counted as a loss, the runway throughput is improved by 15.16%, flight delay losses are decreased by 75.64%, and the robustness is also increased by 20%. The algorithm can improve the efficiency and reduce delay losses effectively and reduce the workload of controllers, thereby improving economic results.

  6. Manufacturing Scheduling Using Colored Petri Nets and Reinforcement Learning

    Directory of Open Access Journals (Sweden)

    Maria Drakaki

    2017-02-01

    Full Text Available Agent-based intelligent manufacturing control systems are capable to efficiently respond and adapt to environmental changes. Manufacturing system adaptation and evolution can be addressed with learning mechanisms that increase the intelligence of agents. In this paper a manufacturing scheduling method is presented based on Timed Colored Petri Nets (CTPNs and reinforcement learning (RL. CTPNs model the manufacturing system and implement the scheduling. In the search for an optimal solution a scheduling agent uses RL and in particular the Q-learning algorithm. A warehouse order-picking scheduling is presented as a case study to illustrate the method. The proposed scheduling method is compared to existing methods. Simulation and state space results are used to evaluate performance and identify system properties.

  7. 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......-ahead energy cost and expected real-time operation cost. In the real-time charging management, the cost of employing the charging flexibility from the EV owners is explicitly modelled. The aggregator uses a transactive market to manage the real-time charging demand to provide the regulating power. A model...... 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...

  8. Effects of activity-rest schedules on physiological strain and spinal load in hospital-based porters.

    Science.gov (United States)

    Beynon, C; Burke, J; Doran, D; Nevill, A

    2000-10-01

    Workers in physically demanding occupations require rest breaks to recover from physiological stress and biomechanical loading. Physiological stress can increase the risk of developing musculoskeletal disorders and repeated loading of the spine may increase the potential for incurring back pain. The aim of the study was to assess the impact of an altered activity-rest schedule on physiological and spinal loading in hospital-based porters. An existing 4-h activity-rest schedule was obtained from observations on eight male porters. This schedule formed the normal trial, which included two 5- and one 15-min breaks. An alternative 4-h schedule was proposed (experimental condition) that had two breaks each of 12.5 min. It was hypothesized that the experimental trial is more effective in promoting recovery from physiological strain and spinal shrinkage than the normal trial, due to the 5-min breaks being insufficient to allow physiological variables to return to resting levels or the intervertebral discs to reabsorb fluid. Ten males performed both test conditions and oxygen uptake VO2, heart rate, minute ventilation VE, perceived exertion and spinal shrinkage were recorded. There were no significant differences in any of the measured variables between the two trials (p > 0.05). Median heart rates were 78 (range 71-93) and 82 (71-90) beats.min(-1) for the normal trial and the experimental trial respectively, indicating that the activity was of low intensity. The light intensity was corroborated by the oxygen uptakes (0.75, range 0.65-0.94 1.min(-1)). Spinal shrinkage occurred to the same extent in the two trials (2.12 +/- 3.16 mm and 2.88 +/- 2.92 mm in the normal trial and the experimental trial respectively). Varying the length and positioning of the rest breaks did not significantly affect the physiological responses or magnitude of spinal shrinkage between the two trials. More physically demanding work than the porters' schedule should induce greater physiological

  9. Methods and time schedule for follow-up of intracranial aneurysms treated with endovascular embolization: a systematic review.

    Science.gov (United States)

    Serafin, Zbigniew; Strześniewski, Piotr; Lasek, Władysław; Beuth, Wojciech

    2011-01-01

    To review the diagnostic value of angiographic methods and the optimal timetable for follow-up imaging of patients after endovascular treatment of intracranial aneurysms. A comprehensive computer-aided search for relevant primary papers was performed using the MEDLINE, PubMed, Embase, and Cochrane Collaboration database from January 1991 to March 2011. Original papers were included that reported either diagnostic value of angiographic modalities for follow-up vs. digital subtracted angiography (DSA) or comparison of aneurysm occlusion rate in delayed vs. early follow-up. The systematic review identified 35 relevant studies: 3 on the diagnostic value of three-dimensional (3D) DSA, 30 on the performance of magnetic resonance angiography (MRA), and 3 on time schedules for follow-up. 3D DSA had sensitivity of 100%, and specificity of 58.3-94.7%. Magnetic resonance angiography had sensitivity of 28.4-100%, and specificity of 50.0-100%. The proportion of aneurysms that recanalized between the early follow-up examination at 6 months and the delayed imaging at 1.5-6.0 years was 0-2.5%. Magnetic resonance angiography seems to be the best imaging method for the follow-up. In selected cases, when invasive angiography is necessary, 3D DSA should be considered to improve the diagnostic accuracy. Most patients who present with stable and adequate aneurysm occlusion at 6 months after coiling may not require further follow-up. Key words: intracranial aneurysm, embolization, coils, digital subtracted angiography, magnetic resonance, computed tomography.

  10. Reputation-based Joint Scheduling of Households Appliances and Storage in a Microgrid with a Shared Battery

    DEFF Research Database (Denmark)

    AlSkaif, Tarek; Hernández, Adriana Carolina Luna; Guerrero Zapata, Manel

    2017-01-01

    . Deploying a shared storage unit in a residential microgrid is an alternative scenario that allows households to store their surplus renewable energy for a later use. However, this creates some challenges in managing the battery and the available energy resource in a fair way. In this paper, a reputation...... be achieved, in comparison with the classical scheduling scenario. The saving can reach up to 68% when dierent classes of households exist in the microgrid. The results also show that the fairness in energy allocation is guaranteed by the reputation-based policy, and that the total power absorbed from...... the main grid by the whole microgrid is significantly decreased....

  11. On the modeling of uplink inter-cell interference based on proportional fair scheduling

    KAUST Repository

    Tabassum, Hina

    2012-10-03

    We derive a semi-analytical expression for the uplink inter-cell interference (ICI) assuming proportional fair scheduling (with a maximum normalized signal-to-noise ratio (SNR) criterion) deployed in the cellular network. The derived expression can be customized for different models of channel statistics that can capture path loss, shadowing, and fading. Firstly, we derive an expression for the distribution of the locations of the allocated user in a given cell. Then, we derive the distribution and moment generating function of the uplink ICI from one interfering cell. Finally, we determine the moment generating function of the cumulative uplink ICI from all interfering cells. The derived expression is utilized to evaluate important network performance metrics such as outage probability and fairness among users. The accuracy of the derived expressions is verified by comparing the obtained results to Monte Carlo simulations. © 2012 IEEE.

  12. On the modeling of uplink inter-cell interference based on proportional fair scheduling

    KAUST Repository

    Tabassum, Hina; Yilmaz, Ferkan; Dawy, Zaher; Alouini, Mohamed-Slim

    2012-01-01

    We derive a semi-analytical expression for the uplink inter-cell interference (ICI) assuming proportional fair scheduling (with a maximum normalized signal-to-noise ratio (SNR) criterion) deployed in the cellular network. The derived expression can be customized for different models of channel statistics that can capture path loss, shadowing, and fading. Firstly, we derive an expression for the distribution of the locations of the allocated user in a given cell. Then, we derive the distribution and moment generating function of the uplink ICI from one interfering cell. Finally, we determine the moment generating function of the cumulative uplink ICI from all interfering cells. The derived expression is utilized to evaluate important network performance metrics such as outage probability and fairness among users. The accuracy of the derived expressions is verified by comparing the obtained results to Monte Carlo simulations. © 2012 IEEE.

  13. The Home Care Crew Scheduling Problem: Preference-based visit clustering and temporal dependencies

    DEFF Research Database (Denmark)

    Rasmussen, Matias Sevel; Justesen, Tor Fog; Dohn, Anders Høeg

    2012-01-01

    In the Home Care Crew Scheduling Problem a staff of home carers has to be assigned a number of visits to patients’ homes, such that the overall service level is maximised. The problem is a generalisation of the vehicle routing problem with time windows. Required travel time between visits and time...... preference constraints. The algorithm is tested both on real-life problem instances and on generated test instances inspired by realistic settings. The use of the specialised branching scheme on real-life problems is novel. The visit clustering decreases run times significantly, and only gives a loss...... windows of the visits must be respected. The challenge when assigning visits to home carers lies in the existence of soft preference constraints and in temporal dependencies between the start times of visits.We model the problem as a set partitioning problem with side constraints and develop an exact...

  14. Decentralized Ground Staff Scheduling

    DEFF Research Database (Denmark)

    Sørensen, M. D.; Clausen, Jens

    2002-01-01

    scheduling is investigated. The airport terminal is divided into zones, where each zone consists of a set of stands geographically next to each other. Staff is assigned to work in only one zone and the staff scheduling is planned decentralized for each zone. The advantage of this approach is that the staff...... work in a smaller area of the terminal and thus spends less time walking between stands. When planning decentralized the allocation of stands to flights influences the staff scheduling since the workload in a zone depends on which flights are allocated to stands in the zone. Hence solving the problem...... depends on the actual stand allocation but also on the number of zones and the layout of these. A mathematical model of the problem is proposed, which integrates the stand allocation and the staff scheduling. A heuristic solution method is developed and applied on a real case from British Airways, London...

  15. Entropy-based benchmarking methods

    NARCIS (Netherlands)

    Temurshoev, Umed

    2012-01-01

    We argue that benchmarking sign-volatile series should be based on the principle of movement and sign preservation, which states that a bench-marked series should reproduce the movement and signs in the original series. We show that the widely used variants of Denton (1971) method and the growth

  16. Scheduling Network Traffic for Grid Purposes

    DEFF Research Database (Denmark)

    Gamst, Mette

    This thesis concerns scheduling of network traffic in grid context. Grid computing consists of a number of geographically distributed computers, which work together for solving large problems. The computers are connected through a network. When scheduling job execution in grid computing, data...... transmission has so far not been taken into account. This causes stability problems, because data transmission takes time and thus causes delays to the execution plan. This thesis proposes the integration of job scheduling and network routing. The scientific contribution is based on methods from operations...... research and consists of six papers. The first four considers data transmission in grid context. The last two solves the data transmission problem, where the number of paths per data connection is bounded from above. The thesis shows that it is possible to solve the integrated job scheduling and network...

  17. A Novel Energy Efficient Topology Control Scheme Based on a Coverage-Preserving and Sleep Scheduling Model for Sensor Networks

    Science.gov (United States)

    Shi, Binbin; Wei, Wei; Wang, Yihuai; Shu, Wanneng

    2016-01-01

    In high-density sensor networks, scheduling some sensor nodes to be in the sleep mode while other sensor nodes remain active for monitoring or forwarding packets is an effective control scheme to conserve energy. In this paper, a Coverage-Preserving Control Scheduling Scheme (CPCSS) based on a cloud model and redundancy degree in sensor networks is proposed. Firstly, the normal cloud model is adopted for calculating the similarity degree between the sensor nodes in terms of their historical data, and then all nodes in each grid of the target area can be classified into several categories. Secondly, the redundancy degree of a node is calculated according to its sensing area being covered by the neighboring sensors. Finally, a centralized approximation algorithm based on the partition of the target area is designed to obtain the approximate minimum set of nodes, which can retain the sufficient coverage of the target region and ensure the connectivity of the network at the same time. The simulation results show that the proposed CPCSS can balance the energy consumption and optimize the coverage performance of the sensor network. PMID:27754405

  18. A Novel Energy Efficient Topology Control Scheme Based on a Coverage-Preserving and Sleep Scheduling Model for Sensor Networks.

    Science.gov (United States)

    Shi, Binbin; Wei, Wei; Wang, Yihuai; Shu, Wanneng

    2016-10-14

    In high-density sensor networks, scheduling some sensor nodes to be in the sleep mode while other sensor nodes remain active for monitoring or forwarding packets is an effective control scheme to conserve energy. In this paper, a Coverage-Preserving Control Scheduling Scheme (CPCSS) based on a cloud model and redundancy degree in sensor networks is proposed. Firstly, the normal cloud model is adopted for calculating the similarity degree between the sensor nodes in terms of their historical data, and then all nodes in each grid of the target area can be classified into several categories. Secondly, the redundancy degree of a node is calculated according to its sensing area being covered by the neighboring sensors. Finally, a centralized approximation algorithm based on the partition of the target area is designed to obtain the approximate minimum set of nodes, which can retain the sufficient coverage of the target region and ensure the connectivity of the network at the same time. The simulation results show that the proposed CPCSS can balance the energy consumption and optimize the coverage performance of the sensor network.

  19. A Novel Energy Efficient Topology Control Scheme Based on a Coverage-Preserving and Sleep Scheduling Model for Sensor Networks

    Directory of Open Access Journals (Sweden)

    Binbin Shi

    2016-10-01

    Full Text Available In high-density sensor networks, scheduling some sensor nodes to be in the sleep mode while other sensor nodes remain active for monitoring or forwarding packets is an effective control scheme to conserve energy. In this paper, a Coverage-Preserving Control Scheduling Scheme (CPCSS based on a cloud model and redundancy degree in sensor networks is proposed. Firstly, the normal cloud model is adopted for calculating the similarity degree between the sensor nodes in terms of their historical data, and then all nodes in each grid of the target area can be classified into several categories. Secondly, the redundancy degree of a node is calculated according to its sensing area being covered by the neighboring sensors. Finally, a centralized approximation algorithm based on the partition of the target area is designed to obtain the approximate minimum set of nodes, which can retain the sufficient coverage of the target region and ensure the connectivity of the network at the same time. The simulation results show that the proposed CPCSS can balance the energy consumption and optimize the coverage performance of the sensor network.

  20. Generation maintenance scheduling based on multiple ob jectives and their relationship analysis

    Institute of Scientific and Technical Information of China (English)

    Jun-peng ZHAN; Chuang-xin GUO; Qing-hua WU; Lu-liang ZHANG; Hong-jun FU

    2014-01-01

    In a market environment of power systems, each producer pursues its maximal profit while the independent system operator is in charge of the system reliability and the minimization of the total generation cost when generating the generation maintenance scheduling (GMS). Thus, the GMS is inherently a multi-objective optimization problem as its objectives usually conflict with each other. This paper proposes a multi-objective GMS model in a market environment which includes three types of objectives, i.e., each producer’s profit, the system reliability, and the total generation cost. The GMS model has been solved by the group search optimizer with multiple producers (GSOMP) on two test systems. The simulation results show that the model is well solved by the GSOMP with a set of evenly distributed Pareto-optimal solutions obtained. The simulation results also illustrate that one producer’s profit conflicts with another one’s, that the total generation cost does not conflict with the profit of the producer possessing the cheapest units while the total generation cost conflicts with the other producers’ profits, and that the reliability objective conflicts with the other objectives.

  1. 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.

  2. 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%.

  3. Diverse task scheduling for individualized requirements in cloud manufacturing

    Science.gov (United States)

    Zhou, Longfei; Zhang, Lin; Zhao, Chun; Laili, Yuanjun; Xu, Lida

    2018-03-01

    Cloud manufacturing (CMfg) has emerged as a new manufacturing paradigm that provides ubiquitous, on-demand manufacturing services to customers through network and CMfg platforms. In CMfg system, task scheduling as an important means of finding suitable services for specific manufacturing tasks plays a key role in enhancing the system performance. Customers' requirements in CMfg are highly individualized, which leads to diverse manufacturing tasks in terms of execution flows and users' preferences. We focus on diverse manufacturing tasks and aim to address their scheduling issue in CMfg. First of all, a mathematical model of task scheduling is built based on analysis of the scheduling process in CMfg. To solve this scheduling problem, we propose a scheduling method aiming for diverse tasks, which enables each service demander to obtain desired manufacturing services. The candidate service sets are generated according to subtask directed graphs. An improved genetic algorithm is applied to searching for optimal task scheduling solutions. The effectiveness of the scheduling method proposed is verified by a case study with individualized customers' requirements. The results indicate that the proposed task scheduling method is able to achieve better performance than some usual algorithms such as simulated annealing and pattern search.

  4. A reduced feedback proportional fair multiuser scheduling scheme

    KAUST Repository

    Shaqfeh, Mohammad

    2011-12-01

    Multiuser switched-diversity scheduling schemes were recently proposed in order to overcome the heavy feedback requirements of conventional opportunistic scheduling schemes by applying a threshold-based, distributed and ordered scheduling mechanism. A slight reduction in the prospected multiuser diversity gains is an acceptable trade-off for great savings in terms of required channel-state-information feedback messages. In this work, we propose a novel proportional fair multiuser switched-diversity scheduling scheme and we demonstrate that it can be optimized using a practical and distributed method to obtain the per-user feedback thresholds. We demonstrate by numerical examples that our reduced feedback proportional fair scheduler operates within 0.3 bits/sec/Hz from the achievable rates by the conventional full feedback proportional fair scheduler in Rayleigh fading conditions. © 2011 IEEE.

  5. Comparison of two dose and three dose human papillomavirus vaccine schedules: cost effectiveness analysis based on transmission model.

    Science.gov (United States)

    Jit, Mark; Brisson, Marc; Laprise, Jean-François; Choi, Yoon Hong

    2015-01-06

    To investigate the incremental cost effectiveness of two dose human papillomavirus vaccination and of additionally giving a third dose. Cost effectiveness study based on a transmission dynamic model of human papillomavirus vaccination. Two dose schedules for bivalent or quadrivalent human papillomavirus vaccines were assumed to provide 10, 20, or 30 years' vaccine type protection and cross protection or lifelong vaccine type protection without cross protection. Three dose schedules were assumed to give lifelong vaccine type and cross protection. United Kingdom. Males and females aged 12-74 years. No, two, or three doses of human papillomavirus vaccine given routinely to 12 year old girls, with an initial catch-up campaign to 18 years. Costs (from the healthcare provider's perspective), health related utilities, and incremental cost effectiveness ratios. Giving at least two doses of vaccine seems to be highly cost effective across the entire range of scenarios considered at the quadrivalent vaccine list price of £86.50 (€109.23; $136.00) per dose. If two doses give only 10 years' protection but adding a third dose extends this to lifetime protection, then the third dose also seems to be cost effective at £86.50 per dose (median incremental cost effectiveness ratio £17,000, interquartile range £11,700-£25,800). If two doses protect for more than 20 years, then the third dose will have to be priced substantially lower (median threshold price £31, interquartile range £28-£35) to be cost effective. Results are similar for a bivalent vaccine priced at £80.50 per dose and when the same scenarios are explored by parameterising a Canadian model (HPV-ADVISE) with economic data from the United Kingdom. Two dose human papillomavirus vaccine schedules are likely to be the most cost effective option provided protection lasts for at least 20 years. As the precise duration of two dose schedules may not be known for decades, cohorts given two doses should be closely

  6. Dwell scheduling algorithm based on analyzing scheduling interval for digital array radar%数字阵列雷达波束驻留调度间隔分析算法

    Institute of Scientific and Technical Information of China (English)

    赵洪涛; 程婷; 何子述

    2011-01-01

    针对数字阵列雷达波束驻留调度问题,研究了基于调度间隔分析的调度算法.该算法综合分析了1个调度间隔内申请执行的波束驻留任务,且调度过程中进行了脉冲交错.调度准则充分考虑了任务的工作方式优先级和截止期,并以任务丢失率、实现价值率、系统时间利用率作为评估指标.仿真结果表明修正截止期准则主要强调任务的紧迫性,修正工作方式优先级主要强调任务的重要性,而截止期--工作方式优先级和工作方式--截止期调度准则可以在二者间更好地折中,在总体性能上要优于其他调度准则.%Aiming at the problem of beam-dwell scheduling for digital array radar, the algorithm based on analyzing scheduling interval was studied. This algorithm analyzed the dwells applied to be executed in one scheduling interval and introduced pulse interleaving. The scheduling criterion took both priorities and deadlines into account fully, with the Task Drop Ratio, Hit Value Ratio, Time Utilization Ratio as evaluation indexes. The simulation results showed that the modified deadline criterion mainly emphasized the urgency of tasks, while the modified priority criterion mainly emphasized the importance of tasks; the deadline-priority and priority-deadline scheduling criterions could make good balance between urgency and importance. thus superior to other criterions in overall performances.

  7. Year-Round Irrigation Schedule for a Tomato–Maize Rotation System in Reservoir-Based Irrigation Schemes in Ghana

    Directory of Open Access Journals (Sweden)

    Ephraim Sekyi-Annan

    2018-05-01

    Full Text Available Improving irrigation management in semi-arid regions of Sub-Saharan Africa is crucial to respond to increasing variability in rainfall and overcome deficits in current irrigation schemes. In small-scale and medium-scale reservoir-based irrigation schemes in the Upper East region of Ghana, we explored options for improving the traditional, dry season irrigation practices and assessed the potential for supplemental irrigation in the rainy season. The AquaCrop model was used to (i assess current water management in the typical tomato-maize rotational system; (ii develop an improved irrigation schedule for dry season cultivation of tomato; and (iii determine the requirement for supplemental irrigation of maize in the rainy season under different climate scenarios. The improved irrigation schedule for dry season tomato cultivation would result in a water saving of 130–1325 mm compared to traditional irrigation practices, accompanied by approximately a 4–14% increase in tomato yield. The supplemental irrigation of maize would require 107–126 mm of water in periods of low rainfall and frequent dry spells, and 88–105 mm in periods of high rainfall and rare dry spells. Therefore, year-round irrigated crop production may be feasible, using water saved during dry season tomato cultivation for supplemental irrigation of maize in the rainy season.

  8. Effect of AQM-Based RLC Buffer Management on the eNB Scheduling Algorithm in LTE Network

    Directory of Open Access Journals (Sweden)

    Anup Kumar Paul

    2017-09-01

    Full Text Available With the advancement of the Long-Term Evolution (LTE network and smart-phones, most of today’s internet content is delivered via cellular links. Due to the nature of wireless signal propagation, the capacity of the last hop link can vary within a short period of time. Unfortunately, Transmission Control Protocol (TCP does not perform well in such scenarios, potentially leading to poor Quality of Service (QoS (e.g., end-to-end throughput and delay for the end user. In this work, we have studied the effect of Active Queue Management (AQM based congestion control and intra LTE handover on the performance of different Medium Access Control (MAC schedulers with TCP traffic by ns3 simulation. A proper AQM design in the Radio Link Control (RLC buffer of eNB in the LTE network leads to the avoidance of forced drops and link under-utilization along with robustness to a variety of network traffic-loads. We first demonstrate that the original Random Early Detection (RED linear dropping function cannot cope well with different traffic-load scenarios. Then, we establish a heuristic approach in which different non-linear functions are proposed with one parameter free to define. In our simulations, we demonstrate that the performance of different schedulers can be enhanced via proper dropping function.

  9. The impact of alternative pricing methods for drugs in California Workers' Compensation System: Fee-schedule pricing.

    Science.gov (United States)

    Wilson, Leslie; Turkistani, Fatema A; Huang, Wei; Tran, Dang M; Lin, Tracy Kuo

    2018-01-01

    California's Workers' Compensation System (CAWCS) Department of Industrial Relations questioned the adequacy of the current Medi-Cal fee-schedule pricing and requested analysis of alternatives that maximize price availability and maintain budget neutrality. To compare CAWCS pharmacy-dispensed (PD) drug prices under alternative fee schedules, and identify combinations of alternative benchmarks that have prices available for the largest percentage of PD drugs and that best reach budget neutrality. Claims transaction-level data (2011-2013) from CAWCS were used to estimate total annual PD pharmaceutical payments. Medi-Cal pricing data was from the Workman's Compensation Insurance System (WCIS). Average Wholesale Prices (AWP), Wholesale Acquisition Costs (WAC), Direct Prices (DP), Federal Upper Limit (FUL) prices, and National Average Drug Acquisition Costs (NADAC) were from Medi-Span. We matched National Drug Codes (NDCs), pricing dates, and drug quantity for comparisons. We report pharmacy-dispensed (PD) claims frequency, reimbursement matching rate, and paid costs by CAWCS as the reference price against all alternative price benchmarks. Of 12,529,977 CAWCS claims for pharmaceutical products 11.6% (1,462,814) were for PD drugs. Prescription drug cost for CAWCS was over $152M; $63.9M, $47.9M, and $40.6M in 2011-2013. Ninety seven percent of these CAWCS PD claims had a Medi-Cal price. Alternative mechanisms provided a price for fewer claims; NADAC 94.23%, AWP 90.94%, FUL 73.11%, WAC 66.98%, and DP 14.33%. Among CAWCS drugs with no Medi-Cal price in PD claims, AWP, WAC, NADAC, DP, and FUL provided prices for 96.7%, 63.14%, 24.82%, 20.83%, and 15.08% of claims. Overall CAWCS paid 100.52% of Medi-Cal, 60% of AWP, 97% of WAC, 309.53% of FUL, 103.83% of DP, and 136.27% of NADAC. CAWCS current Medi-Cal fee-schedule price list for PD drugs is more complete than all alternative fee-schedules. However, all reimbursement approaches would require combinations of pricing benchmarks

  10. TCSC control structures for line power scheduling and methods to determine their location and tuning to damp system oscillations

    Energy Technology Data Exchange (ETDEWEB)

    Martins, N; Pinto, H J.C.P.; Bianco, A [Centro de Pesquisas de Energia Eletrica (CEPEL), Rio de Janeiro, RJ (Brazil); Macedo, N J.P. [FURNAS, Rio de Janeiro, RJ (Brazil)

    1994-12-31

    This paper describes control structures and computer methods to enhance the practical use of thyristor controlled series compensation (TCSC) in power systems. The location and controller design of the TCS devices, to damp system oscillations, are based on modal analysis and frequency response techniques, respectively. Results are given for a large practical power system. (author) 15 refs., 18 figs., 5 tabs.

  11. 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 (BESS......) in order to make an optimal dispatch of resources in the microgrid and enhance the storage system lifetime while minimizing the cost of electric consumption. The load demand and generation profiles are derived from the analysis of consumption and renewable production (solar photovoltaic sources and wind...... turbines) of the Western Denmark electric grid. Thus, the proposed microgrid is mainly fed by renewable sources and few electricity is coming from the main grid (which helps operating costs minimization). In this respect, a cost analysis is performed to find the optimal hourly power output of the BESS...

  12. 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.

  13. Activity – based costing method

    Directory of Open Access Journals (Sweden)

    Èuchranová Katarína

    2001-06-01

    Full Text Available Activity based costing is a method of identifying and tracking the operating costs directly associated with processing items. It is the practice of focusing on some unit of output, such as a purchase order or an assembled automobile and attempting to determine its total as precisely as poccible based on the fixed and variable costs of the inputs.You use ABC to identify, quantify and analyze the various cost drivers (such as labor, materials, administrative overhead, rework. and to determine which ones are candidates for reduction.A processes any activity that accepts inputs, adds value to these inputs for customers and produces outputs for these customers. The customer may be either internal or external to the organization. Every activity within an organization comprimes one or more processes. Inputs, controls and resources are all supplied to the process.A process owner is the person responsible for performing and or controlling the activity.The direction of cost through their contact to partial activity and processes is a new modern theme today. Beginning of this method is connected with very important changes in the firm processes.ABC method is a instrument , that bring a competitive advantages for the firm.

  14. Scheduling the scheduling task : a time management perspective on scheduling

    NARCIS (Netherlands)

    Larco Martinelli, J.A.; Wiers, V.C.S.; Fransoo, J.C.

    2013-01-01

    Time is the most critical resource at the disposal of schedulers. Hence, an adequate management of time from the schedulers may impact positively on the scheduler’s productivity and responsiveness to uncertain scheduling environments. This paper presents a field study of how schedulers make use of

  15. Performance analysis of switch-based multiuser scheduling schemes with adaptive modulation in spectrum sharing systems

    KAUST Repository

    Qaraqe, Marwa; Abdallah, Mohamed M.; Serpedin, Erchin; Alouini, Mohamed-Slim

    2014-01-01

    the average spectral efficiency by selecting the user that reports the best channel quality. In order to alleviate the relatively high feedback required by the first scheme, a second scheme based on the concept of switched diversity is proposed, where the base

  16. Self-scheduling with Microsoft Excel.

    Science.gov (United States)

    Irvin, S A; Brown, H N

    1999-01-01

    Excessive time was being spent by the emergency department (ED) staff, head nurse, and unit secretary on a complex 6-week manual self-scheduling system. This issue, plus inevitable errors and staff dissatisfaction, resulted in a manager-lead initiative to automate elements of the scheduling process using Microsoft Excel. The implementation of this initiative included: common coding of all 8-hour and 12-hour shifts, with each 4-hour period represented by a cell; the creation of a 6-week master schedule using the "count-if" function of Excel based on current staffing guidelines; staff time-off requests then entered by the department secretary; the head nurse, with staff input, then fine-tuned the schedule to provide even unit coverage. Outcomes of these changes included an increase in staff satisfaction, time saved by the head nurse, and staff work time saved because there was less arguing about the schedule. Ultimately, the automated self-scheduling method was expanded to the entire 700-bed hospital.

  17. Conflicts between employee preferences and ergonomic recommendations in shift scheduling: regulation based on consent is not sufficient

    Directory of Open Access Journals (Sweden)

    Johannes Gärtner

    2004-12-01

    Full Text Available OBJECTIVE: Contribution to the discussion of the role of participation/consent of employees in working hours regulation. METHODS: Exploratory analysis of conflicts between preferences of employees and ergonomic recommendations in shift scheduling by analysing a large number of participative shift scheduling projects. RESULTS: The analysis showed that very often the pursuit of higher income played the major role in the decision making process of employees and employees preferred working hours in conflict with health and safety principles. CONCLUSIONS: First, the consent of employees or the works council alone does not ensure ergonomically sound schedules. Besides consent, risk assessment procedures seem to be a promising but difficult approach. Secondly, more research is necessary to check the applicability of recommendations under various settings, to support the risk assessment processes and to improve regulatory approaches to working hours.OBJETIVO: Contribuir para a discussão do papel da participação/consentimento dos empregados na regulamentação das horas de trabalho. MÉTODOS: Realizou-se um estudo exploratório dos conflitos existentes entre as preferências dos empregados e as recomendações ergonômicas no planejamento de esquemas de trabalho em turnos, analisando-se um grande número de projetos participativos de planejamento dos turnos. RESULTADOS: O estudo mostrou que, com freqüência, a busca por um rendimento maior teve um papel importante no processo de tomada de decisão dos empregados, quando estes optaram pelas horas de trabalho em oposição aos princípios de saúde e segurança. CONCLUSÕES: Em primeiro lugar, o consentimento dos empregados ou da comissão de trabalhadores por si só não garante horários salutares do ponto de vista ergonômico. Além do consentimento, processos de avaliação de risco parecem ser uma abordagem promissora embora complicada. Em segundo lugar, fazem-se necessários mais estudos para

  18. 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

  19. 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.

  20. Deterministic and stochastic approach for safety and reliability optimization of captive power plant maintenance scheduling using GA/SA-based hybrid techniques: A comparison of results

    International Nuclear Information System (INIS)

    Mohanta, Dusmanta Kumar; Sadhu, Pradip Kumar; Chakrabarti, R.

    2007-01-01

    This paper presents a comparison of results for optimization of captive power plant maintenance scheduling using genetic algorithm (GA) as well as hybrid GA/simulated annealing (SA) techniques. As utilities catered by captive power plants are very sensitive to power failure, therefore both deterministic and stochastic reliability objective functions have been considered to incorporate statutory safety regulations for maintenance of boilers, turbines and generators. The significant contribution of this paper is to incorporate stochastic feature of generating units and that of load using levelized risk method. Another significant contribution of this paper is to evaluate confidence interval for loss of load probability (LOLP) because some variations from optimum schedule are anticipated while executing maintenance schedules due to different real-life unforeseen exigencies. Such exigencies are incorporated in terms of near-optimum schedules obtained from hybrid GA/SA technique during the final stages of convergence. Case studies corroborate that same optimum schedules are obtained using GA and hybrid GA/SA for respective deterministic and stochastic formulations. The comparison of results in terms of interval of confidence for LOLP indicates that levelized risk method adequately incorporates the stochastic nature of power system as compared with levelized reserve method. Also the interval of confidence for LOLP denotes the possible risk in a quantified manner and it is of immense use from perspective of captive power plants intended for quality power

  1. A Bayesian matching pursuit based scheduling algorithm for feedback reduction in MIMO broadcast channels

    KAUST Repository

    Shibli, Hussain J.; Eltayeb, Mohammed E.; Al-Naffouri, Tareq Y.

    2013-01-01

    challenges are faced during uplink transmission. First of all, the statistics of the noisy and fading feedback channels are unknown at the base station (BS) and channel training is usually required from all users. Secondly, the amount of network resources

  2. Scheduling with Group Dynamics: a Multi-Robot Task Allocation Algorithm based on Vacancy Chains

    National Research Council Canada - National Science Library

    Dahl, Torbjorn S; Mataric, Maja J; Sukhatme, Gaurav S

    2002-01-01

    .... We present a multi-robot task allocation algorithm that is sensitive to group dynamics. Our algorithm is based on vacancy chains, a resource distribution process common in human and animal societies...

  3. Off-Line and Dynamic Production Scheduling – A Comparative Case Study

    Directory of Open Access Journals (Sweden)

    Bożek Andrzej

    2016-03-01

    Full Text Available A comprehensive case study of manufacturing scheduling solutions development is given. It includes highly generalized scheduling problem as well as a few scheduling modes, methods and problem models. The considered problem combines flexible job shop structure, lot streaming with variable sublots, transport times, setup times, and machine calendars. Tabu search metaheuristic and constraint programming methods have been used for the off-line scheduling. Two dynamic scheduling methods have also been implemented, i.e., dispatching rules for the completely reactive scheduling and a multi-agent system for the predictivereactive scheduling. In these implementations three distinct models of the problem have been used, based on: graph representation, optimal constraint satisfaction, and Petri net formalism. Each of these solutions has been verified in computational experiments. The results are compared and some findings about advantages, disadvantages, and suggestions on using the solutions are formulated.

  4. Test-Access Planning and Test Scheduling for Embedded Core-Based System Chips

    OpenAIRE

    Goel, Sandeep Kumar

    2005-01-01

    Advances in the semiconductor process technology enable the creation of a complete system on one single die, the so-called system chip or SOC. To reduce time-to-market for large SOCs, reuse of pre-designed and pre-veried blocks called cores is employed. Like the design style, testing of SOCs can be best approached in a core-based fashion. In order to enable core-based test development, an embedded core should be isolated from its surrounding circuitry and electrical test access from chip pins...

  5. Preoperative home-based physical therapy versus usual care to improve functional health of frail older adults scheduled for elective total hip arthroplasty: A pilot randomized controlled trial

    NARCIS (Netherlands)

    Oosting, E.; Jans, M.P.; Dronkers, J.J.; Naber, R.H.; Dronkers-Landman, C.M.; Appelman-De Vries, S.M.; Meeteren, N.L. van

    2012-01-01

    Preoperative home-based physical therapy versus usual care to improve functional health of frail older adults scheduled for elective total hip arthroplasty: a pilot randomized controlled trial. Objective: To investigate the feasibility and preliminary effectiveness of a home-based intensive exercise

  6. Artificial intelligence approaches to astronomical observation scheduling

    Science.gov (United States)

    Johnston, Mark D.; Miller, Glenn

    1988-01-01

    Automated scheduling will play an increasing role in future ground- and space-based observatory operations. Due to the complexity of the problem, artificial intelligence technology currently offers the greatest potential for the development of scheduling tools with sufficient power and flexibility to handle realistic scheduling situations. Summarized here are the main features of the observatory scheduling problem, how artificial intelligence (AI) techniques can be applied, and recent progress in AI scheduling for Hubble Space Telescope.

  7. Comparison of traditional and ET-based irrigation scheduling of surface-irrigated cotton in the arid southwestern USA

    Science.gov (United States)

    The use of irrigation scheduling tools to produce cotton under-surface irrigation in the arid southwesternUSA is minimal. In the State of Arizona, where traditional irrigation scheduling is the norm, producersuse an average of 1460 mm annually to grow a cotton crop. The purpose of this paper was to ...

  8. 2007 Wholesale Power Rate Schedules : 2007 General Rate Schedule Provisions.

    Energy Technology Data Exchange (ETDEWEB)

    United States. Bonneville Power Administration.

    2006-11-01

    This schedule is available for the contract purchase of Firm Power to be used within the Pacific Northwest (PNW). Priority Firm (PF) Power may be purchased by public bodies, cooperatives, and Federal agencies for resale to ultimate consumers, for direct consumption, and for Construction, Test and Start-Up, and Station Service. Rates in this schedule are in effect beginning October 1, 2006, and apply to purchases under requirements Firm Power sales contracts for a three-year period. The Slice Product is only available for public bodies and cooperatives who have signed Slice contracts for the FY 2002-2011 period. Utilities participating in the Residential Exchange Program (REP) under Section 5(c) of the Northwest Power Act may purchase Priority Firm Power pursuant to the Residential Exchange Program. Rates under contracts that contain charges that escalate based on BPA's Priority Firm Power rates shall be based on the three-year rates listed in this rate schedule in addition to applicable transmission charges. This rate schedule supersedes the PF-02 rate schedule, which went into effect October 1, 2001. Sales under the PF-07 rate schedule are subject to BPA's 2007 General Rate Schedule Provisions (2007 GRSPs). Products available under this rate schedule are defined in the 2007 GRSPs. For sales under this rate schedule, bills shall be rendered and payments due pursuant to BPA's 2007 GRSPs and billing process.

  9. Exploratory model analysis of the Space Based Infrared System (SBIRS) Low Global Scheduler problem

    OpenAIRE

    Morgan, Brian L.

    1999-01-01

    Approved for public release; distribution is unlimited Proliferation of theater ballistic missile technologies to potential U.S. adversaries necessitates that the U.S. employ a defensive system to counter this threat. The system that is being developed is called the Space-Based Infrared System (SBIRS) "System of Systems". The SBIRS Low component of the SBIRS "System of Systems" will track strategic and theater ballistic missiles from launch to reentry and relay necessary cueing data to mis...

  10. Scheduling for Multiuser MIMO Downlink Channels with Ranking-Based Feedback

    Science.gov (United States)

    Kountouris, Marios; Sälzer, Thomas; Gesbert, David

    2008-12-01

    We consider a multi-antenna broadcast channel with more single-antenna receivers than transmit antennas and partial channel state information at the transmitter (CSIT). We propose a novel type of CSIT representation for the purpose of user selection, coined as ranking-based feedback. Each user calculates and feeds back the rank, an integer between 1 and W + 1, of its instantaneous channel quality information (CQI) among a set of W past CQI measurements. Apart from reducing significantly the required feedback load, ranking-based feedback enables the transmitter to select users that are on the highest peak (quantile) with respect to their own channel distribution, independently of the distribution of other users. It can also be shown that this feedback metric can restore temporal fairness in heterogeneous networks, in which users' channels are not identically distributed and mobile terminals experience different average signal-to-noise ratio (SNR). The performance of a system that performs user selection using ranking-based CSIT in the context of random opportunistic beamforming is analyzed, and we provide design guidelines on the number of required past CSIT samples and the impact of finite W on average throughput. Simulation results show that feedback reduction of order of 40-50% can be achieved with negligible decrease in system throughput.

  11. Cloud-based multi-agent architecture for effective planning and scheduling of distributed manufacturing

    DEFF Research Database (Denmark)

    Mishra, Nishikant; Singh, Akshit; Kumari, Sushma

    2016-01-01

    at distinct locations are being assembled in a plant to develop the final product. In this complex scenario, manufacturing firms have to be responsive enough to cope with the fluctuating demand of customers. To accomplish it, there is a need to develop an integrated, dynamic and autonomous system....... In this article, a self-reactive cloud-based multi-agent architecture for distributed manufacturing system is developed. The proposed architecture will assist manufacturing industry to establish real-time information exchange between the autonomous agents, clients, suppliers and manufacturing unit. The mechanism...

  12. Gain-scheduling control of a monocular vision-based human-following robot

    CSIR Research Space (South Africa)

    Burke, Michael G

    2011-08-01

    Full Text Available , R. and Zisserman, A. (2004). Multiple View Geometry in Computer Vision. Cambridge University Press, 2nd edition. Hutchinson, S., Hager, G., and Corke, P. (1996). A tutorial on visual servo control. IEEE Trans. on Robotics and Automation, 12... environment, in a passive manner, at relatively high speeds and low cost. The control of mobile robots using vision in the feed- back loop falls into the well-studied field of visual servo control. Two primary approaches are used: image-based visual...

  13. LMI-based gain scheduled controller synthesis for a class of linear parameter varying systems

    DEFF Research Database (Denmark)

    Bendtsen, Jan Dimon; Anderson, Brian; Lanzon, Alexander

    2006-01-01

    This paper presents a novel method for constructing controllers for a class of single-input multiple-output (SIMO) linear parameter varying (LPV) systems. This class of systems encompasses many physical systems, in particular systems where individual components vary with time, and is therefore...... of significant practical relevance to control designers. The control design presented in this paper has the properties that the system matrix of the closed loop is multi-affine in the various scalar parameters, and that the resulting controller ensures a certain degree of stability for the closed loop even when...... as a standard linear time-invariant (LTI) design combined with a set of linear matrix inequalities, which can be solved efficiently with software tools. The design procedure is illustrated by a numerical example....

  14. Probabilistic methods of optimization of scheduled tests for heat equipment of safety systems of reactor at full power

    International Nuclear Information System (INIS)

    Bilej, D.V.; Fridman, N.A.; Kolykhanov, V.N.; Skalozubov, V.I.

    2004-01-01

    This article generalises the basic results of a long-term teamwork with respect to a scientific and technical substantiation of perfection of the regulations of safe operation power units with VVER. This perfection is concerning a periodicity and volumes of tests of safety systems when a reactor works at full power. The article shows that the application of the probabilistic approaches connected to minimisation of a risk criterion function is an effective methodical base for the optimisation. For certain safety systems of serial power units with VVER 1000 the results of calculated substantiations are presented

  15. Intelligent Control of Diesel Generators Using Gain-Scheduling Based on Online External-Load Estimation

    DEFF Research Database (Denmark)

    Mai, Christian; Jepsen, Kasper Lund; Yang, Zhenyu

    2014-01-01

    The development of an intelligent control solution for a wide range of diesel generators is discussed. Compared with most existing solutions, the advantages of the proposed solution lie in two folds: (i) The proposed control has the plug-and-play capability which is reflected by an automatic...... recognition procedure when it is plugged into a specific diesel generator, such that some extensive manual-tuning of the installed controller can be significantly reduced; (ii) The proposed control has an real-time adaptability by using the online external load estimation, such that the integrated system can...... keep a consistent performance for a wide range of operating conditions. Technically, a general nonlinear dynamic model is firstly developed based on fundamental principles of diesel generators. Then, the system parameters of this model can be identified experimentally or partially retrieved from...

  16. CMS multicore scheduling strategy

    International Nuclear Information System (INIS)

    Yzquierdo, Antonio Pérez-Calero; Hernández, Jose; Holzman, Burt; Majewski, Krista; McCrea, Alison

    2014-01-01

    In the next years, processor architectures based on much larger numbers of cores will be most likely the model to continue 'Moore's Law' style throughput gains. This not only results in many more jobs in parallel running the LHC Run 1 era monolithic applications, but also the memory requirements of these processes push the workernode architectures to the limit. One solution is parallelizing the application itself, through forking and memory sharing or through threaded frameworks. CMS is following all of these approaches and has a comprehensive strategy to schedule multicore jobs on the GRID based on the glideinWMS submission infrastructure. The main component of the scheduling strategy, a pilot-based model with dynamic partitioning of resources that allows the transition to multicore or whole-node scheduling without disallowing the use of single-core jobs, is described. This contribution also presents the experiences made with the proposed multicore scheduling schema and gives an outlook of further developments working towards the restart of the LHC in 2015.

  17. Nonlinear model-based control of the Czochralski process III: Proper choice of manipulated variables and controller parameter scheduling

    Science.gov (United States)

    Neubert, M.; Winkler, J.

    2012-12-01

    This contribution continues an article series [1,2] about the nonlinear model-based control of the Czochralski crystal growth process. The key idea of the presented approach is to use a sophisticated combination of nonlinear model-based and conventional (linear) PI controllers for tracking of both, crystal radius and growth rate. Using heater power and pulling speed as manipulated variables several controller structures are possible. The present part tries to systematize the properties of the materials to be grown in order to get unambiguous decision criteria for a most profitable choice of the controller structure. For this purpose a material specific constant M called interface mobility and a more process specific constant S called system response number are introduced. While the first one summarizes important material properties like thermal conductivity and latent heat the latter one characterizes the process by evaluating the average axial thermal gradients at the phase boundary and the actual growth rate at which the crystal is grown. Furthermore these characteristic numbers are useful for establishing a scheduling strategy for the PI controller parameters in order to improve the controller performance. Finally, both numbers give a better understanding of the general thermal system dynamics of the Czochralski technique.

  18. wayGoo recommender system: personalized recommendations for events scheduling, based on static and real-time information

    Science.gov (United States)

    Thanos, Konstantinos-Georgios; Thomopoulos, Stelios C. A.

    2016-05-01

    wayGoo is a fully functional application whose main functionalities include content geolocation, event scheduling, and indoor navigation. However, significant information about events do not reach users' attention, either because of the size of this information or because some information comes from real - time data sources. The purpose of this work is to facilitate event management operations by prioritizing the presented events, based on users' interests using both, static and real - time data. Through the wayGoo interface, users select conceptual topics that are interesting for them. These topics constitute a browsing behavior vector which is used for learning users' interests implicitly, without being intrusive. Then, the system estimates user preferences and return an events list sorted from the most preferred one to the least. User preferences are modeled via a Naïve Bayesian Network which consists of: a) the `decision' random variable corresponding to users' decision on attending an event, b) the `distance' random variable, modeled by a linear regression that estimates the probability that the distance between a user and each event destination is not discouraging, ` the seat availability' random variable, modeled by a linear regression, which estimates the probability that the seat availability is encouraging d) and the `relevance' random variable, modeled by a clustering - based collaborative filtering, which determines the relevance of each event users' interests. Finally, experimental results show that the proposed system contribute essentially to assisting users in browsing and selecting events to attend.

  19. Schedules of Controlled Substances: Temporary Placement of 4-Fluoroisobutyryl Fentanyl into Schedule I. Temporary scheduling order.

    Science.gov (United States)

    2017-05-03

    The Administrator of the Drug Enforcement Administration is issuing this temporary scheduling order to schedule the synthetic opioid, N-(4-fluorophenyl)-N-(1-phenethylpiperidin-4-yl)isobutyramide (4-fluoroisobutyryl fentanyl or para-fluoroisobutyryl fentanyl), and its isomers, esters, ethers, salts and salts of isomers, esters, and ethers, into schedule I pursuant to the temporary scheduling provisions of the Controlled Substances Act. This action is based on a finding by the Administrator that the placement of 4-fluoroisobutyryl fentanyl into schedule I of the Controlled Substances Act is necessary to avoid an imminent hazard to the public safety. As a result of this order, the regulatory controls and administrative, civil, and criminal sanctions applicable to schedule I controlled substances will be imposed on persons who handle (manufacture, distribute, reverse distribute, import, export, engage in research, conduct instructional activities or chemical analysis, or possess), or propose to handle, 4-fluoroisobutyryl fentanyl.

  20. Integrated network design and scheduling problems :

    Energy Technology Data Exchange (ETDEWEB)

    Nurre, Sarah G.; Carlson, Jeffrey J.

    2014-01-01

    We consider the class of integrated network design and scheduling problems. These problems focus on selecting and scheduling operations that will change the characteristics of a network, while being speci cally concerned with the performance of the network over time. Motivating applications of INDS problems include infrastructure restoration after extreme events and building humanitarian distribution supply chains. While similar models have been proposed, no one has performed an extensive review of INDS problems from their complexity, network and scheduling characteristics, information, and solution methods. We examine INDS problems under a parallel identical machine scheduling environment where the performance of the network is evaluated by solving classic network optimization problems. We classify that all considered INDS problems as NP-Hard and propose a novel heuristic dispatching rule algorithm that selects and schedules sets of arcs based on their interactions in the network. We present computational analysis based on realistic data sets representing the infrastructures of coastal New Hanover County, North Carolina, lower Manhattan, New York, and a realistic arti cial community CLARC County. These tests demonstrate the importance of a dispatching rule to arrive at near-optimal solutions during real-time decision making activities. We extend INDS problems to incorporate release dates which represent the earliest an operation can be performed and exible release dates through the introduction of specialized machine(s) that can perform work to move the release date earlier in time. An online optimization setting is explored where the release date of a component is not known.

  1. A new distributed systems scheduling algorithm: a swarm intelligence approach

    Science.gov (United States)

    Haghi Kashani, Mostafa; Sarvizadeh, Raheleh; Jameii, Mahdi

    2011-12-01

    The scheduling problem in distributed systems is known as an NP-complete problem, and methods based on heuristic or metaheuristic search have been proposed to obtain optimal and suboptimal solutions. The task scheduling is a key factor for distributed systems to gain better performance. In this paper, an efficient method based on memetic algorithm is developed to solve the problem of distributed systems scheduling. With regard to load balancing efficiently, Artificial Bee Colony (ABC) has been applied as local search in the proposed memetic algorithm. The proposed method has been compared to existing memetic-Based approach in which Learning Automata method has been used as local search. The results demonstrated that the proposed method outperform the above mentioned method in terms of communication cost.

  2. Shiftwork Scheduling for the 1990s.

    Science.gov (United States)

    Coleman, Richard M.

    1989-01-01

    The author discusses the problems of scheduling shift work, touching on such topics as employee desires, health requirements, and business needs. He presents a method for developing shift schedules that addresses these three areas. Implementation hints are also provided. (CH)

  3. Nuclear power plant maintenance scheduling dilemma: a genetic algorithm approach

    International Nuclear Information System (INIS)

    Mahdavi, M.H.; Modarres, M.

    2004-01-01

    There are huge numbers of components scheduled for maintenance when a nuclear power plant is shut down. Among these components, a number of them are safety related which their operability as well as reliability when plant becomes up is main concerns. Not performing proper maintenance on this class of components/system would impose substantial risk on operating the NPP. In this paper a new approach based on genetic algorithms is presented to optimize the NPP maintenance schedule during shutdown. following this approach the cost incurred by maintenance activities for each schedule is balanced with the risk imposed by the maintenance scheduling plan to the plant operation status when it is up. The risk model implemented in the GA scheduler as its evaluation function is developed on the basis of the probabilistic risk assessment methodology. the Ga optimizers itself is shown to be superior compared to other optimization methods such as the monte carlo technique

  4. Aircraft Route Recovery Based on An Improved GRASP Method

    Directory of Open Access Journals (Sweden)

    Yang He

    2017-01-01

    Full Text Available Aircrafts maintenance, temporary airport closures are common factors that disrupt normal flight schedule. The aircraft route recovery aims to recover original schedules by some strategies, including flights swaps, and cancellations, which is a NP-hard problem. This paper proposes an improved heuristic procedure based on Greedy Random Adaptive Search Procedure (GRASP to solve this problem. The effectiveness and high global optimization capability of the heuristic is illustrated through experiments based on large-scale problems. Compared to the original one, it is shown that the improved procedure can find feasible flight recovered schedules with lower cost in a short time.

  5. A New Evolutionary Algorithm Based on Bacterial Evolution and Its Application for Scheduling A Flexible Manufacturing System

    Directory of Open Access Journals (Sweden)

    Chandramouli Anandaraman

    2012-01-01

    Full Text Available A new evolutionary computation algorithm, Superbug algorithm, which simulates evolution of bacteria in a culture, is proposed. The algorithm is developed for solving large scale optimization problems such as scheduling, transportation and assignment problems. In this work, the algorithm optimizes machine schedules in a Flexible Manufacturing System (FMS by minimizing makespan. The FMS comprises of four machines and two identical Automated Guided Vehicles (AGVs. AGVs are used for carrying jobs between the Load/Unload (L/U station and the machines. Experimental results indicate the efficiency of the proposed algorithm in its optimization performance in scheduling is noticeably superior to other evolutionary algorithms when compared to the best results reported in the literature for FMS Scheduling.

  6. A model-based gain scheduling approach for controlling the common-rail system for GDI engines

    Science.gov (United States)

    di Gaeta, Alessandro; Montanaro, Umberto; Fiengo, Giovanni; Palladino, Angelo; Giglio, Veniero

    2012-04-01

    The progressive reduction in vehicle emission requirements have forced the automotive industry to invest in research for developing alternative and more efficient control strategies. All control features and resources are permanently active in an electronic control unit (ECU), ensuring the best performance with respect to emissions, fuel economy, driveability and diagnostics, independently from engine working point. In this article, a considerable step forward has been achieved by the common-rail technology which has made possible to vary the injection pressure over the entire engine speed range. As a consequence, the injection of a fixed amount of fuel is more precise and multiple injections in a combustion cycle can be made. In this article, a novel gain scheduling pressure controller for gasoline direct injection (GDI) engine is designed to stabilise the mean fuel pressure into the rail and to track demanded pressure trajectories. By exploiting a simple control-oriented model describing the mean pressure dynamics in the rail, the control structure turns to be simple enough to be effectively implemented in commercial ECUs. Experimental results in a wide range of operating points confirm the effectiveness of the proposed control method to tame efficiently the mean value pressure dynamics of the plant showing a good accuracy and robustness with respect to unavoidable parameters uncertainties, unmodelled dynamics, and hidden coupling terms.

  7. Fuzzy-Logic-Based Gain-Scheduling Control for State-of-Charge Balance of Distributed Energy Storage Systems for DC Microgrids

    DEFF Research Database (Denmark)

    Aldana, Nelson Leonardo Diaz; Dragicevic, Tomislav; Vasquez, Juan Carlos

    2014-01-01

    -charge or deep-discharge in one of the energy storage units. Primary control in a microgrid is responsible for power sharing among units; and droop control is typically used in this stage. This paper proposes a modular and decentralized gain-scheduling control strategy based on fuzzy logic that ensures balanced...

  8. Re-scheduling nursing shifts: Scoping the challenge and examining the potential of mathematical model based tools

    OpenAIRE

    Clark, A.; Moule, P.; Topping, A.; Serpell, M.

    2015-01-01

    Aims: To review research in the literature on nursing shift scheduling/rescheduling, and report key issues identified in a listening exercise with managers in four English NHS trusts to inform the development of mathematical tools for rescheduling decision-making.\\ud Background: Shift rescheduling is unrecognised as an everyday time-consuming management task with different imperatives than scheduling. Poor rescheduling decisions can have quality, cost and morale implications.\\ud Evaluation: A...

  9. A Review Of Fault Tolerant Scheduling In Multicore Systems

    Directory of Open Access Journals (Sweden)

    Shefali Malhotra

    2015-05-01

    Full Text Available Abstract In this paper we have discussed about various fault tolerant task scheduling algorithm for multi core system based on hardware and software. Hardware based algorithm which is blend of Triple Modulo Redundancy and Double Modulo Redundancy in which Agricultural Vulnerability Factor is considered while deciding the scheduling other than EDF and LLF scheduling algorithms. In most of the real time system the dominant part is shared memory.Low overhead software based fault tolerance approach can be implemented at user-space level so that it does not require any changes at application level. Here redundant multi-threaded processes are used. Using those processes we can detect soft errors and recover from them. This method gives low overhead fast error detection and recovery mechanism. The overhead incurred by this method ranges from 0 to 18 for selected benchmarks. Hybrid Scheduling Method is another scheduling approach for real time systems. Dynamic fault tolerant scheduling gives high feasibility rate whereas task criticality is used to select the type of fault recovery method in order to tolerate the maximum number of faults.

  10. Maternal Nonstandard Work Schedules and Breastfeeding Behaviors.

    Science.gov (United States)

    Zilanawala, Afshin

    2017-06-01

    Objectives Although maternal employment rates have increased in the last decade in the UK, there is very little research investigating the linkages between maternal nonstandard work schedules (i.e., work schedules outside of the Monday through Friday, 9-5 schedule) and breastfeeding initiation and duration, especially given the wide literature citing the health advantages of breastfeeding for mothers and children. Methods This paper uses a population-based, UK cohort study, the Millennium Cohort Study (n = 17,397), to investigate the association between types of maternal nonstandard work (evening, night, away from home overnight, and weekends) and breastfeeding behaviors. Results In unadjusted models, exposure to evening shifts was associated with greater odds of breastfeeding initiation (OR 1.71, CI 1.50-1.94) and greater odds of short (OR 1.55, CI 1.32-1.81), intermediate (OR 2.01, CI 1.64-2.47), prolonged partial duration (OR 2.20, CI 1.78-2.72), and prolonged exclusive duration (OR 1.53, CI 1.29-1.82), compared with mothers who were unemployed and those who work other types of nonstandard shifts. Socioeconomic advantage of mothers working evening schedules largely explained the higher odds of breastfeeding initiation and duration. Conclusions Socioeconomic characteristics explain more breastfeeding behaviors among mothers working evening shifts. Policy interventions to increase breastfeeding initiation and duration should consider the timing of maternal work schedules.

  11. A low delay transmission method of multi-channel video based on FPGA

    Science.gov (United States)

    Fu, Weijian; Wei, Baozhi; Li, Xiaobin; Wang, Quan; Hu, Xiaofei

    2018-03-01

    In order to guarantee the fluency of multi-channel video transmission in video monitoring scenarios, we designed a kind of video format conversion method based on FPGA and its DMA scheduling for video data, reduces the overall video transmission delay.In order to sace the time in the conversion process, the parallel ability of FPGA is used to video format conversion. In order to improve the direct memory access (DMA) writing transmission rate of PCIe bus, a DMA scheduling method based on asynchronous command buffer is proposed. The experimental results show that this paper designs a low delay transmission method based on FPGA, which increases the DMA writing transmission rate by 34% compared with the existing method, and then the video overall delay is reduced to 23.6ms.

  12. Efficient Academic Scheduling at the U.S. Naval Academy

    National Research Council Canada - National Science Library

    Zane, David

    2003-01-01

    This research project examined academic scheduling problems at the U.S. Naval Academy. The focus was on devising methods to construct good final exam schedules and improve existing course schedules by facilitation course changes...

  13. A nodal method based on matrix-response method

    International Nuclear Information System (INIS)

    Rocamora Junior, F.D.; Menezes, A.

    1982-01-01

    A nodal method based in the matrix-response method, is presented, and its application to spatial gradient problems, such as those that exist in fast reactors, near the core - blanket interface, is investigated. (E.G.) [pt

  14. Job shop scheduling with makespan objective: A heuristic approach

    Directory of Open Access Journals (Sweden)

    Mohsen Ziaee

    2014-04-01

    Full Text Available Job shop has been considered as one of the most challenging scheduling problems and there are literally tremendous efforts on reducing the complexity of solution procedure for solving job shop problem. This paper presents a heuristic method to minimize makespan for different jobs in a job shop scheduling. The proposed model is based on a constructive procedure to obtain good quality schedules, very quickly. The performance of the proposed model of this paper is examined on standard benchmarks from the literature in order to evaluate its performance. Computational results show that, despite its simplicity, the proposed heuristic is computationally efficient and practical approach for the problem.

  15. 基于ISM的动态优先级调度算法%Dynamic Priority Schedule Algorithm Based on ISM

    Institute of Scientific and Technical Information of China (English)

    余祖峰; 蔡启先; 刘明

    2011-01-01

    The EDF schedule algorithm, one of main real-time schedule algorithms of the embedded Linux operating system, can not solve the overload schedule.For this, the paper introduces SLAD algorithm and BACKSLASH algorithm, which have good performance of system load.According to thinking of ISM algorithm, it puts forward a kind of dynamic priority schedule algorithm.According to case of overloads within some time, the algorithm can adjust EDF algorithm and SLAD algorithm neatly, thus improves schedule efficiency of system in usual load and overload cases.Test results for real-time tasks Deadline Miss Ratio(DMR) show its improvement effect.%在嵌入式Linux操作系统的实时调度算法中,EDF调度算法不能解决负载过载问题.为此,引进对系统负载有着良好表现的SLAD算法和BACKSLASH算法.基于ISM算法思路,提出一种动态优先级调度算法.该算法能根据一段时间内负载过载的情况,灵活地调度EDF算法和SLAD算法,从面提高系统在正常负载和过载情况下的调度效率.对实时任务截止期错失率DMR指标的测试结果证明了其改进效果.

  16. Experimental demonstration of bandwidth on demand (BoD) provisioning based on time scheduling in software-defined multi-domain optical networks

    Science.gov (United States)

    Zhao, Yongli; Li, Yajie; Wang, Xinbo; Chen, Bowen; Zhang, Jie

    2016-09-01

    A hierarchical software-defined networking (SDN) control architecture is designed for multi-domain optical networks with the Open Daylight (ODL) controller. The OpenFlow-based Control Virtual Network Interface (CVNI) protocol is deployed between the network orchestrator and the domain controllers. Then, a dynamic bandwidth on demand (BoD) provisioning solution is proposed based on time scheduling in software-defined multi-domain optical networks (SD-MDON). Shared Risk Link Groups (SRLG)-disjoint routing schemes are adopted to separate each tenant for reliability. The SD-MDON testbed is built based on the proposed hierarchical control architecture. Then the proposed time scheduling-based BoD (Ts-BoD) solution is experimentally demonstrated on the testbed. The performance of the Ts-BoD solution is evaluated with respect to blocking probability, resource utilization, and lightpath setup latency.

  17. Optimal charging scheduling for large-scale EV (electric vehicle) deployment based on the interaction of the smart-grid and intelligent-transport systems

    International Nuclear Information System (INIS)

    Luo, Yugong; Zhu, Tao; Wan, Shuang; Zhang, Shuwei; Li, Keqiang

    2016-01-01

    The widespread use of electric vehicles (EVs) is becoming an imminent trend. Research has been done on the scheduling of EVs from the perspective of the charging characteristic, improvement in the safety and economy of the power grid, or the traffic jams in the transport system caused by a large number of EVs driven to charging stations. There is a lack of systematic studies considering EVs, the power grid, and the transport system all together. In this paper, a novel optimal charging scheduling strategy for different types of EVs is proposed based on not only transport system information, such as road length, vehicle velocity and waiting time, but also grid system information, such as load deviation and node voltage. In addition, a charging scheduling simulation platform suitable for large-scale EV deployment is developed based on actual charging scenarios. The simulation results show that the improvements in both the transport system efficiency and the grid system operation can be obtained by using the optimal strategy, such as the node voltage drop is decreased, the power loss is reduced, and the load curve is optimized. - Highlights: • A novel optimal charging scheduling strategy is proposed for different electric vehicles (EVs). • A simulation platform suitable for large-scale EV deployment is established. • The traffic congestion near the charging and battery-switch stations is relieved. • The safety and economy problems of the distribution network are solved. • The peak-to-valley load of the distribution system is reduced.

  18. [Bases and methods of suturing].

    Science.gov (United States)

    Vogt, P M; Altintas, M A; Radtke, C; Meyer-Marcotty, M

    2009-05-01

    If pharmaceutic modulation of scar formation does not improve the quality of the healing process over conventional healing, the surgeon must rely on personal skill and experience. Therefore a profound knowledge of wound healing based on experimental and clinical studies supplemented by postsurgical means of scar management and basic techniques of planning incisions, careful tissue handling, and thorough knowledge of suturing remain the most important ways to avoid abnormal scarring. This review summarizes the current experimental and clinical bases of surgical scar management.

  19. Performance comparison of some evolutionary algorithms on job shop scheduling problems

    Science.gov (United States)

    Mishra, S. K.; Rao, C. S. P.

    2016-09-01

    Job Shop Scheduling as a state space search problem belonging to NP-hard category due to its complexity and combinational explosion of states. Several naturally inspire evolutionary methods have been developed to solve Job Shop Scheduling Problems. In this paper the evolutionary methods namely Particles Swarm Optimization, Artificial Intelligence, Invasive Weed Optimization, Bacterial Foraging Optimization, Music Based Harmony Search Algorithms are applied and find tuned to model and solve Job Shop Scheduling Problems. To compare about 250 Bench Mark instances have been used to evaluate the performance of these algorithms. The capabilities of each these algorithms in solving Job Shop Scheduling Problems are outlined.

  20. A Dynamic Resource Scheduling Method Based on Fuzzy Control Theory in Cloud Environment

    OpenAIRE

    Chen, Zhijia; Zhu, Yuanchang; Di, Yanqiang; Feng, Shaochong

    2015-01-01

    The resources in cloud environment have features such as large-scale, diversity, and heterogeneity. Moreover, the user requirements for cloud computing resources are commonly characterized by uncertainty and imprecision. Hereby, to improve the quality of cloud computing service, not merely should the traditional standards such as cost and bandwidth be satisfied, but also particular emphasis should be laid on some extended standards such as system friendliness. This paper proposes a dynamic re...

  1. Based on Penalty Function Method

    Directory of Open Access Journals (Sweden)

    Ishaq Baba

    2015-01-01

    Full Text Available The dual response surface for simultaneously optimizing the mean and variance models as separate functions suffers some deficiencies in handling the tradeoffs between bias and variance components of mean squared error (MSE. In this paper, the accuracy of the predicted response is given a serious attention in the determination of the optimum setting conditions. We consider four different objective functions for the dual response surface optimization approach. The essence of the proposed method is to reduce the influence of variance of the predicted response by minimizing the variability relative to the quality characteristics of interest and at the same time achieving the specific target output. The basic idea is to convert the constraint optimization function into an unconstraint problem by adding the constraint to the original objective function. Numerical examples and simulations study are carried out to compare performance of the proposed method with some existing procedures. Numerical results show that the performance of the proposed method is encouraging and has exhibited clear improvement over the existing approaches.

  2. COMPANY VALUATION METHODS BASED ON PATRIMONY

    Directory of Open Access Journals (Sweden)

    SUCIU GHEORGHE

    2013-02-01

    Full Text Available The methods used for the company valuation can be divided into 3 main groups: methods based on patrimony,methods based on financial performance, methods based both on patrimony and on performance. The companyvaluation methods based on patrimony are implemented taking into account the balance sheet or the financialstatement. The financial statement refers to that type of balance in which the assets are arranged according to liquidity,and the liabilities according to their financial maturity date. The patrimonial methods are based on the principle thatthe value of the company equals that of the patrimony it owns. From a legal point of view, the patrimony refers to allthe rights and obligations of a company. The valuation of companies based on their financial performance can be donein 3 ways: the return value, the yield value, the present value of the cash flows. The mixed methods depend both onpatrimony and on financial performance or can make use of other methods.

  3. Integration of Building Information Modeling and Critical Path Method Schedules to Simulate the Impact of Temperature and Humidity at the Project Level

    Directory of Open Access Journals (Sweden)

    Yongwei Shan

    2014-07-01

    Full Text Available Steel construction activities are often undertaken in an environment with limited climate control. Both hot and cold temperatures can physically and psychologically affect construction workers, thus decreasing their productivity. Temperature and humidity are two factors that constantly exert forces on workers and influence their performance and efficiency. Previous studies have established a relationship between labor productivity and temperature and humidity. This research is built on the existing body of knowledge and develops a framework of integrating building information modeling (BIM with a lower level critical path method (CPM schedule to simulate the overall impact of temperature and humidity on a healthcare facility’s structural steel installation project in terms of total man hours required to build the project. This research effort utilized historical weather data of four cities across the U.S., with each city having workable seasons year-round and conducted a baseline assessment to test if various project starting dates and locations could significantly impact the project’s schedule performance. It was found that both varied project start dates and locations can significantly contribute to the difference in the man hours required to build the model project and that the project start date and location can have an interaction effect. This study contributes to the overall body of knowledge by providing a framework that can help practitioners better understand the overall impact of a productivity influencing factor at a project level, in order to facilitate better decision making.

  4. Optimisation-Based Solution Methods for Set Partitioning Models

    DEFF Research Database (Denmark)

    Rasmussen, Matias Sevel

    The scheduling of crew, i.e. the construction of work schedules for crew members, is often not a trivial task, but a complex puzzle. The task is complicated by rules, restrictions, and preferences. Therefore, manual solutions as well as solutions from standard software packages are not always su......_cient with respect to solution quality and solution time. Enhancement of the overall solution quality as well as the solution time can be of vital importance to many organisations. The _elds of operations research and mathematical optimisation deal with mathematical modelling of di_cult scheduling problems (among...... other topics). The _elds also deal with the development of sophisticated solution methods for these mathematical models. This thesis describes the set partitioning model which has been widely used for modelling crew scheduling problems. Integer properties for the set partitioning model are shown...

  5. Planning and Scheduling for Fleets of Earth Observing Satellites

    Science.gov (United States)

    Frank, Jeremy; Jonsson, Ari; Morris, Robert; Smith, David E.; Norvig, Peter (Technical Monitor)

    2001-01-01

    We address the problem of scheduling observations for a collection of earth observing satellites. This scheduling task is a difficult optimization problem, potentially involving many satellites, hundreds of requests, constraints on when and how to service each request, and resources such as instruments, recording devices, transmitters, and ground stations. High-fidelity models are required to ensure the validity of schedules; at the same time, the size and complexity of the problem makes it unlikely that systematic optimization search methods will be able to solve them in a reasonable time. This paper presents a constraint-based approach to solving the Earth Observing Satellites (EOS) scheduling problem, and proposes a stochastic heuristic search method for solving it.

  6. Pruning-Based, Energy-Optimal, Deterministic I/O Device Scheduling for Hard Real-Time Systems

    Science.gov (United States)

    2005-02-01

    However, DPM via I/O device scheduling for hard real - time systems has received relatively little attention. In this paper,we present an offline I/O...polynomial time. We present experimental results to show that EDS and MDO reduce the energy consumption of I/O devices significantly for hard real - time systems .

  7. Adaptive Gain Scheduled Semiactive Vibration Control Using a Neural Network

    Directory of Open Access Journals (Sweden)

    Kazuhiko Hiramoto

    2018-01-01

    Full Text Available We propose an adaptive gain scheduled semiactive control method using an artificial neural network for structural systems subject to earthquake disturbance. In order to design a semiactive control system with high control performance against earthquakes with different time and/or frequency properties, multiple semiactive control laws with high performance for each of multiple earthquake disturbances are scheduled with an adaptive manner. Each semiactive control law to be scheduled is designed based on the output emulation approach that has been proposed by the authors. As the adaptive gain scheduling mechanism, we introduce an artificial neural network (ANN. Input signals of the ANN are the measured earthquake disturbance itself, for example, the acceleration, velocity, and displacement. The output of the ANN is the parameter for the scheduling of multiple semiactive control laws each of which has been optimized for a single disturbance. Parameters such as weight and bias in the ANN are optimized by the genetic algorithm (GA. The proposed design method is applied to semiactive control design of a base-isolated building with a semiactive damper. With simulation study, the proposed adaptive gain scheduling method realizes control performance exceeding single semiactive control optimizing the average of the control performance subject to various earthquake disturbances.

  8. The effect of alternative work schedules (AWS) on performance during acquisition based testing at the U.S. Army Aberdeen Test Center

    OpenAIRE

    Thomas, Alicia J.

    2014-01-01

    Approved for public release; distribution is unlimited This project analyzed the effects of an alternate work schedule (AWS) on the performance of acquisition based testing conducted at the U.S. Army Aberdeen Test Center (ATC), a subordinate test center to the U.S. Army Test and Evaluation Command. The literature review uncovered how an AWS improved employee work and life balance and performance at three separate external companies. Other potential AWS success factors such as employee abse...

  9. 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.

  10. Application of genetic algorithms to the maintenance scheduling optimization in a nuclear system basing on reliability; Aplicacao de algoritmos geneticos na otimizacao da politica de manutencoes preventivas de um sistema nuclear centrada em confiabilidade

    Energy Technology Data Exchange (ETDEWEB)

    Lapa, Celso M. Franklin; Pereira, Claudio M.N.A.; Mol, Antonio C. de Abreu [Instituto de Engenharia Nuclear (IEN), Rio de Janeiro, RJ (Brazil)

    1999-07-01

    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)

  11. Development of a hybrid genetic algorithm based decision support system for vehicle routing and scheduling in supply chain logistics managment

    OpenAIRE

    Khanian, Seyed Mohammad Shafi

    2007-01-01

    Vehicle Routing and Scheduling (VRS) constitute an important part of logistics management. Given the fact that the worldwide cost on physical distribution is evermore increasing, the global competition and the complex nature of logistics problems, one area, which determines the efficiency of all others, is the VRS activities. The application of Decision Support Systems (DSS) to assist logistics management with an efficient VRS could be of great benefit. Although the benefits of DSS in VRS are...

  12. Simplifying Multiproject Scheduling Problem Based on Design Structure Matrix and Its Solution by an Improved aiNet Algorithm

    Directory of Open Access Journals (Sweden)

    Chunhua Ju

    2012-01-01

    Full Text Available Managing multiple project is a complex task involving the unrelenting pressures of time and cost. Many studies have proposed various tools and techniques for single-project scheduling; however, the literature further considering multimode or multiproject issues occurring in the real world is rather scarce. In this paper, design structure matrix (DSM and an improved artificial immune network algorithm (aiNet are developed to solve a multi-mode resource-constrained scheduling problem. Firstly, the DSM is used to simplify the mathematic model of multi-project scheduling problem. Subsequently, aiNet algorithm comprised of clonal selection, negative selection, and network suppression is adopted to realize the local searching and global searching, which will assure that it has a powerful searching ability and also avoids the possible combinatorial explosion. Finally, the approach is tested on a set of randomly cases generated from ProGen. The computational results validate the effectiveness of the proposed algorithm comparing with other famous metaheuristic algorithms such as genetic algorithm (GA, simulated annealing algorithm (SA, and ant colony optimization (ACO.

  13. EP BASED PSO METHOD FOR SOLVING PROFIT BASED MULTI AREA UNIT COMMITMENT PROBLEM

    Directory of Open Access Journals (Sweden)

    K. VENKATESAN

    2015-04-01

    Full Text Available This paper presents a new approach to solve the profit based multi area unit commitment problem (PBMAUCP using an evolutionary programming based particle swarm optimization (EPPSO method. The objective of this paper is to maximize the profit of generation companies (GENCOs with considering system social benefit. The proposed method helps GENCOs to make a decision, how much power and reserve should be sold in markets, and how to schedule generators in order to receive the maximum profit. Joint operation of generation resources can result in significant operational cost savings. Power transfer between the areas through the tie lines depends upon the operating cost of generation at each hour and tie line transfer limits. The tie line transfer limits were considered as a set of constraints during optimization process to ensure the system security and reliability. The overall algorithm can be implemented on an IBM PC, which can process a fairly large system in a reasonable period of time. Case study of four areas with different load pattern each containing 7 units (NTPS and 26 units connected via tie lines have been taken for analysis. Numerical results showed comparing the profit of evolutionary programming-based particle swarm optimization method (EPPSO with conventional dynamic programming (DP, evolutionary programming (EP, and particle swarm optimization (PSO method. Experimental results shows that the application of this evolutionary programming based particle swarm optimization method have the potential to solve profit based multi area unit commitment problem with lesser computation time.

  14. Cure Schedule for Stycast 2651/Catalyst 9.

    Energy Technology Data Exchange (ETDEWEB)

    Kropka, Jamie Michael [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); McCoy, John D. [New Mexico Inst. of Mining and Technology, Socorro, NM (United States)

    2017-11-01

    The Emerson & Cuming technical data sheet (TDS) for Stycast 2651/Catalyst 9 lists three alternate cure schedules for the material, each of which would result in a different state of reaction and different material properties. Here, a cure schedule that attains full reaction of the material is defined. The use of this cure schedule will eliminate variance in material properties due to changes in the cure state of the material, and the cure schedule will serve as the method to make material prior to characterizing properties. The following recommendation uses one of the schedules within the TDS and adds a “post cure” to obtain full reaction.

  15. 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.

  16. Modeling of Agile Intelligent Manufacturing-oriented Production Scheduling System

    Institute of Scientific and Technical Information of China (English)

    Zhong-Qi Sheng; Chang-Ping Tang; Ci-Xing Lv

    2010-01-01

    Agile intelligent manufacturing is one of the new manufacturing paradigms that adapt to the fierce globalizing market competition and meet the survival needs of the enterprises, in which the management and control of the production system have surpassed the scope of individual enterprise and embodied some new features including complexity, dynamicity, distributivity, and compatibility. The agile intelligent manufacturing paradigm calls for a production scheduling system that can support the cooperation among various production sectors, the distribution of various resources to achieve rational organization, scheduling and management of production activities. This paper uses multi-agents technology to build an agile intelligent manufacturing-oriented production scheduling system. Using the hybrid modeling method, the resources and functions of production system are encapsulated, and the agent-based production system model is established. A production scheduling-oriented multi-agents architecture is constructed and a multi-agents reference model is given in this paper.

  17. An Improved Recovery Algorithm for Decayed AES Key Schedule Images

    Science.gov (United States)

    Tsow, Alex

    A practical algorithm that recovers AES key schedules from decayed memory images is presented. Halderman et al. [1] established this recovery capability, dubbed the cold-boot attack, as a serious vulnerability for several widespread software-based encryption packages. Our algorithm recovers AES-128 key schedules tens of millions of times faster than the original proof-of-concept release. In practice, it enables reliable recovery of key schedules at 70% decay, well over twice the decay capacity of previous methods. The algorithm is generalized to AES-256 and is empirically shown to recover 256-bit key schedules that have suffered 65% decay. When solutions are unique, the algorithm efficiently validates this property and outputs the solution for memory images decayed up to 60%.

  18. SIMULTANEOUS SCHEDULING AND OPERATIONAL OPTIMIZATION OF MULTIPRODUCT, CYCLIC CONTINUOUS PLANTS

    Directory of Open Access Journals (Sweden)

    A. Alle

    2002-03-01

    Full Text Available The problems of scheduling and optimization of operational conditions in multistage, multiproduct continuous plants with intermediate storage are simultaneously addressed. An MINLP model, called TSPFLOW, which is based on the TSP formulation for product sequencing, is proposed to schedule the operation of such plants. TSPFLOW yields a one-order-of-magnitude CPU time reduction as well as the solution of instances larger than those formerly reported (Pinto and Grossmann, 1994. Secondly, processing rates and yields are introduced as additional optimization variables in order to state the simultaneous problem of scheduling with operational optimization. Results show that trade-offs are very complex and that the development of a straightforward (rule of thumb method to optimally schedule the operation is less effective than the proposed approach.

  19. SIMULTANEOUS SCHEDULING AND OPERATIONAL OPTIMIZATION OF MULTIPRODUCT, CYCLIC CONTINUOUS PLANTS

    Directory of Open Access Journals (Sweden)

    Alle A.

    2002-01-01

    Full Text Available The problems of scheduling and optimization of operational conditions in multistage, multiproduct continuous plants with intermediate storage are simultaneously addressed. An MINLP model, called TSPFLOW, which is based on the TSP formulation for product sequencing, is proposed to schedule the operation of such plants. TSPFLOW yields a one-order-of-magnitude CPU time reduction as well as the solution of instances larger than those formerly reported (Pinto and Grossmann, 1994. Secondly, processing rates and yields are introduced as additional optimization variables in order to state the simultaneous problem of scheduling with operational optimization. Results show that trade-offs are very complex and that the development of a straightforward (rule of thumb method to optimally schedule the operation is less effective than the proposed approach.

  20. Scheduling Algorithms for Maximizing Throughput with Zero-Forcing Beamforming in a MIMO Wireless System

    Science.gov (United States)

    Foronda, Augusto; Ohta, Chikara; Tamaki, Hisashi

    Dirty paper coding (DPC) is a strategy to achieve the region capacity of multiple input multiple output (MIMO) downlink channels and a DPC scheduler is throughput optimal if users are selected according to their queue states and current rates. However, DPC is difficult to implement in practical systems. One solution, zero-forcing beamforming (ZFBF) strategy has been proposed to achieve the same asymptotic sum rate capacity as that of DPC with an exhaustive search over the entire user set. Some suboptimal user group selection schedulers with reduced complexity based on ZFBF strategy (ZFBF-SUS) and proportional fair (PF) scheduling algorithm (PF-ZFBF) have also been proposed to enhance the throughput and fairness among the users, respectively. However, they are not throughput optimal, fairness and throughput decrease if each user queue length is different due to different users channel quality. Therefore, we propose two different scheduling algorithms: a throughput optimal scheduling algorithm (ZFBF-TO) and a reduced complexity scheduling algorithm (ZFBF-RC). Both are based on ZFBF strategy and, at every time slot, the scheduling algorithms have to select some users based on user channel quality, user queue length and orthogonality among users. Moreover, the proposed algorithms have to produce the rate allocation and power allocation for the selected users based on a modified water filling method. We analyze the schedulers complexity and numerical results show that ZFBF-RC provides throughput and fairness improvements compared to the ZFBF-SUS and PF-ZFBF scheduling algorithms.

  1. Cost-efficient scheduling of FAST observations

    Science.gov (United States)

    Luo, Qi; Zhao, Laiping; Yu, Ce; Xiao, Jian; Sun, Jizhou; Zhu, Ming; Zhong, Yi

    2018-03-01

    A cost-efficient schedule for the Five-hundred-meter Aperture Spherical radio Telescope (FAST) requires to maximize the number of observable proposals and the overall scientific priority, and minimize the overall slew-cost generated by telescope shifting, while taking into account the constraints including the astronomical objects visibility, user-defined observable times, avoiding Radio Frequency Interference (RFI). In this contribution, first we solve the problem of maximizing the number of observable proposals and scientific priority by modeling it as a Minimum Cost Maximum Flow (MCMF) problem. The optimal schedule can be found by any MCMF solution algorithm. Then, for minimizing the slew-cost of the generated schedule, we devise a maximally-matchable edges detection-based method to reduce the problem size, and propose a backtracking algorithm to find the perfect matching with minimum slew-cost. Experiments on a real dataset from NASA/IPAC Extragalactic Database (NED) show that, the proposed scheduler can increase the usage of available times with high scientific priority and reduce the slew-cost significantly in a very short time.

  2. Adaptation of Shift Sequence Based Method for High Number in Shifts Rostering Problem for Health Care Workers

    Directory of Open Access Journals (Sweden)

    Mindaugas Liogys

    2013-08-01

    Full Text Available Purpose—is to investigate a shift sequence-based approach efficiency then problem consisting of a high number of shifts.Research objectives:• Solve health care workers rostering problem using a shift sequence based method.• Measure its efficiency then number of shifts increases.Design/methodology/approach—Usually rostering problems are highly constrained. Constraints are classified to soft and hard constraints. Soft and hard constraints of the problem are additionally classified to: sequence constraints, schedule constraints and roster constraints. Sequence constraints are considered when constructing shift sequences. Schedule constraints are considered when constructing a schedule. Roster constraints are applied, then constructing overall solution, i.e. combining all schedules.Shift sequence based approach consists of two stages:• Shift sequences construction,• The construction of schedules.In the shift sequences construction stage, the shift sequences are constructed for each set of health care workers of different skill, considering sequence constraints. Shifts sequences are ranked by their penalties for easier retrieval in later stage.In schedules construction stage, schedules for each health care worker are constructed iteratively, using the shift sequences produced in stage 1.Shift sequence based method is an adaptive iterative method where health care workers who received the highest schedule penalties in the last iteration are scheduled first at the current iteration.During the roster construction, and after a schedule has been generated for the current health care worker, an improvement method based on an efficient greedy local search is carried out on the partial roster. It simply swaps any pair of shifts between two health care workers in the (partial roster, as long as the swaps satisfy hard constraints and decrease the roster penalty.Findings—Using shift sequence method for solving health care workers rostering problem

  3. Adaptation of Shift Sequence Based Method for High Number in Shifts Rostering Problem for Health Care Workers

    Directory of Open Access Journals (Sweden)

    Mindaugas Liogys

    2011-08-01

    Full Text Available Purpose—is to investigate a shift sequence-based approach efficiency then problem consisting of a high number of shifts. Research objectives:• Solve health care workers rostering problem using a shift sequence based method.• Measure its efficiency then number of shifts increases. Design/methodology/approach—Usually rostering problems are highly constrained.Constraints are classified to soft and hard constraints. Soft and hard constraints of the problem are additionally classified to: sequence constraints, schedule constraints and roster constraints. Sequence constraints are considered when constructing shift sequences. Schedule constraints are considered when constructing a schedule. Roster constraints are applied, then constructing overall solution, i.e. combining all schedules.Shift sequence based approach consists of two stages:• Shift sequences construction,• The construction of schedules.In the shift sequences construction stage, the shift sequences are constructed for each set of health care workers of different skill, considering sequence constraints. Shifts sequences are ranked by their penalties for easier retrieval in later stage.In schedules construction stage, schedules for each health care worker are constructed iteratively, using the shift sequences produced in stage 1. Shift sequence based method is an adaptive iterative method where health care workers who received the highest schedule penalties in the last iteration are scheduled first at the current iteration. During the roster construction, and after a schedule has been generated for the current health care worker, an improvement method based on an efficient greedy local search is carried out on the partial roster. It simply swaps any pair of shifts between two health care workers in the (partial roster, as long as the swaps satisfy hard constraints and decrease the roster penalty.Findings—Using shift sequence method for solving health care workers rostering

  4. Planning and Scheduling of Airline Operations

    Directory of Open Access Journals (Sweden)

    İlkay ORHAN

    2010-02-01

    Full Text Available The Turkish Civil Aviation sector has grown at a rate of 53 % between the years 2002-2008 owing to countrywide economical developments and some removed restrictions in the aviation field. Successful international companies in the sector use advanced computer-supported solution methods for their planning and scheduling problems. These methods have been providing significant competitive advantages to those companies. There are four major scheduling and planning problems in the airline sector: flight scheduling, aircraft scheduling, crew scheduling and disruptions management. These aforementioned scheduling and planning problems faced by all airline companies in the airline sector were examined in detail. Studies reveal that companies using the advanced methods might gain significant cost reductions. However, even then, the time required for solving large scale problems may not satisfy the decision quality desired by decision makers. In such cases, using modern decision methods integrated with advanced technologies offer companies an opportunity for significant cost-advantages.

  5. A Method for Modeling the Virtual Instrument Automatic Test System Based on the Petri Net

    Institute of Scientific and Technical Information of China (English)

    MA Min; CHEN Guang-ju

    2005-01-01

    Virtual instrument is playing the important role in automatic test system. This paper introduces a composition of a virtual instrument automatic test system and takes the VXIbus based a test software platform which is developed by CAT lab of the UESTC as an example. Then a method to model this system based on Petri net is proposed. Through this method, we can analyze the test task scheduling to prevent the deadlock or resources conflict. At last, this paper analyzes the feasibility of this method.

  6. 15 CFR 700.14 - Preferential scheduling.

    Science.gov (United States)

    2010-01-01

    ...) BUREAU OF INDUSTRY AND SECURITY, DEPARTMENT OF COMMERCE NATIONAL SECURITY INDUSTRIAL BASE REGULATIONS DEFENSE PRIORITIES AND ALLOCATIONS SYSTEM Industrial Priorities § 700.14 Preferential scheduling. (a) A...

  7. Practical quantum appointment scheduling

    Science.gov (United States)

    Touchette, Dave; Lovitz, Benjamin; Lütkenhaus, Norbert

    2018-04-01

    We propose a protocol based on coherent states and linear optics operations for solving the appointment-scheduling problem. Our main protocol leaks strictly less information about each party's input than the optimal classical protocol, even when considering experimental errors. Along with the ability to generate constant-amplitude coherent states over two modes, this protocol requires the ability to transfer these modes back-and-forth between the two parties multiple times with very low losses. The implementation requirements are thus still challenging. Along the way, we develop tools to study quantum information cost of interactive protocols in the finite regime.

  8. Novel Hybrid Scheduling Technique for Sensor Nodes with Mixed Criticality Tasks.

    Science.gov (United States)

    Micea, Mihai-Victor; Stangaciu, Cristina-Sorina; Stangaciu, Valentin; Curiac, Daniel-Ioan

    2017-06-26

    Sensor networks become increasingly a key technology for complex control applications. Their potential use in safety- and time-critical domains has raised the need for task scheduling mechanisms specially adapted to sensor node specific requirements, often materialized in predictable jitter-less execution of tasks characterized by different criticality levels. This paper offers an efficient scheduling solution, named Hybrid Hard Real-Time Scheduling (H²RTS), which combines a static, clock driven method with a dynamic, event driven scheduling technique, in order to provide high execution predictability, while keeping a high node Central Processing Unit (CPU) utilization factor. From the detailed, integrated schedulability analysis of the H²RTS, a set of sufficiency tests are introduced and demonstrated based on the processor demand and linear upper bound metrics. The performance and correct behavior of the proposed hybrid scheduling technique have been extensively evaluated and validated both on a simulator and on a sensor mote equipped with ARM7 microcontroller.

  9. A System for Automatically Generating Scheduling Heuristics

    Science.gov (United States)

    Morris, Robert

    1996-01-01

    The goal of this research is to improve the performance of automated schedulers by designing and implementing an algorithm by automatically generating heuristics by selecting a schedule. The particular application selected by applying this method solves the problem of scheduling telescope observations, and is called the Associate Principal Astronomer. The input to the APA scheduler is a set of observation requests submitted by one or more astronomers. Each observation request specifies an observation program as well as scheduling constraints and preferences associated with the program. The scheduler employs greedy heuristic search to synthesize a schedule that satisfies all hard constraints of the domain and achieves a good score with respect to soft constraints expressed as an objective function established by an astronomer-user.

  10. 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.

  11. Immunization Schedules for Adults

    Science.gov (United States)

    ... ACIP Vaccination Recommendations Why Immunize? Vaccines: The Basics Immunization Schedule for Adults (19 Years of Age and ... diseases that can be prevented by vaccines . 2018 Immunization Schedule Recommended Vaccinations for Adults by Age and ...

  12. Web Publishing Schedule

    Science.gov (United States)

    Section 207(f)(2) of the E-Gov Act requires federal agencies to develop an inventory and establish a schedule of information to be published on their Web sites, make those schedules available for public comment. To post the schedules on the web site.

  13. Preemptive scheduling with rejection

    NARCIS (Netherlands)

    Hoogeveen, H.; Skutella, M.; Woeginger, Gerhard

    2003-01-01

    We consider the problem of preemptively scheduling a set of n jobs on m (identical, uniformly related, or unrelated) parallel machines. The scheduler may reject a subset of the jobs and thereby incur job-dependent penalties for each rejected job, and he must construct a schedule for the remaining

  14. Preemptive scheduling with rejection

    NARCIS (Netherlands)

    Hoogeveen, J.A.; Skutella, M.; Woeginger, G.J.; Paterson, M.

    2000-01-01

    We consider the problem of preemptively scheduling a set of n jobs on m (identical, uniformly related, or unrelated) parallel machines. The scheduler may reject a subset of the jobs and thereby incur job-dependent penalties for each rejected job, and he must construct a schedule for the remaining

  15. Outage scheduling and implementation

    International Nuclear Information System (INIS)

    Allison, J.E.; Segall, P.; Smith, R.R.

    1986-01-01

    Successful preparation and implementation of an outage schedule and completion of scheduled and emergent work within an identified critical path time frame is a result of careful coordination by Operations, Work Control, Maintenance, Engineering, Planning and Administration and others. At the Fast Flux Test Facility (FFTF) careful planning has been responsible for meeting all scheduled outage critical paths

  16. Scheduling with Time Lags

    NARCIS (Netherlands)

    X. Zhang (Xiandong)

    2010-01-01

    textabstractScheduling is essential when activities need to be allocated to scarce resources over time. Motivated by the problem of scheduling barges along container terminals in the Port of Rotterdam, this thesis designs and analyzes algorithms for various on-line and off-line scheduling problems

  17. A nodal method based on the response-matrix method

    International Nuclear Information System (INIS)

    Cunha Menezes Filho, A. da; Rocamora Junior, F.D.

    1983-02-01

    A nodal approach based on the Response-Matrix method is presented with the purpose of investigating the possibility of mixing two different allocations in the same problem. It is found that the use of allocation of albedo combined with allocation of direct reflection produces good results for homogeneous fast reactor configurations. (Author) [pt

  18. EFFICIENT MULTI-OBJECTIVE EVOLUTIONARY ALGORITHM FOR JOB SHOP SCHEDULING

    Institute of Scientific and Technical Information of China (English)

    Lei Deming; Wu Zhiming

    2005-01-01

    A new representation method is first presented based on priority rules. According to this method, each entry in the chromosome indicates that in the procedure of the Giffler and Thompson (GT) algorithm, the conflict occurring in the corresponding machine is resolved by the corresponding priority rule. Then crowding-measure multi-objective evolutionary algorithm (CMOEA) is designed,in which both archive maintenance and fitness assignment use crowding measure. Finally the comparisons between CMOEA and SPEA in solving 15 scheduling problems demonstrate that CMOEA is suitable to job shop scheduling.

  19. The comparison of predictive scheduling algorithms for different sizes of job shop scheduling problems

    Science.gov (United States)

    Paprocka, I.; Kempa, W. M.; Grabowik, C.; Kalinowski, K.; Krenczyk, D.

    2016-08-01

    In the paper a survey of predictive and reactive scheduling methods is done in order to evaluate how the ability of prediction of reliability characteristics influences over robustness criteria. The most important reliability characteristics are: Mean Time to Failure, Mean Time of Repair. Survey analysis is done for a job shop scheduling problem. The paper answers the question: what method generates robust schedules in the case of a bottleneck failure occurrence before, at the beginning of planned maintenance actions or after planned maintenance actions? Efficiency of predictive schedules is evaluated using criteria: makespan, total tardiness, flow time, idle time. Efficiency of reactive schedules is evaluated using: solution robustness criterion and quality robustness criterion. This paper is the continuation of the research conducted in the paper [1], where the survey of predictive and reactive scheduling methods is done only for small size scheduling problems.

  20. A solution approach based on Benders decomposition for the preventive maintenance scheduling problem of a stochastic large-scale energy system

    DEFF Research Database (Denmark)

    Lusby, Richard Martin; Muller, Laurent Flindt; Petersen, Bjørn

    2013-01-01

    This paper describes a Benders decomposition-based framework for solving the large scale energy management problem that was posed for the ROADEF 2010 challenge. The problem was taken from the power industry and entailed scheduling the outage dates for a set of nuclear power plants, which need...... to be regularly taken down for refueling and maintenance, in such away that the expected cost of meeting the power demand in a number of potential scenarios is minimized. We show that the problem structure naturally lends itself to Benders decomposition; however, not all constraints can be included in the mixed...

  1. An extended Intelligent Water Drops algorithm for workflow scheduling in cloud computing environment

    Directory of Open Access Journals (Sweden)

    Shaymaa Elsherbiny

    2018-03-01

    Full Text Available Cloud computing is emerging as a high performance computing environment with a large scale, heterogeneous collection of autonomous systems and flexible computational architecture. Many resource management methods may enhance the efficiency of the whole cloud computing system. The key part of cloud computing resource management is resource scheduling. Optimized scheduling of tasks on the cloud virtual machines is an NP-hard problem and many algorithms have been presented to solve it. The variations among these schedulers are due to the fact that the scheduling strategies of the schedulers are adapted to the changing environment and the types of tasks. The focus of this paper is on workflows scheduling in cloud computing, which is gaining a lot of attention recently because workflows have emerged as a paradigm to represent complex computing problems. We proposed a novel algorithm extending the natural-based Intelligent Water Drops (IWD algorithm that optimizes the scheduling of workflows on the cloud. The proposed algorithm is implemented and embedded within the workflows simulation toolkit and tested in different simulated cloud environments with different cost models. Our algorithm showed noticeable enhancements over the classical workflow scheduling algorithms. We made a comparison between the proposed IWD-based algorithm with other well-known scheduling algorithms, including MIN-MIN, MAX-MIN, Round Robin, FCFS, and MCT, PSO and C-PSO, where the proposed algorithm presented noticeable enhancements in the performance and cost in most situations.

  2. 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

    -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......Water shortage is the main limiting factor for agricultural productivity in many countries and improving water use efficiency in agriculture has been the focus of numerous studies. The usual approach to limit water consumption in agriculture is to apply water quotas and in such a situation farmers...... 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...

  3. Color image definition evaluation method based on deep learning method

    Science.gov (United States)

    Liu, Di; Li, YingChun

    2018-01-01

    In order to evaluate different blurring levels of color image and improve the method of image definition evaluation, this paper proposed a method based on the depth learning framework and BP neural network classification model, and presents a non-reference color image clarity evaluation method. Firstly, using VGG16 net as the feature extractor to extract 4,096 dimensions features of the images, then the extracted features and labeled images are employed in BP neural network to train. And finally achieve the color image definition evaluation. The method in this paper are experimented by using images from the CSIQ database. The images are blurred at different levels. There are 4,000 images after the processing. Dividing the 4,000 images into three categories, each category represents a blur level. 300 out of 400 high-dimensional features are trained in VGG16 net and BP neural network, and the rest of 100 samples are tested. The experimental results show that the method can take full advantage of the learning and characterization capability of deep learning. Referring to the current shortcomings of the major existing image clarity evaluation methods, which manually design and extract features. The method in this paper can extract the images features automatically, and has got excellent image quality classification accuracy for the test data set. The accuracy rate is 96%. Moreover, the predicted quality levels of original color images are similar to the perception of the human visual system.

  4. A Pareto-Based Adaptive Variable Neighborhood Search for Biobjective Hybrid Flow Shop Scheduling Problem with Sequence-Dependent Setup Time

    Directory of Open Access Journals (Sweden)

    Huixin Tian

    2016-01-01

    Full Text Available Different from most researches focused on the single objective hybrid flowshop scheduling (HFS problem, this paper investigates a biobjective HFS problem with sequence dependent setup time. The two objectives are the minimization of total weighted tardiness and the total setup time. To efficiently solve this problem, a Pareto-based adaptive biobjective variable neighborhood search (PABOVNS is developed. In the proposed PABOVNS, a solution is denoted as a sequence of all jobs and a decoding procedure is presented to obtain the corresponding complete schedule. In addition, the proposed PABOVNS has three major features that can guarantee a good balance of exploration and exploitation. First, an adaptive selection strategy of neighborhoods is proposed to automatically select the most promising neighborhood instead of the sequential selection strategy of canonical VNS. Second, a two phase multiobjective local search based on neighborhood search and path relinking is designed for each selected neighborhood. Third, an external archive with diversity maintenance is adopted to store the nondominated solutions and at the same time provide initial solutions for the local search. Computational results based on randomly generated instances show that the PABOVNS is efficient and even superior to some other powerful multiobjective algorithms in the literature.

  5. History based batch method preserving tally means

    International Nuclear Information System (INIS)

    Shim, Hyung Jin; Choi, Sung Hoon

    2012-01-01

    In the Monte Carlo (MC) eigenvalue calculations, the sample variance of a tally mean calculated from its cycle-wise estimates is biased because of the inter-cycle correlations of the fission source distribution (FSD). Recently, we proposed a new real variance estimation method named the history-based batch method in which a MC run is treated as multiple runs with small number of histories per cycle to generate independent tally estimates. In this paper, the history-based batch method based on the weight correction is presented to preserve the tally mean from the original MC run. The effectiveness of the new method is examined for the weakly coupled fissile array problem as a function of the dominance ratio and the batch size, in comparison with other schemes available

  6. Model-Based Method for Sensor Validation

    Science.gov (United States)

    Vatan, Farrokh

    2012-01-01

    Fault detection, diagnosis, and prognosis are essential tasks in the operation of autonomous spacecraft, instruments, and in situ platforms. One of NASA s key mission requirements is robust state estimation. Sensing, using a wide range of sensors and sensor fusion approaches, plays a central role in robust state estimation, and there is a need to diagnose sensor failure as well as component failure. Sensor validation can be considered to be part of the larger effort of improving reliability and safety. The standard methods for solving the sensor validation problem are based on probabilistic analysis of the system, from which the method based on Bayesian networks is most popular. Therefore, these methods can only predict the most probable faulty sensors, which are subject to the initial probabilities defined for the failures. The method developed in this work is based on a model-based approach and provides the faulty sensors (if any), which can be logically inferred from the model of the system and the sensor readings (observations). The method is also more suitable for the systems when it is hard, or even impossible, to find the probability functions of the system. The method starts by a new mathematical description of the problem and develops a very efficient and systematic algorithm for its solution. The method builds on the concepts of analytical redundant relations (ARRs).

  7. On Coding of Scheduling Information in OFDM

    OpenAIRE

    Gunnarsson, Fredrik; Moosavi, Reza; Eriksson, Jonas; Larsson, Erik G.; Wiberg, Niklas; Frenger, Pål

    2009-01-01

    Control signaling strategies for scheduling information in cellular OFDM systems are studied. A single-cell multiuser system model is formulated that provides system capacity estimates accounting for the signaling overhead. Different scheduling granularities are considered, including the one used in the specifications for the 3G Long Term Evolution (LTE). A greedy scheduling method is assumed, where each resource is assigned to the user for which it can support the highest number of bits. The...

  8. Design Principles and Algorithms for Air Traffic Arrival Scheduling

    Science.gov (United States)

    Erzberger, Heinz; Itoh, Eri

    2014-01-01

    This report presents design principles and algorithms for building a real-time scheduler of arrival aircraft based on a first-come-first-served (FCFS) scheduling protocol. The algorithms provide the conceptual and computational foundation for the Traffic Management Advisor (TMA) of the Center/terminal radar approach control facilities (TRACON) automation system, which comprises a set of decision support tools for managing arrival traffic at major airports in the United States. The primary objective of the scheduler is to assign arrival aircraft to a favorable landing runway and schedule them to land at times that minimize delays. A further objective of the scheduler is to allocate delays between high-altitude airspace far away from the airport and low-altitude airspace near the airport. A method of delay allocation is described that minimizes the average operating cost in the presence of errors in controlling aircraft to a specified landing time. This report is a revision of an earlier paper first presented as part of an Advisory Group for Aerospace Research and Development (AGARD) lecture series in September 1995. The authors, during vigorous discussions over the details of this paper, felt it was important to the air-trafficmanagement (ATM) community to revise and extend the original 1995 paper, providing more detail and clarity and thereby allowing future researchers to understand this foundational work as the basis for the TMA's scheduling algorithms.

  9. Schedule and staffing of a nuclear power project

    International Nuclear Information System (INIS)

    Polliart, A.J.; Csik, B.

    1977-01-01

    Establishment of construction schedule: a) preliminary construction schedule; b) PERT (Program Evaluation Review Techniques) analytical method; c) identify key milestone target dates; d) inter-action by participants and contribution to support revised construction schedule. - Construction schedule control: a) ability to update and modify construction schedule; b) alternate plans to circumvent restraints (problems); c) critical path activity-controls; d) continuous review and report system. - Updating construction site reports to include: 1) progress, 2) accomplishments, 3) potential problems and alternate plans; b) progress reports on related support services; c) total assessment of participating groups on schedule; d) information required by management for decisions. - Typical causes for delays in project schedule. (orig.) [de

  10. Spectrum estimation method based on marginal spectrum

    International Nuclear Information System (INIS)

    Cai Jianhua; Hu Weiwen; Wang Xianchun

    2011-01-01

    FFT method can not meet the basic requirements of power spectrum for non-stationary signal and short signal. A new spectrum estimation method based on marginal spectrum from Hilbert-Huang transform (HHT) was proposed. The procession of obtaining marginal spectrum in HHT method was given and the linear property of marginal spectrum was demonstrated. Compared with the FFT method, the physical meaning and the frequency resolution of marginal spectrum were further analyzed. Then the Hilbert spectrum estimation algorithm was discussed in detail, and the simulation results were given at last. The theory and simulation shows that under the condition of short data signal and non-stationary signal, the frequency resolution and estimation precision of HHT method is better than that of FFT method. (authors)

  11. Environmental surveillance master sampling schedule

    International Nuclear Information System (INIS)

    Bisping, L.E.

    1997-01-01

    Environmental surveillance of the Hanford Site and surrounding areas is conducted by the Pacific Northwest National Laboratory (PNNL)(a) for the US Department of Energy (DOE). This document contains the planned 1997 schedules for routine collection of samples for the Surface Environmental Surveillance Project (SESP) and Drinking Water Monitoring Project. In addition, Section 3.0, Biota, also reflects a rotating collection schedule identifying the year a specific sample is scheduled for collection. The purpose of these monitoring projects is to evaluate levels of radioactive and nonradioactive pollutants in the Hanford environs, as required in DOE Order 5400.1, General Environmental Protection Program, and DOE Order 5400.5, Radiation Protection of the Public and the Environment. The sampling methods will be the same as those described in the Environmental Monitoring Plan, US Department of Energy, Richland Operations Office, DOE/RL91-50, Rev. 1, US Department of Energy, Richland, Washington

  12. Interchange Recognition Method Based on CNN

    Directory of Open Access Journals (Sweden)

    HE Haiwei

    2018-03-01

    Full Text Available The identification and classification of interchange structures in OSM data can provide important information for the construction of multi-scale model, navigation and location services, congestion analysis, etc. The traditional method of interchange identification relies on the low-level characteristics of artificial design, and cannot distinguish the complex interchange structure with interference section effectively. In this paper, a new method based on convolutional neural network for identification of the interchange is proposed. The method combines vector data with raster image, and uses neural network to learn the fuzzy characteristics of the interchange, and classifies the complex interchange structure in OSM. Experiments show that this method has strong anti-interference, and has achieved good results in the classification of complex interchange shape, and there is room for further improvement with the expansion of the case base and the optimization of neural network model.

  13. Improved Low Power FPGA Binding of Datapaths from Data Flow Graphs with NSGA II -based Schedule Selection

    Directory of Open Access Journals (Sweden)

    BHUVANESWARI, M. C.

    2013-11-01

    Full Text Available FPGAs are increasingly being used to implement data path intensive algorithms for signal processing and image processing applications. In High Level Synthesis of Data Flow Graphs targeted at FPGAs, the effect of interconnect resources such as multiplexers must be considered since they contribute significantly to the area and switching power. We propose a binding framework for behavioral synthesis of Data Flow Graphs (DFGs onto FPGA targets with power reduction as the main criterion. The technique uses a multi-objective GA, NSGA II for design space exploration to identify schedules that have the potential to yield low-power bindings from a population of non-dominated solutions. A greedy constructive binding technique reported in the literature is adapted for interconnect minimization. The binding is further subjected to a perturbation process by altering the register and multiplexer assignments. Results obtained on standard DFG benchmarks indicate that our technique yields better power aware bindings than the constructive binding approach with little or no area overhead.

  14. Hypothetical operation model for the multi-bed system of the Tritium plant based on the scheduling approach

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Jae-Uk, E-mail: eslee@dongguk.edu [Department of Chemical Engineering, Pohang University of Science and Technology, San 31, Hyoja-Dong, Pohang 790-784 (Korea, Republic of); Chang, Min Ho; Yun, Sei-Hun [National Fusion Research Institute, 169-148-gil Kwahak-ro, Yusong-gu, Daejon 34133 (Korea, Republic of); Lee, Euy Soo [Department of Chemical & Biochemical Engineering, Dongguk University, Seoul 100-715 (Korea, Republic of); Lee, In-Beum [Department of Chemical Engineering and Graduate School of Engineering Mastership, Pohang University of Science and Technology, San 31, Hyoja-Dong, Pohang 790-784 (Korea, Republic of); Lee, Kun-Hong [Department of Chemical Engineering, Pohang University of Science and Technology, San 31, Hyoja-Dong, Pohang 790-784 (Korea, Republic of)

    2016-11-01

    Highlights: • We introduce a mathematical model for the multi-bed storage system in the tritium plant. • We obtain details of operation by solving the model. • The model assesses diverse operation scenarios with respect to risk. - Abstract: In this paper, we describe our hypothetical operation model (HOM) for the multi-bed system of the storage and delivery system (SDS) of the ITER tritium plant. The multi-bed system consists of multiple getter beds (i.e., for batch operation) and buffer vessels (i.e., for continuous operation). Our newly developed HOM is formulated as a mixed-integer linear programming (MILP) model and has been extensively investigated to optimize chemical and petrochemical production planning and scheduling. Our model determines the timing, duration, and size of tasks corresponding to each set of equipment. Further, inventory levels for each set of equipment are calculated. Our proposed model considers the operation of one cycle of one set of getter beds and is implemented and assessed as a case study problem.

  15. Recommendation advertising method based on behavior retargeting

    Science.gov (United States)

    Zhao, Yao; YIN, Xin-Chun; CHEN, Zhi-Min

    2011-10-01

    Online advertising has become an important business in e-commerce. Ad recommended algorithms are the most critical part in recommendation systems. We propose a recommendation advertising method based on behavior retargeting which can avoid leakage click of advertising due to objective reasons and can observe the changes of the user's interest in time. Experiments show that our new method can have a significant effect and can be further to apply to online system.

  16. Personnel Selection Based on Fuzzy Methods

    Directory of Open Access Journals (Sweden)

    Lourdes Cañós

    2011-03-01

    Full Text Available The decisions of managers regarding the selection of staff strongly determine the success of the company. A correct choice of employees is a source of competitive advantage. We propose a fuzzy method for staff selection, based on competence management and the comparison with the valuation that the company considers the best in each competence (ideal candidate. Our method is based on the Hamming distance and a Matching Level Index. The algorithms, implemented in the software StaffDesigner, allow us to rank the candidates, even when the competences of the ideal candidate have been evaluated only in part. Our approach is applied in a numerical example.

  17. Scheduling for decommissioning projects

    International Nuclear Information System (INIS)

    Podmajersky, O.E.

    1987-01-01

    This paper describes the Project Scheduling system being employed by the Decommissioning Operations Contractor at the Shippingport Station Decommissioning Project (SSDP). Results from the planning system show that the project continues to achieve its cost and schedule goals. An integrated cost and schedule control system (C/SCS) which uses the concept of earned value for measurement of performance was instituted in accordance with DOE orders. The schedule and cost variances generated by the C/SCS system are used to confirm management's assessment of project status. This paper describes the types of schedules and tools used on the SSDP project to plan and monitor the work, and identifies factors that are unique to a decommissioning project that make scheduling critical to the achievement of the project's goals. 1 fig

  18. Program reference schedule baseline

    International Nuclear Information System (INIS)

    1986-07-01

    This Program Reference Schedule Baseline (PRSB) provides the baseline Program-level milestones and associated schedules for the Civilian Radioactive Waste Management Program. It integrates all Program-level schedule-related activities. This schedule baseline will be used by the Director, Office of Civilian Radioactive Waste Management (OCRWM), and his staff to monitor compliance with Program objectives. Chapter 1 includes brief discussions concerning the relationship of the PRSB to the Program Reference Cost Baseline (PRCB), the Mission Plan, the Project Decision Schedule, the Total System Life Cycle Cost report, the Program Management Information System report, the Program Milestone Review, annual budget preparation, and system element plans. Chapter 2 includes the identification of all Level 0, or Program-level, milestones, while Chapter 3 presents and discusses the critical path schedules that correspond to those Level 0 milestones

  19. GPScheDVS: A New Paradigm of the Autonomous CPU Speed Control for Commodity-OS-based General-Purpose Mobile Computers with a DVS-friendly Task Scheduling

    OpenAIRE

    Kim, Sookyoung

    2008-01-01

    This dissertation studies the problem of increasing battery life-time and reducing CPU heat dissipation without degrading system performance in commodity-OS-based general-purpose (GP) mobile computers using the dynamic voltage scaling (DVS) function of modern CPUs. The dissertation especially focuses on the impact of task scheduling on the effectiveness of DVS in achieving this goal. The task scheduling mechanism used in most contemporary general-purpose operating systems (GPOS) prioritizes t...

  20. Rostering and Task Scheduling

    DEFF Research Database (Denmark)

    Dohn, Anders Høeg

    . The rostering process is non-trivial and especially when service is required around the clock, rostering may involve considerable effort from a designated planner. Therefore, in order to minimize costs and overstaffing, to maximize the utilization of available staff, and to ensure a high level of satisfaction...... as possible to the available staff, while respecting various requirements and rules and while including possible transportation time between tasks. This thesis presents a number of industrial applications in rostering and task scheduling. The applications exist within various contexts in health care....... 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...

  1. Approximating Preemptive Stochastic Scheduling

    OpenAIRE

    Megow Nicole; Vredeveld Tjark

    2009-01-01

    We present constant approximative policies for preemptive stochastic scheduling. We derive policies with a guaranteed performance ratio of 2 for scheduling jobs with release dates on identical parallel machines subject to minimizing the sum of weighted completion times. Our policies as well as their analysis apply also to the recently introduced more general model of stochastic online scheduling. The performance guarantee we give matches the best result known for the corresponding determinist...

  2. Revisiting Symbiotic Job Scheduling

    OpenAIRE

    Eyerman , Stijn; Michaud , Pierre; Rogiest , Wouter

    2015-01-01

    International audience; —Symbiotic job scheduling exploits the fact that in a system with shared resources, the performance of jobs is impacted by the behavior of other co-running jobs. By coscheduling combinations of jobs that have low interference, the performance of a system can be increased. In this paper, we investigate the impact of using symbiotic job scheduling for increasing throughput. We find that even for a theoretically optimal scheduler, this impact is very low, despite the subs...

  3. A spray based method for biofilm removal

    NARCIS (Netherlands)

    Cense, A.W.

    2005-01-01

    Biofilm growth on human teeth is the cause of oral diseases such as caries (tooth decay), gingivitis (inflammation of the gums) and periodontitis (inflammation of the tooth bone). In this thesis, a water based cleaning method is designed for removal of oral biofilms, or dental plaque. The first part

  4. Arts-Based Methods in Education

    DEFF Research Database (Denmark)

    Chemi, Tatiana; Du, Xiangyun

    2017-01-01

    This chapter introduces the field of arts-based methods in education with a general theoretical perspective, reviewing the journey of learning in connection to the arts, and the contribution of the arts to societies from an educational perspective. Also presented is the rationale and structure...

  5. Departure Queue Prediction for Strategic and Tactical Surface Scheduler Integration

    Science.gov (United States)

    Zelinski, Shannon; Windhorst, Robert

    2016-01-01

    A departure metering concept to be demonstrated at Charlotte Douglas International Airport (CLT) will integrate strategic and tactical surface scheduling components to enable the respective collaborative decision making and improved efficiency benefits these two methods of scheduling provide. This study analyzes the effect of tactical scheduling on strategic scheduler predictability. Strategic queue predictions and target gate pushback times to achieve a desired queue length are compared between fast time simulations of CLT surface operations with and without tactical scheduling. The use of variable departure rates as a strategic scheduler input was shown to substantially improve queue predictions over static departure rates. With target queue length calibration, the strategic scheduler can be tuned to produce average delays within one minute of the tactical scheduler. However, root mean square differences between strategic and tactical delays were between 12 and 15 minutes due to the different methods the strategic and tactical schedulers use to predict takeoff times and generate gate pushback clearances. This demonstrates how difficult it is for the strategic scheduler to predict tactical scheduler assigned gate delays on an individual flight basis as the tactical scheduler adjusts departure sequence to accommodate arrival interactions. Strategic/tactical scheduler compatibility may be improved by providing more arrival information to the strategic scheduler and stabilizing tactical scheduler changes to runway sequence in response to arrivals.

  6. Computer Animation Based on Particle Methods

    Directory of Open Access Journals (Sweden)

    Rafal Wcislo

    1999-01-01

    Full Text Available The paper presents the main issues of a computer animation of a set of elastic macroscopic objects based on the particle method. The main assumption of the generated animations is to achieve very realistic movements in a scene observed on the computer display. The objects (solid bodies interact mechanically with each other, The movements and deformations of solids are calculated using the particle method. Phenomena connected with the behaviour of solids in the gravitational field, their defomtations caused by collisions and interactions with the optional liquid medium are simulated. The simulation ofthe liquid is performed using the cellular automata method. The paper presents both simulation schemes (particle method and cellular automata rules an the method of combining them in the single animation program. ln order to speed up the execution of the program the parallel version based on the network of workstation was developed. The paper describes the methods of the parallelization and it considers problems of load-balancing, collision detection, process synchronization and distributed control of the animation.

  7. GPU-based parallel algorithm for blind image restoration using midfrequency-based methods

    Science.gov (United States)

    Xie, Lang; Luo, Yi-han; Bao, Qi-liang

    2013-08-01

    GPU-based general-purpose computing is a new branch of modern parallel computing, so the study of parallel algorithms specially designed for GPU hardware architecture is of great significance. In order to solve the problem of high computational complexity and poor real-time performance in blind image restoration, the midfrequency-based algorithm for blind image restoration was analyzed and improved in this paper. Furthermore, a midfrequency-based filtering method is also used to restore the image hardly with any recursion or iteration. Combining the algorithm with data intensiveness, data parallel computing and GPU execution model of single instruction and multiple threads, a new parallel midfrequency-based algorithm for blind image restoration is proposed in this paper, which is suitable for stream computing of GPU. In this algorithm, the GPU is utilized to accelerate the estimation of class-G point spread functions and midfrequency-based filtering. Aiming at better management of the GPU threads, the threads in a grid are scheduled according to the decomposition of the filtering data in frequency domain after the optimization of data access and the communication between the host and the device. The kernel parallelism structure is determined by the decomposition of the filtering data to ensure the transmission rate to get around the memory bandwidth limitation. The results show that, with the new algorithm, the operational speed is significantly increased and the real-time performance of image restoration is effectively improved, especially for high-resolution images.

  8. Scheduling Aircraft Landings under Constrained Position Shifting

    Science.gov (United States)

    Balakrishnan, Hamsa; Chandran, Bala

    2006-01-01

    Optimal scheduling of airport runway operations can play an important role in improving the safety and efficiency of the National Airspace System (NAS). Methods that compute the optimal landing sequence and landing times of aircraft must accommodate practical issues that affect the implementation of the schedule. One such practical consideration, known as Constrained Position Shifting (CPS), is the restriction that each aircraft must land within a pre-specified number of positions of its place in the First-Come-First-Served (FCFS) sequence. We consider the problem of scheduling landings of aircraft in a CPS environment in order to maximize runway throughput (minimize the completion time of the landing sequence), subject to operational constraints such as FAA-specified minimum inter-arrival spacing restrictions, precedence relationships among aircraft that arise either from airline preferences or air traffic control procedures that prevent overtaking, and time windows (representing possible control actions) during which each aircraft landing can occur. We present a Dynamic Programming-based approach that scales linearly in the number of aircraft, and describe our computational experience with a prototype implementation on realistic data for Denver International Airport.

  9. New Approaches to Irrigation Scheduling of Vegetables

    Directory of Open Access Journals (Sweden)

    Michael D. Cahn

    2017-04-01

    Full Text Available Using evapotranspiration (ET data for scheduling irrigations on vegetable farms is challenging due to imprecise crop coefficients, time consuming computations, and the need to simultaneously manage many fields. Meanwhile, the adoption of soil moisture monitoring in vegetables has historically been limited by sensor accuracy and cost, as well as labor required for installation, removal, and collection of readings. With recent improvements in sensor technology, public weather-station networks, satellite and aerial imaging, wireless communications, and cloud computing, many of the difficulties in using ET data and soil moisture sensors for irrigation scheduling of vegetables can now be addressed. Web and smartphone applications have been developed that automate many of the calculations involved in ET-based irrigation scheduling. Soil moisture sensor data can be collected through wireless networks and accessed using web browser or smartphone apps. Energy balance methods of crop ET estimation, such as eddy covariance and Bowen ratio, provide research options for further developing and evaluating crop coefficient guidelines of vegetables, while recent advancements in surface renewal instrumentation have led to a relatively low-cost tool for monitoring crop water requirement in commercial farms. Remote sensing of crops using satellite, manned aircraft, and UAV platforms may also provide useful tools for vegetable growers to evaluate crop development, plant stress, water consumption, and irrigation system performance.

  10. USING COMPUTER-BASED TESTING AS ALTERNATIVE ASSESSMENT METHOD OF STUDENT LEARNING IN DISTANCE EDUCATION

    Directory of Open Access Journals (Sweden)

    Amalia SAPRIATI

    2010-04-01

    Full Text Available This paper addresses the use of computer-based testing in distance education, based on the experience of Universitas Terbuka (UT, Indonesia. Computer-based testing has been developed at UT for reasons of meeting the specific needs of distance students as the following: Ø students’ inability to sit for the scheduled test, Ø conflicting test schedules, and Ø students’ flexibility to take examination to improve their grades. In 2004, UT initiated a pilot project in the development of system and program for computer-based testing method. Then in 2005 and 2006 tryouts in the use of computer-based testing methods were conducted in 7 Regional Offices that were considered as having sufficient supporting recourses. The results of the tryouts revealed that students were enthusiastic in taking computer-based tests and they expected that the test method would be provided by UT as alternative to the traditional paper and pencil test method. UT then implemented computer-based testing method in 6 and 12 Regional Offices in 2007 and 2008 respectively. The computer-based testing was administered in the city of the designated Regional Office and was supervised by the Regional Office staff. The development of the computer-based testing was initiated with conducting tests using computers in networked configuration. The system has been continually improved, and it currently uses devices linked to the internet or the World Wide Web. The construction of the test involves the generation and selection of the test items from the item bank collection of the UT Examination Center. Thus the combination of the selected items compromises the test specification. Currently UT has offered 250 courses involving the use of computer-based testing. Students expect that more courses are offered with computer-based testing in Regional Offices within easy access by students.

  11. Real-time energy resources scheduling considering short-term and very short-term wind forecast

    Energy Technology Data Exchange (ETDEWEB)

    Silva, Marco; Sousa, Tiago; Morais, Hugo; Vale, Zita [Polytechnic of Porto (Portugal). GECAD - Knowledge Engineering and Decision Support Research Center

    2012-07-01

    This paper proposes an energy resources management methodology based on three distinct time horizons: day-ahead scheduling, hour-ahead scheduling, and real-time scheduling. In each scheduling process the update of generation and consumption operation and of the storage and electric vehicles storage status are used. Besides the new operation conditions, the most accurate forecast values of wind generation and of consumption using results of short-term and very short-term methods are used. A case study considering a distribution network with intensive use of distributed generation and electric vehicles is presented. (orig.)

  12. Analisis Performansi Algoritma Penjadwalan Log Rule dan Frame Level Schedule Skenario Multicell Pada Layer Mac LTE

    Directory of Open Access Journals (Sweden)

    Ridwan

    2016-03-01

    Full Text Available Mobile telecommunications technology gradually evolved to support better services such as voice, data, and video to users of telecommunications services. LTE (Long Term Evolution is a network based on Internet Protocol (IP standardized by 3rd Generation Partnership Project (3GPP. To support it, LTE requires a mechanism that can support. One of them by applying methods of scheduling packets in each service. Scheduling is a different treatment to packets that come in accordance with the priorities of the scheduling algorithm. In this research, to analyze the performance of LTE with paramater delay, packet loss ratio, throughput and fairness index uses a scheduling algorithms Frame Level Schedule (FLS and Log Rule on LTE-Simulator with scenarios using Voip traffic, Video and Best Effort (BE. The results is scheduling algorithms FLS is better than log rule in term of throughput values, while of scheduling algorithms log rule is better than FLS in terms of delay based on the number and speed of the users. This indicates that both scheduling algorithms suitable for use in LTE networks within conditions of traffic real time services, but not for non real time services such as BE.

  13. Handbook of methods for risk-based analysis of technical specifications

    International Nuclear Information System (INIS)

    Samanta, P.K.; Kim, I.S.; Mankamo, T.; Vesely, W.E.

    1996-01-01

    Technical Specifications (TS) requirements for nuclear power plants define the Limiting Conditions for Operations (LCOs) and Surveillance Requirements (SRs) to assure safety during operation. In general, these requirements are based on deterministic analyses and engineering judgments. Improvements in these requirements are facilitated by the availability of plant-specific Probabilistic Risk Assessments (PRAs). The US Nuclear Regulatory Commission (USNRC) Office of Research sponsored research to develop systematic, risk-based methods to improve various aspects of TS requirements. A handbook of methods summarizing such risk-based approaches has been completed in 1994. It is expected that this handbook will provide valuable input to NRC's present work in developing guidance for using PRA in risk-informed regulation. The handbook addresses reliability and risk-based methods for evaluating allowed outage times (AOTs), action statements requiring shutdown where shutdown risk may be substantial, surveillance test intervals (STIs), managing plant configurations, and scheduling maintenance

  14. Alternative Work Schedules: Definitions

    Science.gov (United States)

    Journal of the College and University Personnel Association, 1977

    1977-01-01

    The term "alternative work schedules" encompasses any variation of the requirement that all permanent employees in an organization or one shift of employees adhere to the same five-day, seven-to-eight-hour schedule. This article defines staggered hours, flexible working hours (flexitour and gliding time), compressed work week, the task system, and…

  15. The triangle scheduling problem

    NARCIS (Netherlands)

    Dürr, Christoph; Hanzálek, Zdeněk; Konrad, Christian; Seddik, Yasmina; Sitters, R.A.; Vásquez, Óscar C.; Woeginger, Gerhard

    2017-01-01

    This paper introduces a novel scheduling problem, where jobs occupy a triangular shape on the time line. This problem is motivated by scheduling jobs with different criticality levels. A measure is introduced, namely the binary tree ratio. It is shown that the Greedy algorithm solves the problem to

  16. An evolutionary programming based simulated annealing method for solving the unit commitment problem

    Energy Technology Data Exchange (ETDEWEB)

    Christober Asir Rajan, C. [Department of EEE, Pondicherry Engineering College, Pondicherry 605014 (India); Mohan, M.R. [Department of EEE, Anna University, Chennai 600 025 (India)

    2007-09-15

    This paper presents a new approach to solve the short-term unit commitment problem using an evolutionary programming based simulated annealing method. The objective of this paper is to find the generation scheduling such that the total operating cost can be minimized, when subjected to a variety of constraints. This also means that it is desirable to find the optimal generating unit commitment in the power system for the next H hours. Evolutionary programming, which happens to be a global optimisation technique for solving unit commitment Problem, operates on a system, which is designed to encode each unit's operating schedule with regard to its minimum up/down time. In this, the unit commitment schedule is coded as a string of symbols. An initial population of parent solutions is generated at random. Here, each schedule is formed by committing all the units according to their initial status (''flat start''). Here the parents are obtained from a pre-defined set of solution's, i.e. each and every solution is adjusted to meet the requirements. Then, a random recommitment is carried out with respect to the unit's minimum down times. And SA improves the status. The best population is selected by evolutionary strategy. The Neyveli Thermal Power Station (NTPS) Unit-II in India demonstrates the effectiveness of the proposed approach; extensive studies have also been performed for different power systems consists of 10, 26, 34 generating units. Numerical results are shown comparing the cost solutions and computation time obtained by using the Evolutionary Programming method and other conventional methods like Dynamic Programming, Lagrangian Relaxation and Simulated Annealing and Tabu Search in reaching proper unit commitment. (author)

  17. Coordination between Generation and Transmission Maintenance Scheduling by Means of Multi-agent Technique

    Science.gov (United States)

    Nagata, Takeshi; Tao, Yasuhiro; Utatani, Masahiro; Sasaki, Hiroshi; Fujita, Hideki

    This paper proposes a multi-agent approach to maintenance scheduling in restructured power systems. The restructuring of electric power industry has resulted in market-based approaches for unbundling a multitude of service provided by self-interested entities such as power generating companies (GENCOs), transmission providers (TRANSCOs) and distribution companies (DISCOs). The Independent System Operator (ISO) is responsible for the security of the system operation. The schedule submitted to ISO by GENCOs and TRANSCOs should satisfy security and reliability constraints. The proposed method consists of several GENCO Agents (GAGs), TARNSCO Agents (TAGs) and a ISO Agent(IAG). The IAG’s role in maintenance scheduling is limited to ensuring that the submitted schedules do not cause transmission congestion or endanger the system reliability. From the simulation results, it can be seen the proposed multi-agent approach could coordinate between generation and transmission maintenance schedules.

  18. A customizable, scalable scheduling and reporting system.

    Science.gov (United States)

    Wood, Jody L; Whitman, Beverly J; Mackley, Lisa A; Armstrong, Robert; Shotto, Robert T

    2014-06-01

    Scheduling is essential for running a facility smoothly and for summarizing activities in use reports. The Penn State Hershey Clinical Simulation Center has developed a scheduling interface that uses off-the-shelf components, with customizations that adapt to each institution's data collection and reporting needs. The system is designed using programs within the Microsoft Office 2010 suite. Outlook provides the scheduling component, while the reporting is performed using Access or Excel. An account with a calendar is created for the main schedule, with separate resource accounts created for each room within the center. The Outlook appointment form's 2 default tabs are used, in addition to a customized third tab. The data are then copied from the calendar into either a database table or a spreadsheet, where the reports are generated.Incorporating this system into an institution-wide structure allows integration of personnel lists and potentially enables all users to check the schedule from their desktop. Outlook also has a Web-based application for viewing the basic schedule from outside the institution, although customized data cannot be accessed. The scheduling and reporting functions have been used for a year at the Penn State Hershey Clinical Simulation Center. The schedule has increased workflow efficiency, improved the quality of recorded information, and provided more accurate reporting. The Penn State Hershey Clinical Simulation Center's scheduling and reporting system can be adapted easily to most simulation centers and can expand and change to meet future growth with little or no expense to the center.

  19. A DSM-based “2.0” System for Human Intervention Planning and Scheduling in Facilities Emitting Ionizing Radiations

    CERN Document Server

    Baudin, M; De Jonghe, J

    2012-01-01

    To efficiently and safely plan, schedule and control its interventions in underground facilities, which are subject to ionizing radiations, CERN is currently developing a collaborative Web-based system. A similar project for maintenance management is also under way. On top of presenting their key requirements, this paper shows how the implementation of DSM can enhance a so-called Web 2.0 or collaborative dimension by bringing an intuitive and fair way of taking the dependencies between several activities into account. It is also discussed that the incoherencies brought in DSM by collaborative use (for instance regarding the time intervals) can be addressed by enlarging the binary DSM span of dependencies to ones of the Allen’s interval algebra or at least a subset of its dependencies.

  20. Oil drilling rig diesel power-plant fuel efficiency improvement potentials through rule-based generator scheduling and utilization of battery energy storage system

    International Nuclear Information System (INIS)

    Pavković, Danijel; Sedić, Almir; Guzović, Zvonimir

    2016-01-01

    Highlights: • Isolated oil drilling rig microgrid power flows are analyzed over 30 days. • Rule-based diesel generator scheduling is proposed to reduce fuel consumption. • A battery energy storage is parameterized and used for peak load leveling. • The effectiveness of proposed hybrid microgrid is verified by simulations. • Return-of-investment might be expected within 20% of battery system lifetime. - Abstract: This paper presents the development of a rule-based energy management control strategy suitable for isolated diesel power-plants equipped with a battery energy storage system for peak load shaving. The proposed control strategy includes the generator scheduling strategy and peak load leveling scheme based on current microgrid active and reactive power requirements. In order to investigate the potentials for fuel expenditure reduction, 30 days-worth of microgrid power flow data has been collected on an isolated land-based oil drilling rig powered by a diesel generator power-plant, characterized by highly-variable active and reactive load profiles due to intermittent engagements and disengagements of high-power electric machinery such as top-drive, draw-works and mud-pump motors. The analysis has indicated that by avoiding the low-power operation of individual generators and by providing the peak power requirements (peak shaving) from a dedicated energy storage system, the power-plant fuel efficiency may be notably improved. An averaged power flow simulation model has been built, comprising the proposed rule-based power flow control strategy and the averaged model of a suitably sized battery energy storage system equipped with grid-tied power converter and state-of-charge control system. The effectiveness of the proposed rule-based strategy has been evaluated by means of computer simulation analysis based on drilling rig microgrid active and reactive power data recorded during the 30 day period. The analysis has indicated that fuel consumption of