Solving scheduling problems by untimed model checking. The clinical chemical analyser case study
Margaria, T.; Wijs, Anton J.; Massink, M.; van de Pol, Jan Cornelis; Bortnik, Elena M.
2009-01-01
In this article, we show how scheduling problems can be modelled in untimed process algebra, by using special tick actions. A minimal-cost trace leading to a particular action, is one that minimises the number of tick steps. As a result, we can use any (timed or untimed) model checking tool to find
Solving a chemical batch scheduling problem by local search
Brucker, P.; Hurink, Johann L.
1999-01-01
A chemical batch scheduling problem is modelled in two different ways as a discrete optimization problem. Both models are used to solve the batch scheduling problem in a two-phase tabu search procedure. The method is tested on real-world data.
Directory of Open Access Journals (Sweden)
H Kazemipoor
2012-04-01
Full Text Available A multi-skilled project scheduling problem (MSPSP has been generally presented to schedule a project with staff members as resources. Each activity in project network requires different skills and also staff members have different skills, too. This causes the MSPSP becomes a special type of a multi-mode resource-constrained project scheduling problem (MM-RCPSP with a huge number of modes. Given the importance of this issue, in this paper, a mixed integer linear programming for the MSPSP is presented. Due to the complexity of the problem, a meta-heuristic algorithm is proposed in order to find near optimal solutions. To validate performance of the algorithm, results are compared against exact solutions solved by the LINGO solver. The results are promising and show that optimal or near-optimal solutions are derived for small instances and good solutions for larger instances in reasonable time.
Solving cyclical nurse scheduling problem using preemptive goal programming
Sundari, V. E.; Mardiyati, S.
2017-07-01
Nurse scheduling system in a hospital is being modeled as a preemptive goal programming problem that is solved by using LINGO software with the objective function to minimize deviation variable at each goal. The scheduling is done cyclically, so every nurse is treated fairly since they have the same work shift portion with the other nurses. By paying attention to the hospital's rules regarding nursing work shift cyclically, it can be obtained that numbers of nurse needed in every ward are 18 nurses and the numbers of scheduling periods are 18 periods where every period consists of 21 days.
Ebrahimi, Ahmad; Kia, Reza; Komijan, Alireza Rashidi
2016-01-01
In this article, a novel integrated mixed-integer nonlinear programming model is presented for designing a cellular manufacturing system (CMS) considering machine layout and part scheduling problems simultaneously as interrelated decisions. The integrated CMS model is formulated to incorporate several design features including part due date, material handling time, operation sequence, processing time, an intra-cell layout of unequal-area facilities, and part scheduling. The objective function is to minimize makespan, tardiness penalties, and material handling costs of inter-cell and intra-cell movements. Two numerical examples are solved by the Lingo software to illustrate the results obtained by the incorporated features. In order to assess the effects and importance of integration of machine layout and part scheduling in designing a CMS, two approaches, sequentially and concurrent are investigated and the improvement resulted from a concurrent approach is revealed. Also, due to the NP-hardness of the integrated model, an efficient genetic algorithm is designed. As a consequence, computational results of this study indicate that the best solutions found by GA are better than the solutions found by B&B in much less time for both sequential and concurrent approaches. Moreover, the comparisons between the objective function values (OFVs) obtained by sequential and concurrent approaches demonstrate that the OFV improvement is averagely around 17 % by GA and 14 % by B&B.
Solving University Scheduling Problem Using Hybrid Approach
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Aftab Ahmed Shaikh
2011-10-01
Full Text Available In universities scheduling curriculum activity is an essential job. Primarily, scheduling is a distribution of limited resources under interrelated constraints. The set of hard constraints demand the highest priority and should not to be violated at any cost, while the maximum soft constraints satisfaction mounts the quality scale of solution. In this research paper, a novel bisected approach is introduced that is comprisesd of GA (Genetic Algorithm as well as Backtracking Recursive Search. The employed technique deals with both hard and soft constraints successively. The first phase decisively is focused over elimination of all the hard constraints bounded violations and eventually produces partial solution for subsequent step. The second phase is supposed to draw the best possible solution on the search space. Promising results are obtained by implementation on the real dataset. The key points of the research approach are to get assurance of hard constraints removal from the dataset and minimizing computational time for GA by initializing pre-processed set of chromosomes.
Modelling altered fractionation schedules
International Nuclear Information System (INIS)
Fowler, J.F.
1993-01-01
The author discusses the conflicting requirements of hyperfractionation and accelerated fractionation used in radiotherapy, and the development of computer modelling to predict how to obtain an optimum of tumour cell kill without exceeding normal-tissue tolerance. The present trend is to shorten hyperfractionated schedules from 6 or 7 weeks to give overall times of 4 or 5 weeks as in new schedules by Herskovic et al (1992) and Harari (1992). Very high doses are given, much higher than can be given when ultrashort schedules such as CHART (12 days) are used. Computer modelling has suggested that optimum overall times, to yield maximum cell kill in tumours ((α/β = 10 Gy) for a constant level of late complications (α/β = 3 Gy) would be X or X-1 weeks, where X is the doubling time of the tumour cells in days (Fowler 1990). For median doubling times of about 5 days, overall times of 4 or 5 weeks should be ideal. (U.K.)
A matheuristic approach for solving the Integrated Timetabling and Vehicle Scheduling Problem
DEFF Research Database (Denmark)
Fonseca, Joao Filipe Paiva; Larsen, Allan; van der Hurk, Evelien
between different trips. We consider transfers between bus trips scheduled by the model, but also transfers to other fixed lines that intersect the lines considered in the IT-VSP. We present a MIP formulation of the IT-VSP able to solve small instances of the problem, and a matheuristic approach that uses...... the compact MIP to solve larger instances of the problem. The idea is to iteratively solve restricted versions of the MIP selecting at each step a subset of trips where modifications are allowed, while all other trips remain fixed. The performance of the proposed matheuristic is shown on a case study...
Group Elevator Peak Scheduling Based on Robust Optimization Model
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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.
Modeling the Cray memory scheduler
Energy Technology Data Exchange (ETDEWEB)
Wickham, K.L.; Litteer, G.L.
1992-04-01
This report documents the results of a project to evaluate low cost modeling and simulation tools when applied to modeling the Cray memory scheduler. The specific tool used is described and the basics of the memory scheduler are covered. Results of simulations using the model are discussed and a favorable recommendation is made to make more use of this inexpensive technology.
Directory of Open Access Journals (Sweden)
Behnam Barzegar
2012-01-01
Full Text Available Scheduled production system leads to avoiding stock accumulations, losses reduction, decreasing or even eliminating idol machines, and effort to better benefitting from machines for on time responding customer orders and supplying requested materials in suitable time. In flexible job-shop scheduling production systems, we could reduce time and costs by transferring and delivering operations on existing machines, that is, among NP-hard problems. The scheduling objective minimizes the maximal completion time of all the operations, which is denoted by Makespan. Different methods and algorithms have been presented for solving this problem. Having a reasonable scheduled production system has significant influence on improving effectiveness and attaining to organization goals. In this paper, new algorithm were proposed for flexible job-shop scheduling problem systems (FJSSP-GSPN that is based on gravitational search algorithm (GSA. In the proposed method, the flexible job-shop scheduling problem systems was modeled by color Petri net and CPN tool and then a scheduled job was programmed by GSA algorithm. The experimental results showed that the proposed method has reasonable performance in comparison with other algorithms.
Solving project scheduling problems by minimum cut computations
Möhring, R.H.; Schulz, A.S.; Stork, F.; Uetz, Marc Jochen
In project scheduling, a set of precedence-constrained jobs has to be scheduled so as to minimize a given objective. In resource-constrained project scheduling, the jobs additionally compete for scarce resources. Due to its universality, the latter problem has a variety of applications in
Multiagent scheduling models and algorithms
Agnetis, Alessandro; Gawiejnowicz, Stanisław; Pacciarelli, Dario; Soukhal, Ameur
2014-01-01
This book presents multi-agent scheduling models in which subsets of jobs sharing the same resources are evaluated by different criteria. It discusses complexity results, approximation schemes, heuristics and exact algorithms.
Linearly Ordered Attribute Grammar Scheduling Using SAT-Solving
Bransen, Jeroen; van Binsbergen, L.Thomas; Claessen, Koen; Dijkstra, Atze
2015-01-01
Many computations over trees can be specified using attribute grammars. Compilers for attribute grammars need to find an evaluation order (or schedule) in order to generate efficient code. For the class of linearly ordered attribute grammars such a schedule can be found statically, but this problem
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...
A meta-heuristic method for solving scheduling problem: crow search algorithm
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.
Solving a manpower scheduling problem for airline catering using metaheuristics
DEFF Research Database (Denmark)
Ho, Sin C.; Leung, Janny M. Y.
2010-01-01
We study a manpower scheduling problem with job time-windows and job-skills compatibility constraints. This problem is motivated by airline catering operations, whereby airline meals and other supplies are delivered to aircrafts on the tarmac just before the flights take-off. Jobs (flights) must...
Solving Large Scale Crew Scheduling Problems in Practice
E.J.W. Abbink (Erwin); L. Albino; T.A.B. Dollevoet (Twan); D. Huisman (Dennis); J. Roussado; R.L. Saldanha
2010-01-01
textabstractThis paper deals with large-scale crew scheduling problems arising at the Dutch railway operator, Netherlands Railways (NS). NS operates about 30,000 trains a week. All these trains need a driver and a certain number of guards. Some labor rules restrict the duties of a certain crew base
Directory of Open Access Journals (Sweden)
Alexandr Victorovich Budylskiy
2014-06-01
Full Text Available This article considers the multicriteria optimization approach using the modified genetic algorithm to solve the project-scheduling problem under duration and cost constraints. The work contains the list of choices for solving this problem. The multicriteria optimization approach is justified here. The study describes the Pareto principles, which are used in the modified genetic algorithm. We identify the mathematical model of the project-scheduling problem. We introduced the modified genetic algorithm, the ranking strategies, the elitism approaches. The article includes the example.
Shao, Zhongshi; Pi, Dechang; Shao, Weishi
2017-11-01
This article proposes an extended continuous estimation of distribution algorithm (ECEDA) to solve the permutation flow-shop scheduling problem (PFSP). In ECEDA, to make a continuous estimation of distribution algorithm (EDA) suitable for the PFSP, the largest order value rule is applied to convert continuous vectors to discrete job permutations. A probabilistic model based on a mixed Gaussian and Cauchy distribution is built to maintain the exploration ability of the EDA. Two effective local search methods, i.e. revolver-based variable neighbourhood search and Hénon chaotic-based local search, are designed and incorporated into the EDA to enhance the local exploitation. The parameters of the proposed ECEDA are calibrated by means of a design of experiments approach. Simulation results and comparisons based on some benchmark instances show the efficiency of the proposed algorithm for solving the PFSP.
Resource-constrained project scheduling: computing lower bounds by solving minimum cut problems
Möhring, R.H.; Nesetril, J.; Schulz, A.S.; Stork, F.; Uetz, Marc Jochen
1999-01-01
We present a novel approach to compute Lagrangian lower bounds on the objective function value of a wide class of resource-constrained project scheduling problems. The basis is a polynomial-time algorithm to solve the following scheduling problem: Given a set of activities with start-time dependent
Directory of Open Access Journals (Sweden)
Renata Melo e Silva de Oliveira
2015-03-01
Full Text Available Scheduling is a key factor for operations management as well as for business success. From industrial Job-shop Scheduling problems (JSSP, many optimization challenges have emerged since de 1960s when improvements have been continuously required such as bottlenecks allocation, lead-time reductions and reducing response time to requests. With this in perspective, this work aims to discuss 3 different optimization models for minimizing Makespan. Those 3 models were applied on 17 classical problems of examples JSSP and produced different outputs. The first model resorts on Mixed and Integer Programming (MIP and it resulted on optimizing 60% of the studied problems. The other models were based on Constraint Programming (CP and approached the problem in two different ways: a model CP1 is a standard IBM algorithm whereof restrictions have an interval structure that fail to solve 53% of the proposed instances, b Model CP-2 approaches the problem with disjunctive constraints and optimized 88% of the instances. In this work, each model is individually analyzed and then compared considering: i Optimization success performance, ii Computational processing time, iii Greatest Resource Utilization and, iv Minimum Work-in-process Inventory. Results demonstrated that CP-2 presented best results on criteria i and ii, but MIP was superior on criteria iii and iv and those findings are discussed at the final section of this work.
Solving Multi-Resource Constrained Project Scheduling Problem using Ant Colony Optimization
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Hsiang-Hsi Huang
2015-01-01
Full Text Available This paper applied Ant Colony Optimization (ACO to develop a resource constraints scheduling model to achieve the resource allocation optimization and the shortest completion time of a project under resource constraints and the activities precedence requirement for projects. Resource leveling is also discussed and has to be achieved under the resource allocation optimization in this research. Testing cases and examples adopted from the international test bank were studied for verifying the effectiveness of the proposed model. The results showed that the solutions of different cases all have a better performance within a reasonable time. These can be obtained through ACO algorithm under the same constrained conditions. A program was written for the proposed model that is able to automatically produce the project resource requirement figure after the project duration is solved.
Hybrid Metaheuristics for Solving a Fuzzy Single Batch-Processing Machine Scheduling Problem
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S. Molla-Alizadeh-Zavardehi
2014-01-01
Full Text Available This paper deals with a problem of minimizing total weighted tardiness of jobs in a real-world single batch-processing machine (SBPM scheduling in the presence of fuzzy due date. In this paper, first a fuzzy mixed integer linear programming model is developed. Then, due to the complexity of the problem, which is NP-hard, we design two hybrid metaheuristics called GA-VNS and VNS-SA applying the advantages of genetic algorithm (GA, variable neighborhood search (VNS, and simulated annealing (SA frameworks. Besides, we propose three fuzzy earliest due date heuristics to solve the given problem. Through computational experiments with several random test problems, a robust calibration is applied on the parameters. Finally, computational results on different-scale test problems are presented to compare the proposed algorithms.
SOLVING FLOWSHOP SCHEDULING PROBLEMS USING A DISCRETE AFRICAN WILD DOG ALGORITHM
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M. K. Marichelvam
2013-04-01
Full Text Available The problem of m-machine permutation flowshop scheduling is considered in this paper. The objective is to minimize the makespan. The flowshop scheduling problem is a typical combinatorial optimization problem and has been proved to be strongly NP-hard. Hence, several heuristics and meta-heuristics were addressed by the researchers. In this paper, a discrete African wild dog algorithm is applied for solving the flowshop scheduling problems. Computational results using benchmark problems show that the proposed algorithm outperforms many other algorithms addressed in the literature.
A review on application of neural networks and fuzzy logic to solve hydrothermal scheduling problem
International Nuclear Information System (INIS)
Haroon, S.; Malik, T.N.; Zafar, S.
2014-01-01
Electrical power system is highly complicated having hydro and thermal mix with large number of machines. To reduce power production cost, hydro and thermal resources are mixed. Hydrothermal scheduling is the optimal coordination of hydro and thermal plants to meet the system load demand at minimum possible operational cost while satisfying the system constraints. Hydrothermal scheduling is dynamic, large scale, non-linear and non-convex optimization problem. The classical techniques have failed in solving such problem. Artificial Intelligence Tools based techniques are used now a day to solve this complex optimization problem because of their no requirements on the nature of the problem. The aim of this research paper is to provide a comprehensive survey of literature related to both Artificial Neural Network (ANN) and Fuzzy Logic (FL) as effective optimization algorithms for the hydrothermal scheduling problem. The outcomes along with the merits and demerits of individual techniques are also discussed. (author)
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.
Directory of Open Access Journals (Sweden)
Jamal Abdul Nasir
2018-01-01
Full Text Available Development of an efficient and effective home health care (HHC service system is a quite recent and challenging task for the HHC firms. This paper aims to develop an HHC service system in the perspective of long-term economic sustainability as well as operational efficiency. A more flexible mixed-integer linear programming (MILP model is formulated by incorporating the dynamic arrival and departure of patients along with the selection of new patients and nursing staff. An integrated model is proposed that jointly addresses: (i patient selection; (ii nurse hiring; (iii nurse to patient assignment; and (iv scheduling and routing decisions in a daily HHC planning problem. The proposed model extends the HHC problem from conventional scheduling and routing issues to demand and capacity management aspects. It enables an HHC firm to solve the daily scheduling and routing problem considering existing patients and nursing staff in combination with the simultaneous selection of new patients and nurses, and optimizing the existing routes by including new patients and nurses. The model considers planning issues related to compatibility, time restrictions, contract durations, idle time and workload balance. Two heuristic methods are proposed to solve the model by exploiting the variable neighborhood search (VNS approach. Results obtained from the heuristic methods are compared with a CPLEX based solution. Numerical experiments performed on different data sets, show the efficiency and effectiveness of the solution methods to handle the considered problem.
Santosa, B.; Siswanto, N.; Fiqihesa
2018-04-01
This paper proposes a discrete Particle Swam Optimization (PSO) to solve limited-wait hybrid flowshop scheduing problem with multi objectives. Flow shop schedulimg represents the condition when several machines are arranged in series and each job must be processed at each machine with same sequence. The objective functions are minimizing completion time (makespan), total tardiness time, and total machine idle time. Flow shop scheduling model always grows to cope with the real production system accurately. Since flow shop scheduling is a NP-Hard problem then the most suitable method to solve is metaheuristics. One of metaheuristics algorithm is Particle Swarm Optimization (PSO), an algorithm which is based on the behavior of a swarm. Originally, PSO was intended to solve continuous optimization problems. Since flow shop scheduling is a discrete optimization problem, then, we need to modify PSO to fit the problem. The modification is done by using probability transition matrix mechanism. While to handle multi objectives problem, we use Pareto Optimal (MPSO). The results of MPSO is better than the PSO because the MPSO solution set produced higher probability to find the optimal solution. Besides the MPSO solution set is closer to the optimal solution
Solving a large-scale precedence constrained scheduling problem with elastic jobs using tabu search
DEFF Research Database (Denmark)
Pedersen, C.R.; Rasmussen, R.V.; Andersen, Kim Allan
2007-01-01
exploitation of the elastic jobs and solve the problem using a tabu search procedure. Finding an initial feasible solution is in general -complete, but the tabu search procedure includes a specialized heuristic for solving this problem. The solution method has proven to be very efficient and leads......This paper presents a solution method for minimizing makespan of a practical large-scale scheduling problem with elastic jobs. The jobs are processed on three servers and restricted by precedence constraints, time windows and capacity limitations. We derive a new method for approximating the server...... to a significant decrease in makespan compared to the strategy currently implemented....
Solving a large-scale precedence constrained scheduling problem with elastic jobs using tabu search
DEFF Research Database (Denmark)
Pedersen, C.R.; Rasmussen, R.V.; Andersen, Kim Allan
2007-01-01
This paper presents a solution method for minimizing makespan of a practical large-scale scheduling problem with elastic jobs. The jobs are processed on three servers and restricted by precedence constraints, time windows and capacity limitations. We derive a new method for approximating the server...... exploitation of the elastic jobs and solve the problem using a tabu search procedure. Finding an initial feasible solution is in general -complete, but the tabu search procedure includes a specialized heuristic for solving this problem. The solution method has proven to be very efficient and leads...
Processing time tolerance-based ACO algorithm for solving job-shop scheduling problem
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.
Solving and Interpreting Large-scale Harvest Scheduling Problems by Duality and Decomposition
Berck, Peter; Bible, Thomas
1982-01-01
This paper presents a solution to the forest planning problem that takes advantage of both the duality of linear programming formulations currently being used for harvest scheduling and the characteristics of decomposition inherent in the forest land class-relationship. The subproblems of decomposition, defined as the dual, can be solved in a simple, recursive fashion. In effect, such a technique reduces the computational burden in terms of time and computer storage as compared to the traditi...
Solving rational expectations models using Excel
DEFF Research Database (Denmark)
Strulik, Holger
2004-01-01
Problems of discrete time optimal control can be solved using backward iteration and Microsoft Excel. The author explains the method in general and shows how the basic models of neoclassical growth and real business cycles are solved......Problems of discrete time optimal control can be solved using backward iteration and Microsoft Excel. The author explains the method in general and shows how the basic models of neoclassical growth and real business cycles are solved...
A tabu-search heuristic for solving the multi-depot vehicle scheduling problem
Directory of Open Access Journals (Sweden)
Gilmar D'Agostini Oliveira Casalinho
2014-08-01
Full Text Available Currently the logistical problems are relying quite significantly on Operational Research in order to achieve greater efficiency in their operations. Among the problems related to the vehicles scheduling in a logistics system, the Multiple Depot Vehicle Scheduling Problem (MDVSP has been addressed in several studies. The MDVSP presupposes the existence of depots that affect the planning of sequences to which travel must be performed. Often, exact methods cannot solve large instances encountered in practice and in order to take them into account, several heuristic approaches are being developed. The aim of this study was thus to solve the MDVSP using a meta-heuristic based on tabu-search method. The main motivation for this work came from the indication that only recently the use of meta-heuristics is being applied to MDVSP context (Pepin et al. 2008 and, also, the limitations listed by Rohde (2008 in his study, which used the branch-and-bound in one of the steps of the heuristic presented to solve the problem, which has increased the time resolution. The research method for solving this problem was based on adaptations of traditional techniques of Operational Research, and provided resolutions presenting very competitive results for the MDVSP such as the cost of the objective function, number of vehicles used and computational time.
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
Solving multi-objective job shop scheduling problems using a non-dominated sorting genetic algorithm
Piroozfard, Hamed; Wong, Kuan Yew
2015-05-01
The efforts of finding optimal schedules for the job shop scheduling problems are highly important for many real-world industrial applications. In this paper, a multi-objective based job shop scheduling problem by simultaneously minimizing makespan and tardiness is taken into account. The problem is considered to be more complex due to the multiple business criteria that must be satisfied. To solve the problem more efficiently and to obtain a set of non-dominated solutions, a meta-heuristic based non-dominated sorting genetic algorithm is presented. In addition, task based representation is used for solution encoding, and tournament selection that is based on rank and crowding distance is applied for offspring selection. Swapping and insertion mutations are employed to increase diversity of population and to perform intensive search. To evaluate the modified non-dominated sorting genetic algorithm, a set of modified benchmarking job shop problems obtained from the OR-Library is used, and the results are considered based on the number of non-dominated solutions and quality of schedules obtained by the algorithm.
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.
NASA Instrument Cost/Schedule Model
Habib-Agahi, Hamid; Mrozinski, Joe; Fox, George
2011-01-01
NASA's Office of Independent Program and Cost Evaluation (IPCE) has established a number of initiatives to improve its cost and schedule estimating capabilities. 12One of these initiatives has resulted in the JPL developed NASA Instrument Cost Model. NICM is a cost and schedule estimator that contains: A system level cost estimation tool; a subsystem level cost estimation tool; a database of cost and technical parameters of over 140 previously flown remote sensing and in-situ instruments; a schedule estimator; a set of rules to estimate cost and schedule by life cycle phases (B/C/D); and a novel tool for developing joint probability distributions for cost and schedule risk (Joint Confidence Level (JCL)). This paper describes the development and use of NICM, including the data normalization processes, data mining methods (cluster analysis, principal components analysis, regression analysis and bootstrap cross validation), the estimating equations themselves and a demonstration of the NICM tool suite.
A Multivariate Model of Physics Problem Solving
Taasoobshirazi, Gita; Farley, John
2013-01-01
A model of expertise in physics problem solving was tested on undergraduate science, physics, and engineering majors enrolled in an introductory-level physics course. Structural equation modeling was used to test hypothesized relationships among variables linked to expertise in physics problem solving including motivation, metacognitive planning,…
A HYBRID HEURISTIC ALGORITHM FOR SOLVING THE RESOURCE CONSTRAINED PROJECT SCHEDULING PROBLEM (RCPSP
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Juan Carlos Rivera
Full Text Available The Resource Constrained Project Scheduling Problem (RCPSP is a problem of great interest for the scientific community because it belongs to the class of NP-Hard problems and no methods are known that can solve it accurately in polynomial processing times. For this reason heuristic methods are used to solve it in an efficient way though there is no guarantee that an optimal solution can be obtained. This research presents a hybrid heuristic search algorithm to solve the RCPSP efficiently, combining elements of the heuristic Greedy Randomized Adaptive Search Procedure (GRASP, Scatter Search and Justification. The efficiency obtained is measured taking into account the presence of the new elements added to the GRASP algorithm taken as base: Justification and Scatter Search. The algorithms are evaluated using three data bases of instances of the problem: 480 instances of 30 activities, 480 of 60, and 600 of 120 activities respectively, taken from the library PSPLIB available online. The solutions obtained by the developed algorithm for the instances of 30, 60 and 120 are compared with results obtained by other researchers at international level, where a prominent place is obtained, according to Chen (2011.
DEVELOPMENT OF A MAINTENANCE SCHEDULING MODEL FOR ...
African Journals Online (AJOL)
... of minor maintenance, for each machine within this time span. In order to minimize the total cost of repairs and production. A numerical application of this development model in a case study is presented. Key words: Maintenance, modeling, scheduling, optimization. [Global Jnl Engineering Res. Vol.1(2) 2002: 107-118] ...
Bilevel Fuzzy Chance Constrained Hospital Outpatient Appointment Scheduling Model
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Xiaoyang Zhou
2016-01-01
Full Text Available Hospital outpatient departments operate by selling fixed period appointments for different treatments. The challenge being faced is to improve profit by determining the mix of full time and part time doctors and allocating appointments (which involves scheduling a combination of doctors, patients, and treatments to a time period in a department optimally. In this paper, a bilevel fuzzy chance constrained model is developed to solve the hospital outpatient appointment scheduling problem based on revenue management. In the model, the hospital, the leader in the hierarchy, decides the mix of the hired full time and part time doctors to maximize the total profit; each department, the follower in the hierarchy, makes the decision of the appointment scheduling to maximize its own profit while simultaneously minimizing surplus capacity. Doctor wage and demand are considered as fuzzy variables to better describe the real-life situation. Then we use chance operator to handle the model with fuzzy parameters and equivalently transform the appointment scheduling model into a crisp model. Moreover, interactive algorithm based on satisfaction is employed to convert the bilevel programming into a single level programming, in order to make it solvable. Finally, the numerical experiments were executed to demonstrate the efficiency and effectiveness of the proposed approaches.
Gholamnejad, J.; Moosavi, E.
2012-01-01
Determination of the optimum production schedules over the life of a mine is a critical mechanism in open pit mine planning procedures. Long-term production scheduling is used to maximize the net present value of the project under technical, financial, and environmental constraints. Mathematical programming models are well suited for optimizing long-term production schedules of open pit mines. There are two approaches to solving long-term production problems: deterministic- and uncertainty- b...
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J. S. Sadaghiani
2014-04-01
Full Text Available Flexible job shop scheduling problem is a key factor of using efficiently in production systems. This paper attempts to simultaneously optimize three objectives including minimization of the make span, total workload and maximum workload of jobs. Since the multi objective flexible job shop scheduling problem is strongly NP-Hard, an integrated heuristic approach has been used to solve it. The proposed approach was based on a floating search procedure that has used some heuristic algorithms. Within floating search procedure utilize local heuristic algorithms; it makes the considered problem into two sections including assigning and sequencing sub problem. First of all search is done upon assignment space achieving an acceptable solution and then search would continue on sequencing space based on a heuristic algorithm. This paper has used a multi-objective approach for producing Pareto solution. Thus proposed approach was adapted on NSGA II algorithm and evaluated Pareto-archives. The elements and parameters of the proposed algorithms were adjusted upon preliminary experiments. Finally, computational results were used to analyze efficiency of the proposed algorithm and this results showed that the proposed algorithm capable to produce efficient solutions.
Genetic algorithm to solve the problems of lectures and practicums scheduling
Syahputra, M. F.; Apriani, R.; Sawaluddin; Abdullah, D.; Albra, W.; Heikal, M.; Abdurrahman, A.; Khaddafi, M.
2018-02-01
Generally, the scheduling process is done manually. However, this method has a low accuracy level, along with possibilities that a scheduled process collides with another scheduled process. When doing theory class and practicum timetable scheduling process, there are numerous problems, such as lecturer teaching schedule collision, schedule collision with another schedule, practicum lesson schedules that collides with theory class, and the number of classrooms available. In this research, genetic algorithm is implemented to perform theory class and practicum timetable scheduling process. The algorithm will be used to process the data containing lists of lecturers, courses, and class rooms, obtained from information technology department at University of Sumatera Utara. The result of scheduling process using genetic algorithm is the most optimal timetable that conforms to available time slots, class rooms, courses, and lecturer schedules.
Developing a Model for Solving the Flight Perturbation Problem
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Amirreza Nickkar
2015-02-01
Full Text Available Purpose: In the aviation and airline industry, crew costs are the second largest direct operating cost next to the fuel costs. But unlike the fuel costs, a considerable portion of the crew costs can be saved through optimized utilization of the internal resources of an airline company. Therefore, solving the flight perturbation scheduling problem, in order to provide an optimized schedule in a comprehensive manner that covered all problem dimensions simultaneously, is very important. In this paper, we defined an integrated recovery model as that which is able to recover aircraft and crew dimensions simultaneously in order to produce more economical solutions and create fewer incompatibilities between the decisions. Design/methodology/approach: Current research is performed based on the development of one of the flight rescheduling models with disruption management approach wherein two solution strategies for flight perturbation problem are presented: Dantzig-Wolfe decomposition and Lagrangian heuristic. Findings: According to the results of this research, Lagrangian heuristic approach for the DW-MP solved the problem optimally in all known cases. Also, this strategy based on the Dantig-Wolfe decomposition manage to produce a solution within an acceptable time (Under 1 Sec. Originality/value: This model will support the decisions of the flight controllers in the operation centers for the airlines. When the flight network faces a problem the flight controllers achieve a set of ranked answers using this model thus, applying crew’s conditions in the proposed model caused this model to be closer to actual conditions.
Using Optimization Models for Scheduling in Enterprise Resource Planning Systems
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Frank Herrmann
2016-03-01
Full Text Available Companies often use specially-designed production systems and change them from time to time. They produce small batches in order to satisfy specific demands with the least tardiness. This imposes high demands on high-performance scheduling algorithms which can be rapidly adapted to changes in the production system. As a solution, this paper proposes a generic approach: solutions were obtained using a widely-used commercially-available tool for solving linear optimization models, which is available in an Enterprise Resource Planning System (in the SAP system for example or can be connected to it. In a real-world application of a flow shop with special restrictions this approach is successfully used on a standard personal computer. Thus, the main implication is that optimal scheduling with a commercially-available tool, incorporated in an Enterprise Resource Planning System, may be the best approach.
Modeling visual problem solving as analogical reasoning.
Lovett, Andrew; Forbus, Kenneth
2017-01-01
We present a computational model of visual problem solving, designed to solve problems from the Raven's Progressive Matrices intelligence test. The model builds on the claim that analogical reasoning lies at the heart of visual problem solving, and intelligence more broadly. Images are compared via structure mapping, aligning the common relational structure in 2 images to identify commonalities and differences. These commonalities or differences can themselves be reified and used as the input for future comparisons. When images fail to align, the model dynamically rerepresents them to facilitate the comparison. In our analysis, we find that the model matches adult human performance on the Standard Progressive Matrices test, and that problems which are difficult for the model are also difficult for people. Furthermore, we show that model operations involving abstraction and rerepresentation are particularly difficult for people, suggesting that these operations may be critical for performing visual problem solving, and reasoning more generally, at the highest level. (PsycINFO Database Record (c) 2016 APA, all rights reserved).
Problem Solving Model for Science Learning
Alberida, H.; Lufri; Festiyed; Barlian, E.
2018-04-01
This research aims to develop problem solving model for science learning in junior high school. The learning model was developed using the ADDIE model. An analysis phase includes curriculum analysis, analysis of students of SMP Kota Padang, analysis of SMP science teachers, learning analysis, as well as the literature review. The design phase includes product planning a science-learning problem-solving model, which consists of syntax, reaction principle, social system, support system, instructional impact and support. Implementation of problem-solving model in science learning to improve students' science process skills. The development stage consists of three steps: a) designing a prototype, b) performing a formative evaluation and c) a prototype revision. Implementation stage is done through a limited trial. A limited trial was conducted on 24 and 26 August 2015 in Class VII 2 SMPN 12 Padang. The evaluation phase was conducted in the form of experiments at SMPN 1 Padang, SMPN 12 Padang and SMP National Padang. Based on the development research done, the syntax model problem solving for science learning at junior high school consists of the introduction, observation, initial problems, data collection, data organization, data analysis/generalization, and communicating.
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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.
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Zhongfu Tan
2015-01-01
Full Text Available In order to solve the influence of load uncertainty on hydrothermal power system operation and achieve the optimal objectives of system power generation consumption, pollutant emissions, and first-stage hydropower station storage capacity, this paper introduced CVaR method and built a multiobjective optimization model and its solving method. In the optimization model, load demand’s actual values and deviation values are regarded as random variables, scheduling objective is redefined to meet confidence level requirement and system operation constraints and loss function constraints are taken into consideration. To solve the proposed model, this paper linearized nonlinear constraints, applied fuzzy satisfaction, fuzzy entropy, and weighted multiobjective function theories to build a fuzzy entropy multiobjective CVaR model. The model is a mixed integer linear programming problem. Then, six thermal power plants and three cascade hydropower stations are taken as the hydrothermal system for numerical simulation. The results verified that multiobjective CVaR method is applicable to solve hydrothermal scheduling problems. It can better reflect risk level of the scheduling result. The fuzzy entropy satisfaction degree solving algorithm can simplify solving difficulty and get the optimum operation scheduling scheme.
Parametric Cost and Schedule Modeling for Early Technology Development
2018-04-02
Research NoteNational Security Rep rt PARAMETRIC MODELING FOR EARLY TECHNOLOGY DEVELOPMENT COST AND SCHEDULE Chuck...Alexander NSR_11x17_Cover_CostModeling_v8.indd 1 11/20/17 3:15 PM PARAMETRIC COST AND SCHEDULE MODELING FOR EARLY TECHNOLOGY DEVELOPMENT Chuck...COST AND SCHEDULE MODELING FOR EARLY TECHNOLOGY DEVELOPMENT iii Contents Figures
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)
Declarative Modeling for Production Order Portfolio Scheduling
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Banaszak Zbigniew
2014-12-01
Full Text Available A declarative framework enabling to determine conditions as well as to develop decision-making software supporting small- and medium-sized enterprises aimed at unique, multi-project-like and mass customized oriented production is discussed. A set of unique production orders grouped into portfolio orders is considered. Operations executed along different production orders share available resources following a mutual exclusion protocol. A unique product or production batch is completed while following a given activity’s network order. The problem concerns scheduling a newly inserted project portfolio subject to constraints imposed by a multi-project environment The answers sought are: Can a given project portfolio specified by its cost and completion time be completed within the assumed time period in a manufacturing system in hand? Which manufacturing system capability guarantees the completion of a given project portfolio ordered under assumed cost and time constraints? The considered problems regard finding a computationally effective approach aimed at simultaneous routing and allocation as well as batching and scheduling of a newly ordered project portfolio subject to constraints imposed by a multi-project environment. The main objective is to provide a declarative model enabling to state a constraint satisfaction problem aimed at multi-project-like and mass customized oriented production scheduling. Multiple illustrative examples are discussed.
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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.
A novel discrete PSO algorithm for solving job shop scheduling problem to minimize makespan
Rameshkumar, K.; Rajendran, C.
2018-02-01
In this work, a discrete version of PSO algorithm is proposed to minimize the makespan of a job-shop. A novel schedule builder has been utilized to generate active schedules. The discrete PSO is tested using well known benchmark problems available in the literature. The solution produced by the proposed algorithms is compared with best known solution published in the literature and also compared with hybrid particle swarm algorithm and variable neighborhood search PSO algorithm. The solution construction methodology adopted in this study is found to be effective in producing good quality solutions for the various benchmark job-shop scheduling problems.
Mathematical models for a batch scheduling problem to minimize earliness and tardiness
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Basar Ogun
2018-05-01
Full Text Available Purpose: Today’s manufacturing facilities are challenged by highly customized products and just in time manufacturing and delivery of these products. In this study, a batch scheduling problem is addressed to provide on-time completion of customer orders in the environment of lean manufacturing. The problem is to optimize partitioning of product components into batches and scheduling of the resulting batches where each customer order is received as a set of products made of various components. Design/methodology/approach: Three different mathematical models for minimization of total earliness and tardiness of customer orders are developed to provide on-time completion of customer orders and also, to avoid from inventory of final products. The first model is a non-linear integer programming model while the second is a linearized version of the first. Finally, to solve larger sized instances of the problem, an alternative linear integer model is presented. Findings: Computational study using a suit set of test instances showed that the alternative linear integer model is able to solve all test instances in varying sizes within quite shorter computer times comparing to the other two models. It was also showed that the alternative model can solve moderate sized real-world problems. Originality/value: The problem under study differentiates from existing batch scheduling problems in the literature since it includes new circumstances which may arise in real-world applications. This research, also, contributes the literature of batch scheduling problem by presenting new optimization models.
Solving a manpower scheduling problem for airline catering using tabu search
DEFF Research Database (Denmark)
Ho, Sin C.; Leung, Janny M. Y.
We study a manpower scheduling problem with job time-windows and job-skills compatibility constraints. This problem is motivated by airline catering operations, whereby airline meals and other supplies are delivered to aircrafts on the tarmac just before the flights take off. Jobs (flights) must...
A Column Generation Approach for Solving the Patient Admission Scheduling Problem
DEFF Research Database (Denmark)
Range, Troels Martin; Lusby, Richard Martin; Larsen, Jesper
This paper addresses the Patient Admission Scheduling (PAS) problem. The PAS problem deals with assigning elective patients to beds, satisfying a number of soft and hard constraints. The problem can be seen as part of the functions of hospital management at an operational level. There exists a sm...... to produce new best solutions for ve out of six instances from a publicly available repository....
Using the method of ideal point to solve dual-objective problem for production scheduling
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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
Li, Guo; Lv, Fei; Guan, Xu
2014-01-01
This paper investigates a collaborative scheduling model in the assembly system, wherein multiple suppliers have to deliver their components to the multiple manufacturers under the operation of Supply-Hub. We first develop two different scenarios to examine the impact of Supply-Hub. One is that suppliers and manufacturers make their decisions separately, and the other is that the Supply-Hub makes joint decisions with collaborative scheduling. The results show that our scheduling model with the Supply-Hub is a NP-complete problem, therefore, we propose an auto-adapted differential evolution algorithm to solve this problem. Moreover, we illustrate that the performance of collaborative scheduling by the Supply-Hub is superior to separate decision made by each manufacturer and supplier. Furthermore, we also show that the algorithm proposed has good convergence and reliability, which can be applicable to more complicated supply chain environment.
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Guo Li
2014-01-01
Full Text Available This paper investigates a collaborative scheduling model in the assembly system, wherein multiple suppliers have to deliver their components to the multiple manufacturers under the operation of Supply-Hub. We first develop two different scenarios to examine the impact of Supply-Hub. One is that suppliers and manufacturers make their decisions separately, and the other is that the Supply-Hub makes joint decisions with collaborative scheduling. The results show that our scheduling model with the Supply-Hub is a NP-complete problem, therefore, we propose an auto-adapted differential evolution algorithm to solve this problem. Moreover, we illustrate that the performance of collaborative scheduling by the Supply-Hub is superior to separate decision made by each manufacturer and supplier. Furthermore, we also show that the algorithm proposed has good convergence and reliability, which can be applicable to more complicated supply chain environment.
Lv, Fei; Guan, Xu
2014-01-01
This paper investigates a collaborative scheduling model in the assembly system, wherein multiple suppliers have to deliver their components to the multiple manufacturers under the operation of Supply-Hub. We first develop two different scenarios to examine the impact of Supply-Hub. One is that suppliers and manufacturers make their decisions separately, and the other is that the Supply-Hub makes joint decisions with collaborative scheduling. The results show that our scheduling model with the Supply-Hub is a NP-complete problem, therefore, we propose an auto-adapted differential evolution algorithm to solve this problem. Moreover, we illustrate that the performance of collaborative scheduling by the Supply-Hub is superior to separate decision made by each manufacturer and supplier. Furthermore, we also show that the algorithm proposed has good convergence and reliability, which can be applicable to more complicated supply chain environment. PMID:24892104
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Laxmi A. Bewoor
2017-10-01
Full Text Available The no-wait flow shop is a flowshop in which the scheduling of jobs is continuous and simultaneous through all machines without waiting for any consecutive machines. The scheduling of a no-wait flow shop requires finding an appropriate sequence of jobs for scheduling, which in turn reduces total processing time. The classical brute force method for finding the probabilities of scheduling for improving the utilization of resources may become trapped in local optima, and this problem can hence be observed as a typical NP-hard combinatorial optimization problem that requires finding a near optimal solution with heuristic and metaheuristic techniques. This paper proposes an effective hybrid Particle Swarm Optimization (PSO metaheuristic algorithm for solving no-wait flow shop scheduling problems with the objective of minimizing the total flow time of jobs. This Proposed Hybrid Particle Swarm Optimization (PHPSO algorithm presents a solution by the random key representation rule for converting the continuous position information values of particles to a discrete job permutation. The proposed algorithm initializes population efficiently with the Nawaz-Enscore-Ham (NEH heuristic technique and uses an evolutionary search guided by the mechanism of PSO, as well as simulated annealing based on a local neighborhood search to avoid getting stuck in local optima and to provide the appropriate balance of global exploration and local exploitation. Extensive computational experiments are carried out based on Taillard’s benchmark suite. Computational results and comparisons with existing metaheuristics show that the PHPSO algorithm outperforms the existing methods in terms of quality search and robustness for the problem considered. The improvement in solution quality is confirmed by statistical tests of significance.
Crane scheduling for a plate storage in a shipyard: Solving the problem
DEFF Research Database (Denmark)
Hansen, Jesper; Kristensen, Torben F.H.
2003-01-01
. These blocks are again welded together in the dock to produce a ship. Two gantry cranes move the plates into, around and out of the storage when needed in production. Different principles for organizing the storage and also different approaches for solving the problem are compared. Our results indicate...
A Gas Scheduling Optimization Model for Steel Enterprises
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Niu Honghai
2017-01-01
Full Text Available Regarding the scheduling problems of steel enterprises, this research designs the gas scheduling optimization model according to the rules and priorities. Considering different features and the process changes of the gas unit in the process of actual production, the calculation model of process state and gas consumption soft measurement together with the rules of scheduling optimization is proposed to provide the dispatchers with real-time gas using status of each process, then help them to timely schedule and reduce the gas volume fluctuations. In the meantime, operation forewarning and alarm functions are provided to avoid the abnormal situation in the scheduling, which has brought about very good application effect in the actual scheduling and ensures the safety of the gas pipe network system and the production stability.
A column generation approach for solving the patient admission scheduling problem
DEFF Research Database (Denmark)
Range, Troels Martin; Lusby, Richard Martin; Larsen, Jesper
2014-01-01
, different variants of this problem. In this paper we consider one such variant and propose an optimization-based heuristic building on branch-and-bound, column generation, and dynamic constraint aggregation to solve it. We achieve tighter lower bounds than previously reported in the literature and......, in addition, we are able to produce new best known solutions for five out of twelve instances from a publicly available repository. © 2013 Elsevier B.V. All rights reserved....
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Imen Chaieb Memmi
2013-09-01
Full Text Available Purpose: We aim to examine the capacitated multi-item lot sizing problem which is a typical example of a large bucket model, where many different items can be produced on the same machine in one time period. We propose a new approach to determine the production sequence and lot sizes that minimize the sum of start up and setup costs, inventory and production costs over all periods.Design/methodology/approach: The approach is composed of three steps. First, we compute a lower bound on total cost. Then we propose a three sub-steps iteration procedure. We solve optimally the lot sizing problem without considering products sequencing and their cost. Then, we determine products quantities to produce each period while minimizing the storage and variable production costs. Given the products to manufacture each period, we determine its correspondent optimal products sequencing, by using a Branch and Bound algorithm. Given the sequences of products within each period, we evaluate the total start up and setup cost. We compare then the total cost obtained to the lower bound of the total cost. If this value riches a prefixed value, we stop. Otherwise, we modify the results of lot sizing problem.Findings and Originality/value: We show using an illustrative example, that the difference between the total cost and its lower bound is only 10%. This gap depends on the significance of the inventory and production costs and the machine’s capacity. Comparing the approach we develop with a traditional one, we show that we manage to reduce the total cost by 30%.Research limitations/implications: Our model fits better to real-world situations where production systems run continuously. This model is applied for limited number of part types and periods.Practical implications: Our approach determines the products to manufacture each time period, their economic amounts, and their scheduling within each period. This outcome should help decision makers bearing expensive
Schedulability of Herschel revisited using statistical model checking
DEFF Research Database (Denmark)
David, Alexandre; Larsen, Kim Guldstrand; Legay, Axel
2015-01-01
-approximation technique. We can safely conclude that the system is schedulable for varying values of BCET. For the cases where deadlines are violated, we use polyhedra to try to confirm the witnesses. Our alternative method to confirm non-schedulability uses statistical model-checking (SMC) to generate counter...... and blocking times of tasks. Consequently, the method may falsely declare deadline violations that will never occur during execution. This paper is a continuation of previous work of the authors in applying extended timed automata model checking (using the tool UPPAAL) to obtain more exact schedulability...... analysis, here in the presence of non-deterministic computation times of tasks given by intervals [BCET,WCET]. Computation intervals with preemptive schedulers make the schedulability analysis of the resulting task model undecidable. Our contribution is to propose a combination of model checking techniques...
A model for solving the prescribed burn planning problem.
Rachmawati, Ramya; Ozlen, Melih; Reinke, Karin J; Hearne, John W
2015-01-01
The increasing frequency of destructive wildfires, with a consequent loss of life and property, has led to fire and land management agencies initiating extensive fuel management programs. This involves long-term planning of fuel reduction activities such as prescribed burning or mechanical clearing. In this paper, we propose a mixed integer programming (MIP) model that determines when and where fuel reduction activities should take place. The model takes into account multiple vegetation types in the landscape, their tolerance to frequency of fire events, and keeps track of the age of each vegetation class in each treatment unit. The objective is to minimise fuel load over the planning horizon. The complexity of scheduling fuel reduction activities has led to the introduction of sophisticated mathematical optimisation methods. While these approaches can provide optimum solutions, they can be computationally expensive, particularly for fuel management planning which extends across the landscape and spans long term planning horizons. This raises the question of how much better do exact modelling approaches compare to simpler heuristic approaches in their solutions. To answer this question, the proposed model is run using an exact MIP (using commercial MIP solver) and two heuristic approaches that decompose the problem into multiple single-period sub problems. The Knapsack Problem (KP), which is the first heuristic approach, solves the single period problems, using an exact MIP approach. The second heuristic approach solves the single period sub problem using a greedy heuristic approach. The three methods are compared in term of model tractability, computational time and the objective values. The model was tested using randomised data from 711 treatment units in the Barwon-Otway district of Victoria, Australia. Solutions for the exact MIP could be obtained for up to a 15-year planning only using a standard implementation of CPLEX. Both heuristic approaches can solve
An imperialist competitive algorithm for solving the production scheduling problem in open pit mine
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Mojtaba Mokhtarian Asl
2016-06-01
Full Text Available Production scheduling (planning of an open-pit mine is the procedure during which the rock blocks are assigned to different production periods in a way that the highest net present value of the project achieved subject to operational constraints. The paper introduces a new and computationally less expensive meta-heuristic technique known as imperialist competitive algorithm (ICA for long-term production planning of open pit mines. The proposed algorithm modifies the original rules of the assimilation process. The ICA performance for different levels of the control factors has been studied and the results are presented. The result showed that ICA could be efficiently applied on mine production planning problem.
DEFF Research Database (Denmark)
Mirzaei, Mahmood; Poulsen, Niels Kjølstad; Niemann, Hans Henrik
2012-01-01
Robust model predictive control (RMPC) of a class of nonlinear systems is considered in this paper. We will use Linear Parameter Varying (LPV) model of the nonlinear system. By taking the advantage of having future values of the scheduling variable, we will simplify state prediction. Because...... of the special structure of the problem, uncertainty is only in the B matrix (gain) of the state space model. Therefore by taking advantage of this structure, we formulate a tractable minimax optimization problem to solve robust model predictive control problem. Wind turbine is chosen as the case study and we...... choose wind speed as the scheduling variable. Wind speed is measurable ahead of the turbine, therefore the scheduling variable is known for the entire prediction horizon....
Cram, Ana Catalina
As worldwide environmental awareness grow, alternative sources of energy have become important to mitigate climate change. Biogas in particular reduces greenhouse gas emissions that contribute to global warming and has the potential of providing 25% of the annual demand for natural gas in the U.S. In 2011, 55,000 metric tons of methane emissions were reduced and 301 metric tons of carbon dioxide emissions were avoided through the use of biogas alone. Biogas is produced by anaerobic digestion through the fermentation of organic material. It is mainly composed of methane with a rage of 50 to 80% in its concentration. Carbon dioxide covers 20 to 50% and small amounts of hydrogen, carbon monoxide and nitrogen. The biogas production systems are anaerobic digestion facilities and the optimal operation of an anaerobic digester requires the scheduling of all batches from multiple feedstocks during a specific time horizon. The availability times, biomass quantities, biogas production rates and storage decay rates must all be taken into account for maximal biogas production to be achieved during the planning horizon. Little work has been done to optimize the scheduling of different types of feedstock in anaerobic digestion facilities to maximize the total biogas produced by these systems. Therefore, in the present thesis, a new genetic algorithm is developed with the main objective of obtaining the optimal sequence in which different feedstocks will be processed and the optimal time to allocate to each feedstock in the digester with the main objective of maximizing the production of biogas considering different types of feedstocks, arrival times and decay rates. Moreover, all batches need to be processed in the digester in a specified time with the restriction that only one batch can be processed at a time. The developed algorithm is applied to 3 different examples and a comparison with results obtained in previous studies is presented.
Aeon: Synthesizing Scheduling Algorithms from High-Level Models
Monette, Jean-Noël; Deville, Yves; van Hentenryck, Pascal
This paper describes the aeon system whose aim is to synthesize scheduling algorithms from high-level models. A eon, which is entirely written in comet, receives as input a high-level model for a scheduling application which is then analyzed to generate a dedicated scheduling algorithm exploiting the structure of the model. A eon provides a variety of synthesizers for generating complete or heuristic algorithms. Moreover, synthesizers are compositional, making it possible to generate complex hybrid algorithms naturally. Preliminary experimental results indicate that this approach may be competitive with state-of-the-art search algorithms.
A descriptive model of information problem solving while using internet
Brand-Gruwel, Saskia; Wopereis, Iwan; Walraven, Amber
2009-01-01
This paper presents the IPS-I-model: a model that describes the process of information problem solving (IPS) in which the Internet (I) is used to search information. The IPS-I-model is based on three studies, in which students in secondary and (post) higher education were asked to solve information
Model Justified Search Algorithms for Scheduling Under Uncertainty
National Research Council Canada - National Science Library
Howe, Adele; Whitley, L. D
2008-01-01
.... We also identified plateaus as a significant barrier to superb performance of local search on scheduling and have studied several canonical discrete optimization problems to discover and model the nature of plateaus...
Scheduling models in farm management : a new approach
Wijngaard, P.J.M.
1988-01-01
Three operational planning models to calculate schedules for an arable farm are examined. These models are a linear programming model, a dynamic programming model and a simulation model. They are examined at different levels of aggregation and relaxation in a retrospective way. Also a
Discrete Optimization Model for Vehicle Routing Problem with Scheduling Side Cosntraints
Juliandri, Dedy; Mawengkang, Herman; Bu'ulolo, F.
2018-01-01
Vehicle Routing Problem (VRP) is an important element of many logistic systems which involve routing and scheduling of vehicles from a depot to a set of customers node. This is a hard combinatorial optimization problem with the objective to find an optimal set of routes used by a fleet of vehicles to serve the demands a set of customers It is required that these vehicles return to the depot after serving customers’ demand. The problem incorporates time windows, fleet and driver scheduling, pick-up and delivery in the planning horizon. The goal is to determine the scheduling of fleet and driver and routing policies of the vehicles. The objective is to minimize the overall costs of all routes over the planning horizon. We model the problem as a linear mixed integer program. We develop a combination of heuristics and exact method for solving the model.
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.
Directory of Open Access Journals (Sweden)
Wallace Agyei
2015-03-01
Full Text Available Abstract The problem of scheduling nurses at the Out-Patient Department OPD at Tafo Government Hospital Kumasi Ghana is presented. Currently the schedules are prepared by head nurse who performs this difficult and time consuming task by hand. Due to the existence of many constraints the resulting schedule usually does not guarantee the fairness of distribution of work. The problem was formulated as 0-1goal programming model with the of objective of evenly balancing the workload among nurses and satisfying their preferences as much as possible while complying with the legal and working regulations.. The developed model was then solved using LINGO14.0 software. The resulting schedules based on 0-1goal programming model balanced the workload in terms of the distribution of shift duties fairness in terms of the number of consecutive night duties and satisfied the preferences of the nurses. This is an improvement over the schedules done manually.
Effectiveness of discovery learning model on mathematical problem solving
Herdiana, Yunita; Wahyudin, Sispiyati, Ririn
2017-08-01
This research is aimed to describe the effectiveness of discovery learning model on mathematical problem solving. This research investigate the students' problem solving competency before and after learned by using discovery learning model. The population used in this research was student in grade VII in one of junior high school in West Bandung Regency. From nine classes, class VII B were randomly selected as the sample of experiment class, and class VII C as control class, which consist of 35 students every class. The method in this research was quasi experiment. The instrument in this research is pre-test, worksheet and post-test about problem solving of mathematics. Based on the research, it can be conclude that the qualification of problem solving competency of students who gets discovery learning model on level 80%, including in medium category and it show that discovery learning model effective to improve mathematical problem solving.
Modeling and Solving the Train Pathing Problem
Directory of Open Access Journals (Sweden)
Chuen-Yih Chen
2009-04-01
Full Text Available In a railroad system, train pathing is concerned with the assignment of trains to links and tracks, and train timetabling allocates time slots to trains. In this paper, we present an optimization heuristic to solve the train pathing and timetabling problem. This heuristic allows the dwell time of trains in a station or link to be dependent on the assigned tracks. It also allows the minimum clearance time between the trains to depend on their relative status. The heuristic generates a number of alternative paths for each train service in the initialization phase. Then it uses a neighborhood search approach to find good feasible combinations of these paths. A linear program is developed to evaluate the quality of each combination that is encountered. Numerical examples are provided.
Pei, Jun; Liu, Xinbao; Pardalos, Panos M.; Fan, Wenjuan; Wang, Ling; Yang, Shanlin
2016-03-01
Motivated by applications in manufacturing industry, we consider a supply chain scheduling problem, where each job is characterised by non-identical sizes, different release times and unequal processing times. The objective is to minimise the makespan by making batching and sequencing decisions. The problem is formalised as a mixed integer programming model and proved to be strongly NP-hard. Some structural properties are presented for both the general case and a special case. Based on these properties, a lower bound is derived, and a novel two-phase heuristic (TP-H) is developed to solve the problem, which guarantees to obtain a worst case performance ratio of ?. Computational experiments with a set of different sizes of random instances are conducted to evaluate the proposed approach TP-H, which is superior to another two heuristics proposed in the literature. Furthermore, the experimental results indicate that TP-H can effectively and efficiently solve large-size problems in a reasonable time.
A Modeling Framework for Schedulability Analysis of Distributed Avionics Systems
DEFF Research Database (Denmark)
Han, Pujie; Zhai, Zhengjun; Nielsen, Brian
2018-01-01
This paper presents a modeling framework for schedulability analysis of distributed integrated modular avionics (DIMA) systems that consist of spatially distributed ARINC-653 modules connected by a unified AFDX network. We model a DIMA system as a set of stopwatch automata (SWA) in UPPAAL...
Parallel-Batch Scheduling with Two Models of Deterioration to Minimize the Makespan
Directory of Open Access Journals (Sweden)
Cuixia Miao
2014-01-01
Full Text Available We consider the bounded parallel-batch scheduling with two models of deterioration, in which the processing time of the first model is pj=aj+αt and of the second model is pj=a+αjt. The objective is to minimize the makespan. We present O(n log n time algorithms for the single-machine problems, respectively. And we propose fully polynomial time approximation schemes to solve the identical-parallel-machine problem and uniform-parallel-machine problem, respectively.
Spreadsheet-Enhanced Problem Solving in Context as Modeling
Directory of Open Access Journals (Sweden)
Sergei Abramovich
2003-07-01
development through situated mathematical problem solving. Modeling activities described in this paper support the epistemological position regarding the interplay that exists between the development of mathematical concepts and available methods of calculation. The spreadsheet used is Microsoft Excel 2001
A Probabilistic Model for Uncertain Problem Solving
National Research Council Canada - National Science Library
Farley, Arthur M
1981-01-01
... and provide pragmatic focusing. Search methods are generalized to produce tree-structured plans incorporating the use of such operators. Several application domains for the model also are discussed.
Collaborative problem solving with a total quality model.
Volden, C M; Monnig, R
1993-01-01
A collaborative problem-solving system committed to the interests of those involved complies with the teachings of the total quality management movement in health care. Deming espoused that any quality system must become an integral part of routine activities. A process that is used consistently in dealing with problems, issues, or conflicts provides a mechanism for accomplishing total quality improvement. The collaborative problem-solving process described here results in quality decision-making. This model incorporates Ishikawa's cause-and-effect (fishbone) diagram, Moore's key causes of conflict, and the steps of the University of North Dakota Conflict Resolution Center's collaborative problem solving model.
Simulation models generator. Applications in scheduling
Directory of Open Access Journals (Sweden)
Omar Danilo Castrillón
2013-08-01
Rev.Mate.Teor.Aplic. (ISSN 1409-2433 Vol. 20(2: 231–241, July 2013 generador de modelos de simulacion 233 will, in order to have an approach to reality to evaluate decisions in order to take more assertive. To test prototype was used as the modeling example of a production system with 9 machines and 5 works as a job shop configuration, testing stops processing times and stochastic machine to measure rates of use of machines and time average jobs in the system, as measures of system performance. This test shows the goodness of the prototype, to save the user the simulation model building
Solving the flexible job shop problem by hybrid metaheuristics-based multiagent model
Nouri, Houssem Eddine; Belkahla Driss, Olfa; Ghédira, Khaled
2018-03-01
The flexible job shop scheduling problem (FJSP) is a generalization of the classical job shop scheduling problem that allows to process operations on one machine out of a set of alternative machines. The FJSP is an NP-hard problem consisting of two sub-problems, which are the assignment and the scheduling problems. In this paper, we propose how to solve the FJSP by hybrid metaheuristics-based clustered holonic multiagent model. First, a neighborhood-based genetic algorithm (NGA) is applied by a scheduler agent for a global exploration of the search space. Second, a local search technique is used by a set of cluster agents to guide the research in promising regions of the search space and to improve the quality of the NGA final population. The efficiency of our approach is explained by the flexible selection of the promising parts of the search space by the clustering operator after the genetic algorithm process, and by applying the intensification technique of the tabu search allowing to restart the search from a set of elite solutions to attain new dominant scheduling solutions. Computational results are presented using four sets of well-known benchmark literature instances. New upper bounds are found, showing the effectiveness of the presented approach.
Modeling crowdsourcing as collective problem solving
Guazzini, Andrea; Vilone, Daniele; Donati, Camillo; Nardi, Annalisa; Levnajić, Zoran
2015-11-01
Crowdsourcing is a process of accumulating the ideas, thoughts or information from many independent participants, with aim to find the best solution for a given challenge. Modern information technologies allow for massive number of subjects to be involved in a more or less spontaneous way. Still, the full potentials of crowdsourcing are yet to be reached. We introduce a modeling framework through which we study the effectiveness of crowdsourcing in relation to the level of collectivism in facing the problem. Our findings reveal an intricate relationship between the number of participants and the difficulty of the problem, indicating the optimal size of the crowdsourced group. We discuss our results in the context of modern utilization of crowdsourcing.
A stochastic model for forecast consumption in master scheduling
Weeda, P.J.; Weeda, P.J.
1994-01-01
This paper describes a stochastic model for the reduction of the initial forecast in the Master Schedule (MS) of an MRP system during progress of time by the acceptance of customer orders. Results are given for the expectation and variance of the number of yet unknown deliveries as a function of
Analysis and Enhancement of IEEE 802.15.4e DSME Beacon Scheduling Model
Directory of Open Access Journals (Sweden)
Kwang-il Hwang
2014-01-01
Full Text Available In order to construct a successful Internet of things (IoT, reliable network construction and maintenance in a sensor domain should be supported. However, IEEE 802.15.4, which is the most representative wireless standard for IoT, still has problems in constructing a large-scale sensor network, such as beacon collision. To overcome some problems in IEEE 802.15.4, the 15.4e task group proposed various different modes of operation. Particularly, the IEEE 802.15.4e deterministic and synchronous multichannel extension (DSME mode presents a novel scheduling model to solve beacon collision problems. However, the DSME model specified in the 15.4e draft does not present a concrete design model but a conceptual abstract model. Therefore, in this paper we introduce a DSME beacon scheduling model and present a concrete design model. Furthermore, validity and performance of DSME are evaluated through experiments. Based on experiment results, we analyze the problems and limitations of DSME, present solutions step by step, and finally propose an enhanced DSME beacon scheduling model. Through additional experiments, we prove the performance superiority of enhanced DSME.
Routing and Scheduling Optimization Model of Sea Transportation
barus, Mika debora br; asyrafy, Habib; nababan, Esther; mawengkang, Herman
2018-01-01
This paper examines the routing and scheduling optimization model of sea transportation. One of the issues discussed is about the transportation of ships carrying crude oil (tankers) which is distributed to many islands. The consideration is the cost of transportation which consists of travel costs and the cost of layover at the port. Crude oil to be distributed consists of several types. This paper develops routing and scheduling model taking into consideration some objective functions and constraints. The formulation of the mathematical model analyzed is to minimize costs based on the total distance visited by the tanker and minimize the cost of the ports. In order for the model of the problem to be more realistic and the cost calculated to be more appropriate then added a parameter that states the multiplier factor of cost increases as the charge of crude oil is filled.
Seol, Ye-In; Kim, Young-Kuk
2014-01-01
Power-aware scheduling reduces CPU energy consumption in hard real-time systems through dynamic voltage scaling (DVS). In this paper, we deal with pinwheel task model which is known as static and predictable task model and could be applied to various embedded or ubiquitous systems. In pinwheel task model, each task's priority is static and its execution sequence could be predetermined. There have been many static approaches to power-aware scheduling in pinwheel task model. But, in this paper, we will show that the dynamic priority scheduling results in power-aware scheduling could be applied to pinwheel task model. This method is more effective than adopting the previous static priority scheduling methods in saving energy consumption and, for the system being still static, it is more tractable and applicable to small sized embedded or ubiquitous computing. Also, we introduce a novel power-aware scheduling algorithm which exploits all slacks under preemptive earliest-deadline first scheduling which is optimal in uniprocessor system. The dynamic priority method presented in this paper could be applied directly to static systems of pinwheel task model. The simulation results show that the proposed algorithm with the algorithmic complexity of O(n) reduces the energy consumption by 10-80% over the existing algorithms.
An ontological framework for model-based problem-solving
Scholten, H.; Beulens, A.J.M.
2012-01-01
Multidisciplinary projects to solve real world problems of increasing complexity are more and more plagued by obstacles such as miscommunication between modellers with different disciplinary backgrounds and bad modelling practices. To tackle these difficulties, a body of knowledge on problems, on
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.
Decision Model for Planning and Scheduling of Seafood Product Considering Traceability
Agustin; Mawengkang, Herman; Mathelinea, Devy
2018-01-01
Due to the global challenges, it is necessary for an industrial company to integrate production scheduling and distribution planning, in order to be more efficient and to get more economics advantages. This paper presents seafood production planning and scheduling of a seafood manufacture company which produces simultaneously multi kind of seafood products, located at Aceh Province, Indonesia. The perishability nature of fish highly restricts its storage duration and delivery conditions. Traceability is a tracking requirement to check whether the quality of the product is satisfied. The production and distribution planning problem aims to meet customer demand subject to traceability of the seafood product and other restrictions. The problem is modeled as a mixed integer linear program, and then it is solved using neighborhood search approach.
Rapine , Christophe
2013-01-01
International audience; In Allaoui H., Artiba A, ''Johnson's algorithm : A key to solve optimally or approximately flowshop scheduling problems with unavailability periods'' [International Journal of Production Economics 121 (2009)] the authors propose optimality conditions for the Johnson sequence in presence of one unavailability period on the first machine and pretend for a performance guarantee of 2 when several unavailability periods may occur. We establish in this note that these condit...
Constraint-based scheduling applying constraint programming to scheduling problems
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...
Workforce scheduling: A new model incorporating human factors
Directory of Open Access Journals (Sweden)
Mohammed Othman
2012-12-01
Full Text Available Purpose: The majority of a company’s improvement comes when the right workers with the right skills, behaviors and capacities are deployed appropriately throughout a company. This paper considers a workforce scheduling model including human aspects such as skills, training, workers’ personalities, workers’ breaks and workers’ fatigue and recovery levels. This model helps to minimize the hiring, firing, training and overtime costs, minimize the number of fired workers with high performance, minimize the break time and minimize the average worker’s fatigue level.Design/methodology/approach: To achieve this objective, a multi objective mixed integer programming model is developed to determine the amount of hiring, firing, training and overtime for each worker type.Findings: The results indicate that the worker differences should be considered in workforce scheduling to generate realistic plans with minimum costs. This paper also investigates the effects of human fatigue and recovery on the performance of the production systems.Research limitations/implications: In this research, there are some assumptions that might affect the accuracy of the model such as the assumption of certainty of the demand in each period, and the linearity function of Fatigue accumulation and recovery curves. These assumptions can be relaxed in future work.Originality/value: In this research, a new model for integrating workers’ differences with workforce scheduling is proposed. To the authors' knowledge, it is the first time to study the effects of different important human factors such as human personality, skills and fatigue and recovery in the workforce scheduling process. This research shows that considering both technical and human factors together can reduce the costs in manufacturing systems and ensure the safety of the workers.
A multi-criteria model for maintenance job scheduling
Directory of Open Access Journals (Sweden)
Sunday A. Oke
2007-12-01
Full Text Available This paper presents a multi-criteria maintenance job scheduling model, which is formulated using a weighted multi-criteria integer linear programming maintenance scheduling framework. Three criteria, which have direct relationship with the primary objectives of a typical production setting, were used. These criteria are namely minimization of equipment idle time, manpower idle time and lateness of job with unit parity. The mathematical model constrained by available equipment, manpower and job available time within planning horizon was tested with a 10-job, 8-hour time horizon problem with declared equipment and manpower available as against the required. The results, analysis and illustrations justify multi-criteria consideration. Thus, maintenance managers are equipped with a tool for adequate decision making that guides against error in the accumulated data which may lead to wrong decision making. The idea presented is new since it provides an approach that has not been documented previously in the literature.
Short-term generation scheduling model of Fujian hydro system
Energy Technology Data Exchange (ETDEWEB)
Wang Jinwen [School of Hydropower and Information Engineering, Huazhong University of Science and Technology, Wuhan 430074 (China)], E-mail: dr.jinwen.wang@gmail.com
2009-04-15
The Fujian hydropower system (FHS) is one of the provincial hydropower systems with the most complicated hydraulic topology in China. This paper describes an optimization program that is required by Fujian Electric Power Company Ltd. (FEPCL) to aid the shift engineers in making decisions with the short-term hydropower scheduling such that the generation benefit can be maximal. The problem involves 27 reservoirs and is formulated as a nonlinear and discrete programming. It is a very challenging task to solve such a large-scale problem. In this paper, the Lagrangian multipliers are introduced to decompose the primal problem into a hydro subproblem and many individual plant-based subproblems, which are respectively solved by the improved simplex-like method (SLM) and the dynamic programming (DP). A numerical example is given and the derived solution is very close to the optimal one, with the distance in benefit less than 0.004%. All the data needed for the numerical example are presented in detail for further tests and studies from more experts and researchers.
Short-term generation scheduling model of Fujian hydro system
Energy Technology Data Exchange (ETDEWEB)
Wang, Jinwen [School of Hydropower and Information Engineering, Huazhong University of Science and Technology, Wuhan 430074 (China)
2009-04-15
The Fujian hydropower system (FHS) is one of the provincial hydropower systems with the most complicated hydraulic topology in China. This paper describes an optimization program that is required by Fujian Electric Power Company Ltd. (FEPCL) to aid the shift engineers in making decisions with the short-term hydropower scheduling such that the generation benefit can be maximal. The problem involves 27 reservoirs and is formulated as a nonlinear and discrete programming. It is a very challenging task to solve such a large-scale problem. In this paper, the Lagrangian multipliers are introduced to decompose the primal problem into a hydro subproblem and many individual plant-based subproblems, which are respectively solved by the improved simplex-like method (SLM) and the dynamic programming (DP). A numerical example is given and the derived solution is very close to the optimal one, with the distance in benefit less than 0.004%. All the data needed for the numerical example are presented in detail for further tests and studies from more experts and researchers. (author)
Directory of Open Access Journals (Sweden)
Yu Zhang
2014-01-01
Full Text Available We consider an ad hoc Floyd-A∗ algorithm to determine the a priori least-time itinerary from an origin to a destination given an initial time in an urban scheduled public transport (USPT network. The network is bimodal (i.e., USPT lines and walking and time dependent. The modified USPT network model results in more reasonable itinerary results. An itinerary is connected through a sequence of time-label arcs. The proposed Floyd-A∗ algorithm is composed of two procedures designated as Itinerary Finder and Cost Estimator. The A∗-based Itinerary Finder determines the time-dependent, least-time itinerary in real time, aided by the heuristic information precomputed by the Floyd-based Cost Estimator, where a strategy is formed to preestimate the time-dependent arc travel time as an associated static lower bound. The Floyd-A∗ algorithm is proven to guarantee optimality in theory and, demonstrated through a real-world example in Shenyang City USPT network to be more efficient than previous procedures. The computational experiments also reveal the time-dependent nature of the least-time itinerary. In the premise that lines run punctually, “just boarding” and “just missing” cases are identified.
A Decomposition-Based Pricing Method for Solving a Large-Scale MILP Model for an Integrated Fishery
Directory of Open Access Journals (Sweden)
M. Babul Hasan
2007-01-01
The IFP can be decomposed into a trawler-scheduling subproblem and a fish-processing subproblem in two different ways by relaxing different sets of constraints. We tried conventional decomposition techniques including subgradient optimization and Dantzig-Wolfe decomposition, both of which were unacceptably slow. We then developed a decomposition-based pricing method for solving the large fishery model, which gives excellent computation times. Numerical results for several planning horizon models are presented.
Anger in Middle School: The Solving Problems Together Model
Hall, Kimberly R.; Rushing, Jeri L.; Owens, Rachel B.
2009-01-01
Problem-focused interventions are considered to be one of the most effective group counseling strategies with adolescents. This article describes a problem-focused group counseling model, Solving Problems Together (SPT), with a small group of adolescent African American boys struggling with anger management. Adapted from the teaching philosophy of…
A Problem-Solving Model for Literacy Coaching Practice
Toll, Cathy A.
2017-01-01
Literacy coaches are more effective when they have a clear plan for their collaborations with teachers. This article provides details of such a plan, which involves identifying a problem, understanding the problem, deciding what to do differently, and trying something different. For each phase of the problem-solving model, there are key tasks for…
Multiresolution Network Temporal and Spatial Scheduling Model of Scenic Spot
Directory of Open Access Journals (Sweden)
Peng Ge
2013-01-01
Full Text Available Tourism is one of pillar industries of the world economy. Low-carbon tourism will be the mainstream direction of the scenic spots' development, and the ω path of low-carbon tourism development is to develop economy and protect environment simultaneously. However, as the tourists' quantity is increasing, the loads of scenic spots are out of control. And the instantaneous overload in some spots caused the image phenomenon of full capacity of the whole scenic spot. Therefore, realizing the real-time schedule becomes the primary purpose of scenic spot’s management. This paper divides the tourism distribution system into several logically related subsystems and constructs a temporal and spatial multiresolution network scheduling model according to the regularity of scenic spots’ overload phenomenon in time and space. It also defines dynamic distribution probability and equivalent dynamic demand to realize the real-time prediction. We define gravitational function between fields and takes it as the utility of schedule, after resolving the transportation model of each resolution, it achieves hierarchical balance between demand and capacity of the system. The last part of the paper analyzes the time complexity of constructing a multiresolution distribution system.
van Oostrum, J.M.; van Houdenhoven, M.; Hurink, Johann L.; Hans, Elias W.; Wullink, Gerhard; Kazemier, G.
2005-01-01
This paper addresses the problem of operating room scheduling at the tactical level of hospital planning and control. Hospitals repetitively construct operating room schedules, which is a time consuming tedious and complex task. The stochasticity of the durations of surgical procedures complicates
Guidance for modeling causes and effects in environmental problem solving
Armour, Carl L.; Williamson, Samuel C.
1988-01-01
Environmental problems are difficult to solve because their causes and effects are not easily understood. When attempts are made to analyze causes and effects, the principal challenge is organization of information into a framework that is logical, technically defensible, and easy to understand and communicate. When decisionmakers attempt to solve complex problems before an adequate cause and effect analysis is performed there are serious risks. These risks include: greater reliance on subjective reasoning, lessened chance for scoping an effective problem solving approach, impaired recognition of the need for supplemental information to attain understanding, increased chance for making unsound decisions, and lessened chance for gaining approval and financial support for a program/ Cause and effect relationships can be modeled. This type of modeling has been applied to various environmental problems, including cumulative impact assessment (Dames and Moore 1981; Meehan and Weber 1985; Williamson et al. 1987; Raley et al. 1988) and evaluation of effects of quarrying (Sheate 1986). This guidance for field users was written because of the current interest in documenting cause-effect logic as a part of ecological problem solving. Principal literature sources relating to the modeling approach are: Riggs and Inouye (1975a, b), Erickson (1981), and United States Office of Personnel Management (1986).
A genetic algorithm for solving supply chain network design model
Firoozi, Z.; Ismail, N.; Ariafar, S. H.; Tang, S. H.; Ariffin, M. K. M. A.
2013-09-01
Network design is by nature costly and optimization models play significant role in reducing the unnecessary cost components of a distribution network. This study proposes a genetic algorithm to solve a distribution network design model. The structure of the chromosome in the proposed algorithm is defined in a novel way that in addition to producing feasible solutions, it also reduces the computational complexity of the algorithm. Computational results are presented to show the algorithm performance.
Solving large mixed linear models using preconditioned conjugate gradient iteration.
Strandén, I; Lidauer, M
1999-12-01
Continuous evaluation of dairy cattle with a random regression test-day model requires a fast solving method and algorithm. A new computing technique feasible in Jacobi and conjugate gradient based iterative methods using iteration on data is presented. In the new computing technique, the calculations in multiplication of a vector by a matrix were recorded to three steps instead of the commonly used two steps. The three-step method was implemented in a general mixed linear model program that used preconditioned conjugate gradient iteration. Performance of this program in comparison to other general solving programs was assessed via estimation of breeding values using univariate, multivariate, and random regression test-day models. Central processing unit time per iteration with the new three-step technique was, at best, one-third that needed with the old technique. Performance was best with the test-day model, which was the largest and most complex model used. The new program did well in comparison to other general software. Programs keeping the mixed model equations in random access memory required at least 20 and 435% more time to solve the univariate and multivariate animal models, respectively. Computations of the second best iteration on data took approximately three and five times longer for the animal and test-day models, respectively, than did the new program. Good performance was due to fast computing time per iteration and quick convergence to the final solutions. Use of preconditioned conjugate gradient based methods in solving large breeding value problems is supported by our findings.
Jafari, Hamed; Salmasi, Nasser
2015-09-01
The nurse scheduling problem (NSP) has received a great amount of attention in recent years. In the NSP, the goal is to assign shifts to the nurses in order to satisfy the hospital's demand during the planning horizon by considering different objective functions. In this research, we focus on maximizing the nurses' preferences for working shifts and weekends off by considering several important factors such as hospital's policies, labor laws, governmental regulations, and the status of nurses at the end of the previous planning horizon in one of the largest hospitals in Iran i.e., Milad Hospital. Due to the shortage of available nurses, at first, the minimum total number of required nurses is determined. Then, a mathematical programming model is proposed to solve the problem optimally. Since the proposed research problem is NP-hard, a meta-heuristic algorithm based on simulated annealing (SA) is applied to heuristically solve the problem in a reasonable time. An initial feasible solution generator and several novel neighborhood structures are applied to enhance performance of the SA algorithm. Inspired from our observations in Milad hospital, random test problems are generated to evaluate the performance of the SA algorithm. The results of computational experiments indicate that the applied SA algorithm provides solutions with average percentage gap of 5.49 % compared to the upper bounds obtained from the mathematical model. Moreover, the applied SA algorithm provides significantly better solutions in a reasonable time than the schedules provided by the head nurses.
A bi-objective integer programming model for partly-restricted flight departure scheduling.
Zhong, Han; Guan, Wei; Zhang, Wenyi; Jiang, Shixiong; Fan, Lingling
2018-01-01
The normal studies on air traffic departure scheduling problem (DSP) mainly deal with an independent airport in which the departure traffic is not affected by surrounded airports, which, however, is not a consistent case. In reality, there still exist cases where several commercial airports are closely located and one of them possesses a higher priority. During the peak hours, the departure activities of the lower-priority airports are usually required to give way to those of higher-priority airport. These giving-way requirements can inflict a set of changes on the modeling of departure scheduling problem with respect to the lower-priority airports. To the best of our knowledge, studies on DSP under this condition are scarce. Accordingly, this paper develops a bi-objective integer programming model to address the flight departure scheduling of the partly-restricted (e.g., lower-priority) one among several adjacent airports. An adapted tabu search algorithm is designed to solve the current problem. It is demonstrated from the case study of Tianjin Binhai International Airport in China that the proposed method can obviously improve the operation efficiency, while still realizing superior equity and regularity among restricted flows.
Solving Vertex Cover Problem Using DNA Tile Assembly Model
Directory of Open Access Journals (Sweden)
Zhihua Chen
2013-01-01
Full Text Available DNA tile assembly models are a class of mathematically distributed and parallel biocomputing models in DNA tiles. In previous works, tile assembly models have been proved be Turing-universal; that is, the system can do what Turing machine can do. In this paper, we use tile systems to solve computational hard problem. Mathematically, we construct three tile subsystems, which can be combined together to solve vertex cover problem. As a result, each of the proposed tile subsystems consists of Θ(1 types of tiles, and the assembly process is executed in a parallel way (like DNA’s biological function in cells; thus the systems can generate the solution of the problem in linear time with respect to the size of the graph.
Directory of Open Access Journals (Sweden)
Hassan Javanshir
2012-01-01
Full Text Available The world trade has tremendous growth in marine transportation. This paper studies yard crane scheduling problem between different blocks in container terminal. Its purpose is to minimize total travel time of cranes between blocks and total delayed workload in blocks at different periods. In this way the problem is formulated as a mixed integer programming (MIP model. The block pairs between which yard cranes will be transferred, during the various periods, is determined by this model. Afterwards the model is coded in LINGO software, which benefits from branch and bound algorithm to solve. Computational results determine the yard cranes movement sequence among blocks to achieve minimum total travel time for cranes and minimum total delayed workload in blocks at different planning periods. Also the results show capability and adequacy of the developed model.
Updating Linear Schedules with Lowest Cost: a Linear Programming Model
Biruk, Sławomir; Jaśkowski, Piotr; Czarnigowska, Agata
2017-10-01
Many civil engineering projects involve sets of tasks repeated in a predefined sequence in a number of work areas along a particular route. A useful graphical representation of schedules of such projects is time-distance diagrams that clearly show what process is conducted at a particular point of time and in particular location. With repetitive tasks, the quality of project performance is conditioned by the ability of the planner to optimize workflow by synchronizing the works and resources, which usually means that resources are planned to be continuously utilized. However, construction processes are prone to risks, and a fully synchronized schedule may expire if a disturbance (bad weather, machine failure etc.) affects even one task. In such cases, works need to be rescheduled, and another optimal schedule should be built for the changed circumstances. This typically means that, to meet the fixed completion date, durations of operations have to be reduced. A number of measures are possible to achieve such reduction: working overtime, employing more resources or relocating resources from less to more critical tasks, but they all come at a considerable cost and affect the whole project. The paper investigates the problem of selecting the measures that reduce durations of tasks of a linear project so that the cost of these measures is kept to the minimum and proposes an algorithm that could be applied to find optimal solutions as the need to reschedule arises. Considering that civil engineering projects, such as road building, usually involve less process types than construction projects, the complexity of scheduling problems is lower, and precise optimization algorithms can be applied. Therefore, the authors put forward a linear programming model of the problem and illustrate its principle of operation with an example.
Humanoid Walking Robot: Modeling, Inverse Dynamics, and Gain Scheduling Control
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Elvedin Kljuno
2010-01-01
Full Text Available This article presents reference-model-based control design for a 10 degree-of-freedom bipedal walking robot, using nonlinear gain scheduling. The main goal is to show concentrated mass models can be used for prediction of the required joint torques for a bipedal walking robot. Relatively complicated architecture, high DOF, and balancing requirements make the control task of these robots difficult. Although linear control techniques can be used to control bipedal robots, nonlinear control is necessary for better performance. The emphasis of this work is to show that the reference model can be a bipedal walking model with concentrated mass at the center of gravity, which removes the problems related to design of a pseudo-inverse system. Another significance of this approach is the reduced calculation requirements due to the simplified procedure of nominal joint torques calculation. Kinematic and dynamic analysis is discussed including results for joint torques and ground force necessary to implement a prescribed walking motion. This analysis is accompanied by a comparison with experimental data. An inverse plant and a tracking error linearization-based controller design approach is described. We propose a novel combination of a nonlinear gain scheduling with a concentrated mass model for the MIMO bipedal robot system.
A complementarity model for solving stochastic natural gas market equilibria
International Nuclear Information System (INIS)
Zhuang Jifang; Gabriel, Steven A.
2008-01-01
This paper presents a stochastic equilibrium model for deregulated natural gas markets. Each market participant (pipeline operators, producers, etc.) solves a stochastic optimization problem whose optimality conditions, when combined with market-clearing conditions give rise to a certain mixed complementarity problem (MiCP). The stochastic aspects are depicted by a recourse problem for each player in which the first-stage decisions relate to long-term contracts and the second-stage decisions relate to spot market activities for three seasons. Besides showing that such a market model is an instance of a MiCP, we provide theoretical results concerning long-term and spot market prices and solve the resulting MiCP for a small yet representative market. We also note an interesting observation for the value of the stochastic solution for non-optimization problems
A complementarity model for solving stochastic natural gas market equilibria
International Nuclear Information System (INIS)
Jifang Zhuang; Gabriel, S.A.
2008-01-01
This paper presents a stochastic equilibrium model for deregulated natural gas markets. Each market participant (pipeline operators, producers, etc.) solves a stochastic optimization problem whose optimality conditions, when combined with market-clearing conditions give rise to a certain mixed complementarity problem (MiCP). The stochastic aspects are depicted by a recourse problem for each player in which the first-stage decisions relate to long-term contracts and the second-stage decisions relate to spot market activities for three seasons. Besides showing that such a market model is an instance of a MiCP, we provide theoretical results concerning long-term and spot market prices and solve the resulting MiCP for a small yet representative market. We also note an interesting observation for the value of the stochastic solution for non-optimization problems. (author)
Modelling human problem solving with data from an online game.
Rach, Tim; Kirsch, Alexandra
2016-11-01
Since the beginning of cognitive science, researchers have tried to understand human strategies in order to develop efficient and adequate computational methods. In the domain of problem solving, the travelling salesperson problem has been used for the investigation and modelling of human solutions. We propose to extend this effort with an online game, in which instances of the travelling salesperson problem have to be solved in the context of a game experience. We report on our effort to design and run such a game, present the data contained in the resulting openly available data set and provide an outlook on the use of games in general for cognitive science research. In addition, we present three geometrical models mapping the starting point preferences in the problems presented in the game as the result of an evaluation of the data set.
Composite spectral functions for solving Volterra's population model
International Nuclear Information System (INIS)
Ramezani, M.; Razzaghi, M.; Dehghan, M.
2007-01-01
An approximate method for solving Volterra's population model for population growth of a species in a closed system is proposed. Volterra's model is a nonlinear integro-differential equation, where the integral term represents the effect of toxin. The approach is based upon composite spectral functions approximations. The properties of composite spectral functions consisting of few terms of orthogonal functions are presented and are utilized to reduce the solution of the Volterra's model to the solution of a system of algebraic equations. The method is easy to implement and yields very accurate result
Optimal Cluster Mill Pass Scheduling With an Accurate and Rapid New Strip Crown Model
International Nuclear Information System (INIS)
Malik, Arif S.; Grandhi, Ramana V.; Zipf, Mark E.
2007-01-01
Besides the requirement to roll coiled sheet at high levels of productivity, the optimal pass scheduling of cluster-type reversing cold mills presents the added challenge of assigning mill parameters that facilitate the best possible strip flatness. The pressures of intense global competition, and the requirements for increasingly thinner, higher quality specialty sheet products that are more difficult to roll, continue to force metal producers to commission innovative flatness-control technologies. This means that during the on-line computerized set-up of rolling mills, the mathematical model should not only determine the minimum total number of passes and maximum rolling speed, it should simultaneously optimize the pass-schedule so that desired flatness is assured, either by manual or automated means. In many cases today, however, on-line prediction of strip crown and corresponding flatness for the complex cluster-type rolling mills is typically addressed either by trial and error, by approximate deflection models for equivalent vertical roll-stacks, or by non-physical pattern recognition style models. The abundance of the aforementioned methods is largely due to the complexity of cluster-type mill configurations and the lack of deflection models with sufficient accuracy and speed for on-line use. Without adequate assignment of the pass-schedule set-up parameters, it may be difficult or impossible to achieve the required strip flatness. In this paper, we demonstrate optimization of cluster mill pass-schedules using a new accurate and rapid strip crown model. This pass-schedule optimization includes computations of the predicted strip thickness profile to validate mathematical constraints. In contrast to many of the existing methods for on-line prediction of strip crown and flatness on cluster mills, the demonstrated method requires minimal prior tuning and no extensive training with collected mill data. To rapidly and accurately solve the multi-contact problem
Teaching Problem Solving without Modeling through "Thinking Aloud Pair Problem Solving."
Pestel, Beverly C.
1993-01-01
Reviews research relevant to the problem of unsatisfactory student problem-solving abilities and suggests a teaching strategy that addresses the issue. Author explains how she uses teaching aloud problem solving (TAPS) in college chemistry and presents evaluation data. Among the findings are that the TAPS class got fewer problems completely right,…
Directory of Open Access Journals (Sweden)
Paweł Sitek
2016-01-01
Full Text Available This paper proposes a hybrid programming framework for modeling and solving of constraint satisfaction problems (CSPs and constraint optimization problems (COPs. Two paradigms, CLP (constraint logic programming and MP (mathematical programming, are integrated in the framework. The integration is supplemented with the original method of problem transformation, used in the framework as a presolving method. The transformation substantially reduces the feasible solution space. The framework automatically generates CSP and COP models based on current values of data instances, questions asked by a user, and set of predicates and facts of the problem being modeled, which altogether constitute a knowledge database for the given problem. This dynamic generation of dedicated models, based on the knowledge base, together with the parameters changing externally, for example, the user’s questions, is the implementation of the autonomous search concept. The models are solved using the internal or external solvers integrated with the framework. The architecture of the framework as well as its implementation outline is also included in the paper. The effectiveness of the framework regarding the modeling and solution search is assessed through the illustrative examples relating to scheduling problems with additional constrained resources.
Optimization Model for Capacity Management and Bed Scheduling for Hospital
Sitepu, Suryati; Mawengkang, Herman; Husein, Ismail
2018-01-01
Hospital is a very important institution to provide health care for people. It is not surprising that nowadays the people’s demands for hospital is increasing.. However, due to the rising cost of healthcare services, hospitals need to consider efficiencies in order to overcome these two problems. This paper deals with an integrated strategy of staff capacity management and bed allocation planning to tackle these problems. Mathematically, the strategy can be modeled as an integer linear programming problem. We solve the model using a direct neighborhood search approach, based on the notion of superbasic variables.
Mathematical model and algorithm of operation scheduling for monitoring situation in local waters
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Sokolov Boris
2017-01-01
Full Text Available A multiple-model approach to description and investigation of control processes in regional maritime security system is presented. The processes considered in this paper were qualified as control processes of computing operations providing monitoring of the situation adding in the local water area and connected to relocation of different ships classes (further the active mobile objects (AMO. Previously developed concept of active moving object (AMO is used. The models describe operation of AMO automated monitoring and control system (AMCS elements as well as their interaction with objects-in-service that are sources or recipients of information being processed. The unified description of various control processes allows synthesizing simultaneously both technical and functional structures of AMO AMCS. The algorithm for solving the scheduling problem is described in terms of the classical theory of optimal automatic control.
Limited Area Forecasting and Statistical Modelling for Wind Energy Scheduling
DEFF Research Database (Denmark)
Rosgaard, Martin Haubjerg
forecast accuracy for operational wind power scheduling. Numerical weather prediction history and scales of atmospheric motion are summarised, followed by a literature review of limited area wind speed forecasting. Hereafter, the original contribution to research on the topic is outlined. The quality...... control of wind farm data used as forecast reference is described in detail, and a preliminary limited area forecasting study illustrates the aggravation of issues related to numerical orography representation and accurate reference coordinates at ne weather model resolutions. For the o shore and coastal...... sites studied limited area forecasting is found to deteriorate wind speed prediction accuracy, while inland results exhibit a steady forecast performance increase with weather model resolution. Temporal smoothing of wind speed forecasts is shown to improve wind power forecast performance by up to almost...
WE-D-BRE-04: Modeling Optimal Concurrent Chemotherapy Schedules
International Nuclear Information System (INIS)
Jeong, J; Deasy, J O
2014-01-01
Purpose: Concurrent chemo-radiation therapy (CCRT) has become a more common cancer treatment option with a better tumor control rate for several tumor sites, including head and neck and lung cancer. In this work, possible optimal chemotherapy schedules were investigated by implementing chemotherapy cell-kill into a tumor response model of RT. Methods: The chemotherapy effect has been added into a published model (Jeong et al., PMB (2013) 58:4897), in which the tumor response to RT can be simulated with the effects of hypoxia and proliferation. Based on the two-compartment pharmacokinetic model, the temporal concentration of chemotherapy agent was estimated. Log cell-kill was assumed and the cell-kill constant was estimated from the observed increase in local control due to concurrent chemotherapy. For a simplified two cycle CCRT regime, several different starting times and intervals were simulated with conventional RT regime (2Gy/fx, 5fx/wk). The effectiveness of CCRT was evaluated in terms of reduction in radiation dose required for 50% of control to find the optimal chemotherapy schedule. Results: Assuming the typical slope of dose response curve (γ50=2), the observed 10% increase in local control rate was evaluated to be equivalent to an extra RT dose of about 4 Gy, from which the cell-kill rate of chemotherapy was derived to be about 0.35. Best response was obtained when chemotherapy was started at about 3 weeks after RT began. As the interval between two cycles decreases, the efficacy of chemotherapy increases with broader range of optimal starting times. Conclusion: The effect of chemotherapy has been implemented into the resource-conservation tumor response model to investigate CCRT. The results suggest that the concurrent chemotherapy might be more effective when delayed for about 3 weeks, due to lower tumor burden and a larger fraction of proliferating cells after reoxygenation
Two-MILP models for scheduling elective surgeries within a private healthcare facility.
Khlif Hachicha, Hejer; Zeghal Mansour, Farah
2016-11-05
This paper deals with an Integrated Elective Surgery-Scheduling Problem (IESSP) that arises in a privately operated healthcare facility. It aims to optimize the resource utilization of the entire surgery process including pre-operative, per-operative and post-operative activities. Moreover, it addresses a specific feature of private facilities where surgeons are independent service providers and may conduct their surgeries in different private healthcare facilities. Thus, the problem requires the assignment of surgery patients to hospital beds, operating rooms and recovery beds as well as their sequencing over a 1-day period while taking into account surgeons' availability constraints. We present two Mixed Integer Linear Programs (MILP) that model the IESSP as a three-stage hybrid flow-shop scheduling problem with recirculation, resource synchronization, dedicated machines, and blocking constraints. To assess the empirical performance of the proposed models, we conducted experiments on real-world data of a Tunisian private clinic: Clinique Ennasr and on randomly generated instances. Two criteria were minimised: the patients' average length of stay and the number of patients' overnight stays. The computational results show that the proposed models can solve instances with up to 44 surgical cases in a reasonable CPU time using a general-purpose MILP solver.
Parallelization of elliptic solver for solving 1D Boussinesq model
Tarwidi, D.; Adytia, D.
2018-03-01
In this paper, a parallel implementation of an elliptic solver in solving 1D Boussinesq model is presented. Numerical solution of Boussinesq model is obtained by implementing a staggered grid scheme to continuity, momentum, and elliptic equation of Boussinesq model. Tridiagonal system emerging from numerical scheme of elliptic equation is solved by cyclic reduction algorithm. The parallel implementation of cyclic reduction is executed on multicore processors with shared memory architectures using OpenMP. To measure the performance of parallel program, large number of grids is varied from 28 to 214. Two test cases of numerical experiment, i.e. propagation of solitary and standing wave, are proposed to evaluate the parallel program. The numerical results are verified with analytical solution of solitary and standing wave. The best speedup of solitary and standing wave test cases is about 2.07 with 214 of grids and 1.86 with 213 of grids, respectively, which are executed by using 8 threads. Moreover, the best efficiency of parallel program is 76.2% and 73.5% for solitary and standing wave test cases, respectively.
Design Change Model for Effective Scheduling Change Propagation Paths
Zhang, Hai-Zhu; Ding, Guo-Fu; Li, Rong; Qin, Sheng-Feng; Yan, Kai-Yin
2017-09-01
Changes in requirements may result in the increasing of product development project cost and lead time, therefore, it is important to understand how requirement changes propagate in the design of complex product systems and be able to select best options to guide design. Currently, a most approach for design change is lack of take the multi-disciplinary coupling relationships and the number of parameters into account integrally. A new design change model is presented to systematically analyze and search change propagation paths. Firstly, a PDS-Behavior-Structure-based design change model is established to describe requirement changes causing the design change propagation in behavior and structure domains. Secondly, a multi-disciplinary oriented behavior matrix is utilized to support change propagation analysis of complex product systems, and the interaction relationships of the matrix elements are used to obtain an initial set of change paths. Finally, a rough set-based propagation space reducing tool is developed to assist in narrowing change propagation paths by computing the importance of the design change parameters. The proposed new design change model and its associated tools have been demonstrated by the scheduling change propagation paths of high speed train's bogie to show its feasibility and effectiveness. This model is not only supportive to response quickly to diversified market requirements, but also helpful to satisfy customer requirements and reduce product development lead time. The proposed new design change model can be applied in a wide range of engineering systems design with improved efficiency.
Modeling and Solving the Liner Shipping Service Selection Problem
DEFF Research Database (Denmark)
Karsten, Christian Vad; Balakrishnan, Anant
We address a tactical planning problem, the Liner Shipping Service Selection Problem (LSSSP), facing container shipping companies. Given estimated demand between various ports, the LSSSP entails selecting the best subset of non-simple cyclic sailing routes from a given pool of candidate routes...... to accurately model transshipment costs and incorporate routing policies such as maximum transit time, maritime cabotage rules, and operational alliances. Our hop-indexed arc flow model is smaller and easier to solve than path flow models. We outline a preprocessing procedure that exploits both the routing...... requirements and the hop limits to reduce problem size, and describe techniques to accelerate the solution procedure. We present computational results for realistic problem instances from the benchmark suite LINER-LIB....
Directory of Open Access Journals (Sweden)
Ming Zeng
2017-01-01
Full Text Available The gantry crane scheduling and storage space allocation problem in the main containers yard of railway container terminal is studied. A mixed integer programming model which comprehensively considers the handling procedures, noncrossing constraints, the safety margin and traveling time of gantry cranes, and the storage modes in the main area is formulated. A metaheuristic named backtracking search algorithm (BSA is then improved to solve this intractable problem. A series of computational experiments are carried out to evaluate the performance of the proposed algorithm under some randomly generated cases based on the practical operation conditions. The results show that the proposed algorithm can gain the near-optimal solutions within a reasonable computation time.
Solving seismological problems using sgraph program: II-waveform modeling
International Nuclear Information System (INIS)
Abdelwahed, Mohamed F.
2012-01-01
One of the seismological programs to manipulate seismic data is SGRAPH program. It consists of integrated tools to perform advanced seismological techniques. SGRAPH is considered a new system for maintaining and analyze seismic waveform data in a stand-alone Windows-based application that manipulate a wide range of data formats. SGRAPH was described in detail in the first part of this paper. In this part, I discuss the advanced techniques including in the program and its applications in seismology. Because of the numerous tools included in the program, only SGRAPH is sufficient to perform the basic waveform analysis and to solve advanced seismological problems. In the first part of this paper, the application of the source parameters estimation and hypocentral location was given. Here, I discuss SGRAPH waveform modeling tools. This paper exhibits examples of how to apply the SGRAPH tools to perform waveform modeling for estimating the focal mechanism and crustal structure of local earthquakes.
Modeling Blazar Spectra by Solving an Electron Transport Equation
Lewis, Tiffany; Finke, Justin; Becker, Peter A.
2018-01-01
Blazars are luminous active galaxies across the entire electromagnetic spectrum, but the spectral formation mechanisms, especially the particle acceleration, in these sources are not well understood. We develop a new theoretical model for simulating blazar spectra using a self-consistent electron number distribution. Specifically, we solve the particle transport equation considering shock acceleration, adiabatic expansion, stochastic acceleration due to MHD waves, Bohm diffusive particle escape, synchrotron radiation, and Compton radiation, where we implement the full Compton cross-section for seed photons from the accretion disk, the dust torus, and 26 individual broad lines. We used a modified Runge-Kutta method to solve the 2nd order equation, including development of a new mathematical method for normalizing stiff steady-state ordinary differential equations. We show that our self-consistent, transport-based blazar model can qualitatively fit the IR through Fermi g-ray data for 3C 279, with a single-zone, leptonic configuration. We use the solution for the electron distribution to calculate multi-wavelength SED spectra for 3C 279. We calculate the particle and magnetic field energy densities, which suggest that the emitting region is not always in equipartition (a common assumption), but sometimes matter dominated. The stratified broad line region (based on ratios in quasar reverberation mapping, and thus adding no free parameters) improves our estimate of the location of the emitting region, increasing it by ~5x. Our model provides a novel view into the physics at play in blazar jets, especially the relative strength of the shock and stochastic acceleration, where our model is well suited to distinguish between these processes, and we find that the latter tends to dominate.
Performance modeling of parallel algorithms for solving neutron diffusion problems
International Nuclear Information System (INIS)
Azmy, Y.Y.; Kirk, B.L.
1995-01-01
Neutron diffusion calculations are the most common computational methods used in the design, analysis, and operation of nuclear reactors and related activities. Here, mathematical performance models are developed for the parallel algorithm used to solve the neutron diffusion equation on message passing and shared memory multiprocessors represented by the Intel iPSC/860 and the Sequent Balance 8000, respectively. The performance models are validated through several test problems, and these models are used to estimate the performance of each of the two considered architectures in situations typical of practical applications, such as fine meshes and a large number of participating processors. While message passing computers are capable of producing speedup, the parallel efficiency deteriorates rapidly as the number of processors increases. Furthermore, the speedup fails to improve appreciably for massively parallel computers so that only small- to medium-sized message passing multiprocessors offer a reasonable platform for this algorithm. In contrast, the performance model for the shared memory architecture predicts very high efficiency over a wide range of number of processors reasonable for this architecture. Furthermore, the model efficiency of the Sequent remains superior to that of the hypercube if its model parameters are adjusted to make its processors as fast as those of the iPSC/860. It is concluded that shared memory computers are better suited for this parallel algorithm than message passing computers
Solving the Standard Model Problems in Softened Gravity
Salvio, Alberto
2016-11-16
The Higgs naturalness problem is solved if the growth of Einstein's gravitational interaction is softened at an energy $ \\lesssim 10^{11}\\,$GeV (softened gravity). We work here within an explicit realization where the Einstein-Hilbert Lagrangian is extended to include terms quadratic in the curvature and a non-minimal coupling with the Higgs. We show that this solution is preserved by adding three right-handed neutrinos with masses below the electroweak scale, accounting for neutrino oscillations, dark matter and the baryon asymmetry. The smallness of the right-handed neutrino masses (compared to the Planck scale) and the QCD $\\theta$-term are also shown to be natural. We prove that a possible gravitational source of CP violation cannot spoil the model, thanks to the presence of right-handed neutrinos. Starobinsky inflation can occur in this context, even if we live in a metastable vacuum.
Mesoscale modeling: solving complex flows in biology and biotechnology.
Mills, Zachary Grant; Mao, Wenbin; Alexeev, Alexander
2013-07-01
Fluids are involved in practically all physiological activities of living organisms. However, biological and biorelated flows are hard to analyze due to the inherent combination of interdependent effects and processes that occur on a multitude of spatial and temporal scales. Recent advances in mesoscale simulations enable researchers to tackle problems that are central for the understanding of such flows. Furthermore, computational modeling effectively facilitates the development of novel therapeutic approaches. Among other methods, dissipative particle dynamics and the lattice Boltzmann method have become increasingly popular during recent years due to their ability to solve a large variety of problems. In this review, we discuss recent applications of these mesoscale methods to several fluid-related problems in medicine, bioengineering, and biotechnology. Copyright © 2013 Elsevier Ltd. All rights reserved.
Directory of Open Access Journals (Sweden)
Seyyed Mohammad Hassan Hosseini
2016-05-01
Full Text Available Scheduling problem for the hybrid flow shop scheduling problem (HFSP followed by an assembly stage considering aging effects additional preventive and maintenance activities is studied in this paper. In this production system, a number of products of different kinds are produced. Each product is assembled with a set of several parts. The first stage is a hybrid flow shop to produce parts. All machines can process all kinds of parts in this stage but each machine can process only one part at the same time. The second stage is a single assembly machine or a single assembly team of workers. The aim is to schedule the parts on the machines and assembly sequence and also determine when the preventive maintenance activities get done in order to minimize the completion time of all products (makespan. A mathematical modeling is presented and its validation is shown by solving an example in small scale. Since this problem has been proved strongly NP-hard, in order to solve the problem in medium and large scale, four heuristic algorithms is proposed based on the Johnson’s algorithm. The numerical experiments are used to run the mathematical model and evaluate the performance of the proposed algorithms.
Developing a Model to Support Students in Solving Subtraction
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Nila Mareta Murdiyani
2013-01-01
Full Text Available Subtraction has two meanings and each meaning leads to the different strategies. The meaning of “taking away something” suggests a direct subtraction, while the meaning of “determining the difference between two numbers” is more likely to be modeled as indirect addition. Many prior researches found that the second meaning and second strategy rarely appeared in the mathematical textbooks and teacher explanations, including in Indonesia. Therefore, this study was conducted to contribute to the development of a local instruction theory for subtraction by designing instructional activities that can facilitate first grade of primary school students to develop a model in solving two digit numbers subtraction. Consequently, design research was chosen as an appropriate approach for achieving the research aim and Realistic Mathematics Education (RME was used as a guide to design the lesson. This study involved 6 students in the pilot experiment, 31 students in the teaching experiment, and a first grade teacher of SDN 179 Palembang. The result of this study shows that the beads string could bridge students from the contextual problems (taking ginger candies and making grains bracelets to the use of the empty number line. It also shows that the empty number line could promote students to use different strategies (direct subtraction, indirect addition, and indirect subtraction in solving subtraction problems. Based on these findings, it is recommended to apply RME in the teaching learning process to make it more meaningful for students. Keywords: Subtraction, Design Research, Realistic Mathematics Education, The Beads String, The Empty Number Line DOI: http://dx.doi.org/10.22342/jme.4.1.567.95-112
Modelling a Nurse Shift Schedule with Multiple Preference Ranks for Shifts and Days-Off
Directory of Open Access Journals (Sweden)
Chun-Cheng Lin
2014-01-01
Full Text Available When it comes to nurse shift schedules, it is found that the nursing staff have diverse preferences about shift rotations and days-off. The previous studies only focused on the most preferred work shift and the number of satisfactory days-off of the schedule at the current schedule period but had few discussions on the previous schedule periods and other preference levels for shifts and days-off, which may affect fairness of shift schedules. As a result, this paper proposes a nurse scheduling model based upon integer programming that takes into account constraints of the schedule, different preference ranks towards each shift, and the historical data of previous schedule periods to maximize the satisfaction of all the nursing staff's preferences about the shift schedule. The main contribution of the proposed model is that we consider that the nursing staff’s satisfaction level is affected by multiple preference ranks and their priority ordering to be scheduled, so that the quality of the generated shift schedule is more reasonable. Numerical results show that the planned shifts and days-off are fair and successfully meet the preferences of all the nursing staff.
Shift scheduling model considering workload and worker’s preference for security department
Herawati, A.; Yuniartha, D. R.; Purnama, I. L. I.; Dewi, LT
2018-04-01
Security department operates for 24 hours and applies shift scheduling to organize its workers as well as in hotel industry. This research has been conducted to develop shift scheduling model considering the workers physical workload using rating of perceived exertion (RPE) Borg’s Scale and workers’ preference to accommodate schedule flexibility. The mathematic model is developed in integer linear programming and results optimal solution for simple problem. Resulting shift schedule of the developed model has equally distribution shift allocation among workers to balance the physical workload and give flexibility for workers in working hours arrangement.
Klerman, Elizabeth B; Beckett, Scott A; Landrigan, Christopher P
2016-09-13
In 2011 the U.S. Accreditation Council for Graduate Medical Education began limiting first year resident physicians (interns) to shifts of ≤16 consecutive hours. Controversy persists regarding the effectiveness of this policy for reducing errors and accidents while promoting education and patient care. Using a mathematical model of the effects of circadian rhythms and length of time awake on objective performance and subjective alertness, we quantitatively compared predictions for traditional intern schedules to those that limit work to ≤ 16 consecutive hours. We simulated two traditional schedules and three novel schedules using the mathematical model. The traditional schedules had extended duration work shifts (≥24 h) with overnight work shifts every second shift (including every third night, Q3) or every third shift (including every fourth night, Q4) night; the novel schedules had two different cross-cover (XC) night team schedules (XC-V1 and XC-V2) and a Rapid Cycle Rotation (RCR) schedule. Predicted objective performance and subjective alertness for each work shift were computed for each individual's schedule within a team and then combined for the team as a whole. Our primary outcome was the amount of time within a work shift during which a team's model-predicted objective performance and subjective alertness were lower than that expected after 16 or 24 h of continuous wake in an otherwise rested individual. The model predicted fewer hours with poor performance and alertness, especially during night-time work hours, for all three novel schedules than for either the traditional Q3 or Q4 schedules. Three proposed schedules that eliminate extended shifts may improve performance and alertness compared with traditional Q3 or Q4 schedules. Predicted times of worse performance and alertness were at night, which is also a time when supervision of trainees is lower. Mathematical modeling provides a quantitative comparison approach with potential to aid
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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.
Quadratic adaptive algorithm for solving cardiac action potential models.
Chen, Min-Hung; Chen, Po-Yuan; Luo, Ching-Hsing
2016-10-01
An adaptive integration method is proposed for computing cardiac action potential models accurately and efficiently. Time steps are adaptively chosen by solving a quadratic formula involving the first and second derivatives of the membrane action potential. To improve the numerical accuracy, we devise an extremum-locator (el) function to predict the local extremum when approaching the peak amplitude of the action potential. In addition, the time step restriction (tsr) technique is designed to limit the increase in time steps, and thus prevent the membrane potential from changing abruptly. The performance of the proposed method is tested using the Luo-Rudy phase 1 (LR1), dynamic (LR2), and human O'Hara-Rudy dynamic (ORd) ventricular action potential models, and the Courtemanche atrial model incorporating a Markov sodium channel model. Numerical experiments demonstrate that the action potential generated using the proposed method is more accurate than that using the traditional Hybrid method, especially near the peak region. The traditional Hybrid method may choose large time steps near to the peak region, and sometimes causes the action potential to become distorted. In contrast, the proposed new method chooses very fine time steps in the peak region, but large time steps in the smooth region, and the profiles are smoother and closer to the reference solution. In the test on the stiff Markov ionic channel model, the Hybrid blows up if the allowable time step is set to be greater than 0.1ms. In contrast, our method can adjust the time step size automatically, and is stable. Overall, the proposed method is more accurate than and as efficient as the traditional Hybrid method, especially for the human ORd model. The proposed method shows improvement for action potentials with a non-smooth morphology, and it needs further investigation to determine whether the method is helpful during propagation of the action potential. Copyright © 2016 Elsevier Ltd. All rights
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.
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...
Shorikov, A. F.; Butsenko, E. V.
2017-10-01
This paper discusses the problem of multicriterial adaptive optimization the control of investment projects in the presence of several technologies. On the basis of network modeling proposed a new economic and mathematical model and a method for solving the problem of multicriterial adaptive optimization the control of investment projects in the presence of several technologies. Network economic and mathematical modeling allows you to determine the optimal time and calendar schedule for the implementation of the investment project and serves as an instrument to increase the economic potential and competitiveness of the enterprise. On a meaningful practical example, the processes of forming network models are shown, including the definition of the sequence of actions of a particular investment projecting process, the network-based work schedules are constructed. The calculation of the parameters of network models is carried out. Optimal (critical) paths have been formed and the optimal time for implementing the chosen technologies of the investment project has been calculated. It also shows the selection of the optimal technology from a set of possible technologies for project implementation, taking into account the time and cost of the work. The proposed model and method for solving the problem of managing investment projects can serve as a basis for the development, creation and application of appropriate computer information systems to support the adoption of managerial decisions by business people.
A problem solving model for regulatory policy making
Boer, A.; van Engers, T.; Sileno, G.; Wyner, A.; Benn, N.
2011-01-01
In this paper we discuss how the interests and field theory promoted by public administration as a stakeholder in policy argumentation, directly arise from its problem solving activities, using the framework for public administration problem solving we proposed in [1,2]. We propose that calls for
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...
Development of an irrigation scheduling software based on model predicted crop water stress
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...
A QUADTREE ORGANIZATION CONSTRUCTION AND SCHEDULING METHOD FOR URBAN 3D MODEL BASED ON WEIGHT
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...
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.
Model Integrated Problem Solving Based Learning pada Perkuliahan Dasar-dasar Kimia Analitik
Indarini Dwi Pursitasari; Anna Permanasari
2013-01-01
Abstract: Integrated Problem Solving Based Learning Model on Foundation of Analytical Chemistry. This study was conducted to know the effects of Integrated Problem Solving Based Learning (IPSBL) model on problem solving skills and cognitive ability of pre-service teachers. The subjects of the study were 41 pre- service teachers, 21 in the experimental group and 20 in the control group. The data were collected through a test on problem solving skills, a test on cognitive ability, and a questio...
Model Integrated Problem Solving Based Learning Pada Perkuliahan Dasar-dasar Kimia Analitik
Pursitasari, Indarini Dwi; Permanasari, Anna
2012-01-01
: Integrated Problem Solving Based Learning Model on Foundation of Analytical Chemistry. This study was conducted to know the effects of Integrated Problem Solving Based Learning (IPSBL) model on problem solving skills and cognitive ability of pre-service teachers. The subjects of the study were 41 pre- service teachers, 21 in the experimental group and 20 in the control group. The data were collected through a test on problem solving skills, a test on cognitive ability, and a questionnaire o...
Microgrid Reliability Modeling and Battery Scheduling Using Stochastic Linear Programming
Energy Technology Data Exchange (ETDEWEB)
Cardoso, Goncalo; Stadler, Michael; Siddiqui, Afzal; Marnay, Chris; DeForest, Nicholas; Barbosa-Povoa, Ana; Ferrao, Paulo
2013-05-23
This paper describes the introduction of stochastic linear programming into Operations DER-CAM, a tool used to obtain optimal operating schedules for a given microgrid under local economic and environmental conditions. This application follows previous work on optimal scheduling of a lithium-iron-phosphate battery given the output uncertainty of a 1 MW molten carbonate fuel cell. Both are in the Santa Rita Jail microgrid, located in Dublin, California. This fuel cell has proven unreliable, partially justifying the consideration of storage options. Several stochastic DER-CAM runs are executed to compare different scenarios to values obtained by a deterministic approach. Results indicate that using a stochastic approach provides a conservative yet more lucrative battery schedule. Lower expected energy bills result, given fuel cell outages, in potential savings exceeding 6percent.
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...
Scholten, H.
2008-01-01
Mathematical models are more and more used to support to solve multidisciplinary, real world problems of increasing complexity. They are often plagued by obstacles such as miscommunication between modellers with different disciplinary backgrounds leading to a non-transparent modelling process. Other
A Framework for Uplink Intercell Interference Modeling with Channel-Based Scheduling
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
International Nuclear Information System (INIS)
Lee, Kwang Ho; Roh, Myung Sub
2013-01-01
There are so many different factors to consider when constructing a nuclear power plant successfully from planning to decommissioning. According to PMBOK, all projects have nine domains from a holistic project management perspective. They are equally important to all projects, however, this study focuses mostly on the processes required to manage timely completion of the project and conduct risk management. The overall objective of this study is to let you know what the risk analysis derived from scheduling of NPP project is, and understand how to implement the stochastic process modeling through risk management. Building the Nuclear Power Plant is required a great deal of time and fundamental knowledge related to all engineering. That means that integrated project scheduling management with so many activities is necessary and very important. Simulation techniques for scheduling of NPP project using Open Plan program, Crystal Ball program, and Minitab program can be useful tools for designing optimal schedule planning. Thus far, Open Plan and Monte Carlo programs have been used to calculate the critical path for scheduling network analysis. And also, Minitab program has been applied to monitor the scheduling risk. This approach to stochastic modeling through risk analysis of project activities is very useful for optimizing the schedules of activities using Critical Path Method and managing the scheduling control of NPP project. This study has shown new approach to optimal scheduling of NPP project, however, this does not consider the characteristic of activities according to the NPP site conditions. Hence, this study needs more research considering those factors
Energy Technology Data Exchange (ETDEWEB)
Lee, Kwang Ho; Roh, Myung Sub [KEPCO International Nuclear Graduate School, Ulsan (Korea, Republic of)
2013-10-15
There are so many different factors to consider when constructing a nuclear power plant successfully from planning to decommissioning. According to PMBOK, all projects have nine domains from a holistic project management perspective. They are equally important to all projects, however, this study focuses mostly on the processes required to manage timely completion of the project and conduct risk management. The overall objective of this study is to let you know what the risk analysis derived from scheduling of NPP project is, and understand how to implement the stochastic process modeling through risk management. Building the Nuclear Power Plant is required a great deal of time and fundamental knowledge related to all engineering. That means that integrated project scheduling management with so many activities is necessary and very important. Simulation techniques for scheduling of NPP project using Open Plan program, Crystal Ball program, and Minitab program can be useful tools for designing optimal schedule planning. Thus far, Open Plan and Monte Carlo programs have been used to calculate the critical path for scheduling network analysis. And also, Minitab program has been applied to monitor the scheduling risk. This approach to stochastic modeling through risk analysis of project activities is very useful for optimizing the schedules of activities using Critical Path Method and managing the scheduling control of NPP project. This study has shown new approach to optimal scheduling of NPP project, however, this does not consider the characteristic of activities according to the NPP site conditions. Hence, this study needs more research considering those factors.
Taking the lag out of jet lag through model-based schedule design.
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.
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.
Application of 3D model in the schedule management of nuclear power plant construction
International Nuclear Information System (INIS)
Nian Fayang
2009-01-01
While 3D technology has been widely used in engineering design, the 3D model of engineering design also includes information that can be used to construction. By the visual interface, the 3D model can be used in different aspects of construction. By linking the 3D model with the construction schedule, the 4D model can be created, through which the visual manage of the construction schedule can be achieved. (authors)
Modeling a content-aware LTE MAC downlink scheduler with heterogeneous traffic
DEFF Research Database (Denmark)
Artuso, Matteo; Christiansen, Henrik Lehrmann
2013-01-01
The scheduling policy adopted in the LTE (Long Term Evolution) MAC layer is the most valuable degree of freedom left from the 3GPP (3rd Generation Partnership Project) consortium to the industry and the research community . This paper presents an OPNET model of the downlink scheduling in a one...
Directory of Open Access Journals (Sweden)
Maxim A. Dulebenets
2018-03-01
Full Text Available Considering a substantial increase in volumes of the international seaborne trade and drastic climate changes due to carbon dioxide emissions, liner shipping companies have to improve planning of their vessel schedules and improve energy efficiency. This paper presents a novel mixed integer non-linear mathematical model for the green vessel scheduling problem, which directly accounts for the carbon dioxide emission costs in sea and at ports of call. The original non-linear model is linearized and then solved using CPLEX. A set of numerical experiments are conducted for a real-life liner shipping route to reveal managerial insights that can be of importance to liner shipping companies. Results indicate that the proposed mathematical model can serve as an efficient planning tool for liner shipping companies and may assist with evaluation of various carbon dioxide taxation schemes. Increasing carbon dioxide tax may substantially change the design of vessel schedules, incur additional route service costs, and improve the environmental sustainability. However, the effects from increasing carbon dioxide tax on the marine container terminal operations are found to be very limited.
van Hoorn, Jelke J.; Nogueira, Agustín; Ojea, Ignacio; Gromicho Dos Santos, Joaquim Antonio
2017-01-01
In [1] an algorithm is proposed for solving the job-shop scheduling problem optimally using a dynamic programming strategy. This is, according to our knowledge, the first exact algorithm for the Job Shop problem which is not based on integer linear programming and branch and bound. Despite the
Amirghasemi, Mehrdad; Zamani, Reza
2014-01-01
This paper presents an effective procedure for solving the job shop problem. Synergistically combining small and large neighborhood schemes, the procedure consists of four components, namely (i) a construction method for generating semi-active schedules by a forward-backward mechanism, (ii) a local search for manipulating a small neighborhood structure guided by a tabu list, (iii) a feedback-based mechanism for perturbing the solutions generated, and (iv) a very large-neighborhood local search guided by a forward-backward shifting bottleneck method. The combination of shifting bottleneck mechanism and tabu list is used as a means of the manipulation of neighborhood structures, and the perturbation mechanism employed diversifies the search. A feedback mechanism, called repeat-check, detects consequent repeats and ignites a perturbation when the total number of consecutive repeats for two identical makespan values reaches a given threshold. The results of extensive computational experiments on the benchmark instances indicate that the combination of these four components is synergetic, in the sense that they collectively make the procedure fast and robust.
Directory of Open Access Journals (Sweden)
Pongpan Nakkaew
2016-06-01
Full Text Available In manufacturing process where efficiency is crucial in order to remain competitive, flowshop is a common configuration in which machines are arranged in series and products are produced through the stages one by one. In certain production processes, the machines are frequently configured in the way that each production stage may contain multiple processing units in parallel or hybrid. Moreover, along with precedent conditions, the sequence dependent setup times may exist. Finally, in case there is no buffer, a machine is said to be blocked if the next stage to handle its output is being occupied. Such NP-Hard problem, referred as Blocking Hybrid Flowshop Scheduling Problem with Sequence Dependent Setup/Changeover Times, is usually not possible to find the best exact solution to satisfy optimization objectives such as minimization of the overall production time. Thus, it is usually solved by approximate algorithms such as metaheuristics. In this paper, we investigate comparatively the effectiveness of the two approaches: a Genetic Algorithm (GA and an Artificial Bee Colony (ABC algorithm. GA is inspired by the process of natural selection. ABC, in the same manner, resembles the way types of bees perform specific functions and work collectively to find their foods by means of division of labor. Additionally, we apply an algorithm to improve the GA and ABC algorithms so that they can take advantage of parallel processing resources of modern multiple core processors while eliminate the need for screening the optimal parameters of both algorithms in advance.
Simulation of less master production schedule nervousness model
Herrera , Carlos; Thomas , André
2009-01-01
International audience; In production decision making systems, Master Production Schedule (MPS) states the requirements for individual end items by date and quantity. The solution sensitivity to demand forecast changes, unforeseen supplier and production problem occurrences, is known as nervousness. This feature cause undesirable effects at tactical and operational levels. Some of these effects are production and inventory cost increases and, also, negative impacts on overall and labor produc...
Military Free Fall Scheduling And Manifest Optimization Model
2016-12-01
zone. As interest in qualifying more personnel increased, the course expanded. By the mid-1990s, Reyes explains, a new location was required to better...Since 2005, the Chilean Professional Soccer Association has used operations research techniques to schedule professional leagues in Chile . These...a new parachute the students are using, the RA-1. The RA-1 parachute has a longer glide ratio, which means the rate of descent is slower than with
Comparing Model Ozone Loss during the SOLVE and SOLVE-2 Winters
Drdla, K.
2003-01-01
Model simulations have been used to analyze the factors influencing ozone loss during the 1999-2000 and 2002-2003 js. For both winters, the evolution of the Arctic vortex from November to April has been simulated using a trajectory-based microphysical and photochemical model. Extensive PSC formation and strong ozone depletion are evident in both winters. However, the ozone loss begins earlier in the 2002-2003 winter, with significant ozone depletion by early January. Analysis of the model results shows that during December 2002 not only cold temperatures but also the vortex structure was critical, allowing PSC-processed air parcels to experience significant solar exposure. The resultant ozone loss can be differentiated from ozone loss that occurs in the springtime, in particular because of the continued exposure to PSCs. For example, chlorine reactivation by the PSCs causes ozone loss to be insensitive to denitrification. Therefore, diagnosing the extent of ozone loss early in the winter is critical In understanding the overall winter-long ozone depletion.
A Scheduling Model for the Re-entrant Manufacturing System and Its Optimization by NSGA-II
Directory of Open Access Journals (Sweden)
Masoud Rabbani
2016-11-01
Full Text Available In this study, a two-objective mixed-integer linear programming model (MILP for multi-product re-entrant flow shop scheduling problem has been designed. As a result, two objectives are considered. One of them is maximization of the production rate and the other is the minimization of processing time. The system has m stations and can process several products in a moment. The re-entrant ﬂow shop scheduling problem is well known as NP-hard problem and its complexity has been discussed by several researchers. Given that NSGA-II algorithm is one of the strongest and most applicable algorithm in solving multi-objective optimization problems, it is used to solve this problem. To increase algorithm performance, Taguchi technique is used to design experiments for algorithm’s parameters. Numerical experiments are proposed to show the efficiency and effectiveness of the model. Finally, the results of NSGA-II are compared with SPEA2 algorithm (Strength Pareto Evolutionary Algorithm 2. The experimental results show that the proposed algorithm performs significantly better than the SPEA2.
Directory of Open Access Journals (Sweden)
N.M. Ghasem
2003-12-01
Full Text Available In this paper, the simulink block diagram is used to solve a model consists of a set of ordinary differential and algebraic equations to control the temperature inside a simple stirred tank heater. The flexibility of simulink block diagram gives students a better understanding of the control systems. The simulink also allows solution of mathematical models and easy visualization of the system variables. A polyethylene fluidized bed reactor is considered as an industrial example and the effect of the Proportional, Integral and Derivative control policy is presented for comparison.
A Cognitive Model for Problem Solving in Computer Science
Parham, Jennifer R.
2009-01-01
According to industry representatives, computer science education needs to emphasize the processes involved in solving computing problems rather than their solutions. Most of the current assessment tools used by universities and computer science departments analyze student answers to problems rather than investigating the processes involved in…
A Unified Model of Attention and Problem Solving.
1984-02-01
paradigma deocribed boro. In confliot condition. In a facolitation condition GREEN Stroup sitnations signls are preented simultaneously o would be plinted In...and perforlao. paradigma similar to theae studied .. . .. ’ Attention and Problem solInS Page 65 Attention and Problem Solving Page 66 her.. Mis
SURVEY - Multicriteria Models for Just-in-Time Scheduling
T'Kindt , Vincent
2010-01-01
Abstract Just-in-Time manufacturing consists in organizing the production of elements in order to meet a certain number of objectives or requirements according to the so-called ?Just-in-Time philosophy?. Just-in-Time has been extensively studied in the literature for many years due to the high number of real-life situations where it can be applied. This paper aims at revisiting Just-in-Time principles and detailing how they can be applied to the scheduling stage of a manufacturi...
Model Predictive Control of a Nonlinear System with Known Scheduling Variable
DEFF Research Database (Denmark)
Mirzaei, Mahmood; Poulsen, Niels Kjølstad; Niemann, Hans Henrik
2012-01-01
Model predictive control (MPC) of a class of nonlinear systems is considered in this paper. We will use Linear Parameter Varying (LPV) model of the nonlinear system. By taking the advantage of having future values of the scheduling variable, we will simplify state prediction. Consequently...... the control problem of the nonlinear system is simplied into a quadratic programming. Wind turbine is chosen as the case study and we choose wind speed as the scheduling variable. Wind speed is measurable ahead of the turbine, therefore the scheduling variable is known for the entire prediction horizon....
Solving Enterprise Applications Performance Puzzles Queuing Models to the Rescue
Grinshpan, Leonid
2012-01-01
A groundbreaking scientific approach to solving enterprise applications performance problems Enterprise applications are the information backbone of today's corporations, supporting vital business functions such as operational management, supply chain maintenance, customer relationship administration, business intelligence, accounting, procurement logistics, and more. Acceptable performance of enterprise applications is critical for a company's day-to-day operations as well as for its profitability. Unfortunately, troubleshooting poorly performing enterprise applications has traditionally
Haili, Hasnawati; Maknun, Johar; Siahaan, Parsaoran
2017-08-01
Physics is a lessons that related to students' daily experience. Therefore, before the students studying in class formally, actually they have already have a visualization and prior knowledge about natural phenomenon and could wide it themselves. The learning process in class should be aimed to detect, process, construct, and use students' mental model. So, students' mental model agree with and builds in the right concept. The previous study held in MAN 1 Muna informs that in learning process the teacher did not pay attention students' mental model. As a consequence, the learning process has not tried to build students' mental modelling ability (MMA). The purpose of this study is to describe the improvement of students' MMA as a effect of problem solving based learning model with multiple representations approach. This study is pre experimental design with one group pre post. It is conducted in XI IPA MAN 1 Muna 2016/2017. Data collection uses problem solving test concept the kinetic theory of gasses and interview to get students' MMA. The result of this study is clarification students' MMA which is categorized in 3 category; High Mental Modelling Ability (H-MMA) for 7Mental Modelling Ability (M-MMA) for 3Mental Modelling Ability (L-MMA) for 0 ≤ x ≤ 3 score. The result shows that problem solving based learning model with multiple representations approach can be an alternative to be applied in improving students' MMA.
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...
a Quadtree Organization Construction and Scheduling Method for Urban 3d Model Based on Weight
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.
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.
Lee, Young-Jin
2017-01-01
Purpose: The purpose of this paper is to develop a quantitative model of problem solving performance of students in the computer-based mathematics learning environment. Design/methodology/approach: Regularized logistic regression was used to create a quantitative model of problem solving performance of students that predicts whether students can…
Susi Fatikhah Setiyawati; Heru Kuswanto
2015-01-01
Penelitian ini bertujuan: (1) menghasilkan buku pedoman guru untuk pembelajaran fisika SMA menggunakan model problem solving sesuai level inkuiri yang layak digunakan; (2) mendeskripsikan keberhasilan pembelajaran fisika menggunakan model problem solving (MPS) sesuai dengan level inkuiri sesuai dengan buku pedoman terhadap peningkatan aktivitas peserta didik dan kemampuan berpikir kritis peserta didik. Penelitian ini merupakan penelitian pengembangan, sesuai langkah yang dikembangkan oleh Bor...
Future aircraft networks and schedules
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
SMI Compatible Simulation Scheduler Design for Reuse of Model Complying with SMP Standard
Directory of Open Access Journals (Sweden)
Cheol-Hea Koo
2010-12-01
Full Text Available Software reusability is one of key factors which impacts cost and schedule on a software development project. It is very crucial also in satellite simulator development since there are many commercial simulator models related to satellite and dynamics. If these models can be used in another simulator platform, great deal of confidence and cost/schedule reduction would be achieved. Simulation model portability (SMP is maintained by European Space Agency and many models compatible with SMP/simulation model interface (SMI are available. Korea Aerospace Research Institute (KARI is developing hardware abstraction layer (HAL supported satellite simulator to verify on-board software of satellite. From above reasons, KARI wants to port these SMI compatible models to the HAL supported satellite simulator. To port these SMI compatible models to the HAL supported satellite simulator, simulation scheduler is preliminary designed according to the SMI standard.
Constraint optimization model of a scheduling problem for a robotic arm in automatic systems
DEFF Research Database (Denmark)
Kristiansen, Ewa; Smith, Stephen F.; Kristiansen, Morten
2014-01-01
are characteristics of the painting process application itself. Unlike spot-welding, painting tasks require movement of the entire robot arm. In addition to minimizing intertask duration, the scheduler must strive to maximize painting quality and the problem is formulated as a multi-objective optimization problem....... The scheduling model is implemented as a stand-alone module using constraint programming, and integrated with a larger automatic system. The results of a number of simulation experiments with simple parts are reported, both to characterize the functionality of the scheduler and to illustrate the operation...... of the entire software system for automatic generation of robot programs for painting....
Optimal Day-ahead Charging Scheduling of Electric Vehicles through an Aggregative Game Model
DEFF Research Database (Denmark)
Liu, Zhaoxi; Wu, Qiuwei; Huang, Shaojun
2017-01-01
The electric vehicle (EV) market has been growing rapidly around the world. With large scale deployment of EVs in power systems, both the grid and EV owners will benefit if the flexible demand of EV charging is properly managed through the electricity market. When EV charging demand is considerable...... in a grid, it will impact spot prices in the electricity market and consequently influence the charging scheduling itself. The interaction between the spot prices and the EV demand needs to be considered in the EV charging scheduling, otherwise it will lead to a higher charging cost. A day-ahead EV charging...... scheduling based on an aggregative game model is proposed in this paper. The impacts of the EV demand on the electricity prices are formulated with the game model in the scheduling considering possible actions of other EVs. The existence and uniqueness of the pure strategy Nash equilibrium are proved...
Directory of Open Access Journals (Sweden)
Yang Jiang
2016-01-01
Full Text Available It is difficult to generate the new schedule effectively for minimizing the negative impact when an unanticipated disruption occurs after a subset of tasks has been finished in production scheduling. In such cases, continuing with the original schedule may not be optimal or feasible. Based on disruption management and Internet of things (IoT, this study designs a real-time status analyzer to identify the disruption and propose a recovery model to deal with the disruption. The computational result proves that our algorithm is competitive with the existing heuristics. Furthermore, due to the tradeoff between all participators (mainly including customers, managers of production enterprise, and workers involved in production scheduling, our model is more effective than the total rescheduling and right-shift rescheduling.
Model Integrated Problem Solving Based Learning pada Perkuliahan Dasar-dasar Kimia Analitik
Directory of Open Access Journals (Sweden)
Indarini Dwi Pursitasari
2013-07-01
Full Text Available Abstract: Integrated Problem Solving Based Learning Model on Foundation of Analytical Chemistry. This study was conducted to know the effects of Integrated Problem Solving Based Learning (IPSBL model on problem solving skills and cognitive ability of pre-service teachers. The subjects of the study were 41 pre- service teachers, 21 in the experimental group and 20 in the control group. The data were collected through a test on problem solving skills, a test on cognitive ability, and a questionnaire on the students’opinions on the use of IPSBL model. The quantitative data were analyzed using t-test and one-way ANOVA, and the qualitative data were analyzed by counting the percentage. The results of the study show that the implementation of IPSBL model increased the problem solving skills and cognitive ability of the pre-service teachers . The model was also responded positively by the research subjects. Abstrak: Model Integrated Problem Solving Based learning pada Perkuliahan Dasar-dasar Kimia Analitik. Penelitian ini bertujuan menentukan pengaruh model Integrated Problem Solving Based Learning(IPSBL terhadap peningkatan kemampuan problem solving dan kemampuan kognitif mahasiswa calon guru. Subjek penelitian terdiri dari 21 mahasiswa kelas eksperimen dan 20 mahasiswa kelas kontrol. Data dikumpulkan menggunakan tes kemampuan problem solving, tes kemampuan kognitif, dan angket untuk menjaring pendapat mahasiswa terhadap penggunaan model IPSBL . Data kuantitatif dianalisis denga n uji- t dan Anava dengan bantuan program SPSS 16.0. Data kualitatif dihitung persentasenya. Hasil penelitian menunjukkan bahwa model IPSBL dapat meningkatkan kemampuan problem solving dan kemampuan kognitif serta mendapat tanggapan yang positif dari mahasiswa.
TaskMaster: a prototype graphical user interface to a schedule optimization model
Banham, Stephen R.
1990-01-01
Approved for public release, distribution is unlimited This thesis investigates the use of current graphical interface techniques to build more effective computer-user interfaces to Operations Research (OR) schedule optimization models. The design is directed at the scheduling decision maker who possesses limited OR experience. The feasibility and validity of building an interface for this kind of user is demonstrated in the development of a prototype graphical user interface called TaskMa...
Cloud Service Scheduling Algorithm Research and Optimization
Directory of Open Access Journals (Sweden)
Hongyan Cui
2017-01-01
Full Text Available We propose a cloud service scheduling model that is referred to as the Task Scheduling System (TSS. In the user module, the process time of each task is in accordance with a general distribution. In the task scheduling module, we take a weighted sum of makespan and flowtime as the objective function and use an Ant Colony Optimization (ACO and a Genetic Algorithm (GA to solve the problem of cloud task scheduling. Simulation results show that the convergence speed and output performance of our Genetic Algorithm-Chaos Ant Colony Optimization (GA-CACO are optimal.
Sharp, Emily; Shih Dennis, Minyi
2017-01-01
This study used a multiple probe across participants design to examine the effects of a model drawing strategy (MDS) intervention package on fraction comparing and ordering word problem-solving performance of three Grade 4 students. MDS is a form of cognitive strategy instruction for teaching word problem solving that includes explicit instruction…
CQPSO scheduling algorithm for heterogeneous multi-core DAG task model
Zhai, Wenzheng; Hu, Yue-Li; Ran, Feng
2017-07-01
Efficient task scheduling is critical to achieve high performance in a heterogeneous multi-core computing environment. The paper focuses on the heterogeneous multi-core directed acyclic graph (DAG) task model and proposes a novel task scheduling method based on an improved chaotic quantum-behaved particle swarm optimization (CQPSO) algorithm. A task priority scheduling list was built. A processor with minimum cumulative earliest finish time (EFT) was acted as the object of the first task assignment. The task precedence relationships were satisfied and the total execution time of all tasks was minimized. The experimental results show that the proposed algorithm has the advantage of optimization abilities, simple and feasible, fast convergence, and can be applied to the task scheduling optimization for other heterogeneous and distributed environment.
A heuristic model for risk and cost impacts of plant outage maintenance schedule
International Nuclear Information System (INIS)
Mohammad Hadi Hadavi, S.
2009-01-01
Cost and risk are two major competing criteria in maintenance optimization problems. If a plant is forced to shutdown because of accident or fear of accident happening, beside loss of revenue, it causes damage to the credibility and reputation of the business operation. In this paper a heuristic model for incorporating three compelling optimization criteria (i.e., risk, cost, and loss) into a single evaluation function is proposed. Such a model could be used in any evaluation engine of outage maintenance schedule optimizer. It is attempted to make the model realistic and to address the ongoing challenges facing a schedule planner in a simple and commonly understandable fashion. Two simple competing schedules for the NPP feedwater system are examined against the model. The results show that while the model successfully addresses the current challenges for outage maintenance optimization, it properly demonstrates the dynamics of schedule in regards to risk, cost, and losses endured by maintenance schedule, particularly when prolonged outage and lack of maintenance for equipments in need of urgent care are of concern.
A genetic algorithm-based job scheduling model for big data analytics.
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.
Solving the nuclear shell model with an algebraic method
International Nuclear Information System (INIS)
Feng, D.H.; Pan, X.W.; Guidry, M.
1997-01-01
We illustrate algebraic methods in the nuclear shell model through a concrete example, the fermion dynamical symmetry model (FDSM). We use this model to introduce important concepts such as dynamical symmetry, symmetry breaking, effective symmetry, and diagonalization within a higher-symmetry basis. (orig.)
A new neural network model for solving random interval linear programming problems.
Arjmandzadeh, Ziba; Safi, Mohammadreza; Nazemi, Alireza
2017-05-01
This paper presents a neural network model for solving random interval linear programming problems. The original problem involving random interval variable coefficients is first transformed into an equivalent convex second order cone programming problem. A neural network model is then constructed for solving the obtained convex second order cone problem. Employing Lyapunov function approach, it is also shown that the proposed neural network model is stable in the sense of Lyapunov and it is globally convergent to an exact satisfactory solution of the original problem. Several illustrative examples are solved in support of this technique. Copyright © 2017 Elsevier Ltd. All rights reserved.
An instrumental electrode model for solving EIT forward problems.
Zhang, Weida; Li, David
2014-10-01
An instrumental electrode model (IEM) capable of describing the performance of electrical impedance tomography (EIT) systems in the MHz frequency range has been proposed. Compared with the commonly used Complete Electrode Model (CEM), which assumes ideal front-end interfaces, the proposed model considers the effects of non-ideal components in the front-end circuits. This introduces an extra boundary condition in the forward model and offers a more accurate modelling for EIT systems. We have demonstrated its performance using simple geometry structures and compared the results with the CEM and full Maxwell methods. The IEM can provide a significantly more accurate approximation than the CEM in the MHz frequency range, where the full Maxwell methods are favoured over the quasi-static approximation. The improved electrode model will facilitate the future characterization and front-end design of real-world EIT systems.
Modeling of capacitated transportation systems for integral scheduling
Ebben, Mark; van der Heijden, Matthijs C.; Hurink, Johann L.; Schutten, Johannes M.J.
2003-01-01
Motivated by a planned automated cargo transportation network, we consider transportation problems in which the finite capacity of resources has to be taken into account. We present a flexible modeling methodology which allows to construct, evaluate, and improve feasible solutions. The modeling is
Modeling of capacitated transportation systems for integral scheduling
Ebben, Mark; van der Heijden, Matthijs C.; Hurink, Johann L.; Schutten, Johannes M.J.
2003-01-01
Motivated by a planned automated cargo transportation network, we consider transportation problems in which the finite capacity of resources has to be taken nto account. We present a flexible modeling methodology which allows to construct, evaluate, and improve feasible solutions. The modeling is
Nasution, M. L.; Yerizon, Y.; Gusmiyanti, R.
2018-04-01
One of the purpose mathematic learning is to develop problem solving abilities. Problem solving is obtained through experience in questioning non-routine. Improving students’ mathematical problem-solving abilities required an appropriate strategy in learning activities one of them is models problem based learning (PBL). Thus, the purpose of this research is to determine whether the problem solving abilities of mathematical students’ who learn to use PBL better than on the ability of students’ mathematical problem solving by applying conventional learning. This research included quasi experiment with static group design and population is students class XI MIA SMAN 1 Lubuk Alung. Class experiment in the class XI MIA 5 and class control in the class XI MIA 6. The instrument of final test students’ mathematical problem solving used essay form. The result of data final test in analyzed with t-test. The result is students’ mathematical problem solving abilities with PBL better then on the ability of students’ mathematical problem solving by applying conventional learning. It’s seen from the high percentage achieved by the group of students who learn to use PBL for each indicator of students’ mathematical problem solving.
Directory of Open Access Journals (Sweden)
Ahmad Zeraatkar Moghaddam
2012-01-01
Full Text Available This paper presents a mathematical model for the problem of minimizing the maximum lateness on a single machine when the deteriorated jobs are delivered to each customer in various size batches. In reality, this issue may happen within a supply chain in which delivering goods to customers entails cost. Under such situation, keeping completed jobs to deliver in batches may result in reducing delivery costs. In literature review of batch scheduling, minimizing the maximum lateness is known as NP-Hard problem; therefore the present issue aiming at minimizing the costs of delivering, in addition to the aforementioned objective function, remains an NP-Hard problem. In order to solve the proposed model, a Simulation annealing meta-heuristic is used, where the parameters are calibrated by Taguchi approach and the results are compared to the global optimal values generated by Lingo 10 software. Furthermore, in order to check the efficiency of proposed method to solve larger scales of problem, a lower bound is generated. The results are also analyzed based on the effective factors of the problem. Computational study validates the efficiency and the accuracy of the presented model.
Evaluating to Solve Educational Problems: An Alternative Model.
Friedman, Myles I.; Anderson, Lorin W.
1979-01-01
A 19-step general evaluation model is described through its four stages: identifying problems, prescribing program solutions, evaluating the operation of the program, and evaluating the effectiveness of the model. The role of the evaluator in decision making is also explored. (RAO)
A Framework for Uplink Intercell Interference Modeling with Channel-Based Scheduling
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.
International Nuclear Information System (INIS)
Ramasubramaniam, M; Mathirajan, M
2013-01-01
The paper addresses the problem scheduling a batch processing machine with multiple incompatible job families, non-identical job dimensions, non-identical job sizes and non-agreeable release dates to minimize makespan. The research problem is solved by proposing a mixed integer programming model that appropriately takes into account the parameters considered in the problem. The proposed is validated using a numerical example. The experiment conducted show that the model can pose significant difficulties in solving the large scale instances. The paper concludes by giving the scope for future work and some alternative approaches one can use for solving these class of problems.
Optimizing Intermodal Train Schedules with a Design Balanced Network Design Model
DEFF Research Database (Denmark)
Pedersen, Michael Berliner; Crainic, Teodor Gabriel
We present a modeling approach for optimizing intermodal trains schedules based on an infrastructure divided into time-dependent train paths. The formulation can be generalized to a capacitated multi commodity network design model with additional design balance constraints. We present a Tabu Search...
Modeling the violation of reward maximization and invariance in reinforcement schedules.
Directory of Open Access Journals (Sweden)
Giancarlo La Camera
2008-08-01
Full Text Available It is often assumed that animals and people adjust their behavior to maximize reward acquisition. In visually cued reinforcement schedules, monkeys make errors in trials that are not immediately rewarded, despite having to repeat error trials. Here we show that error rates are typically smaller in trials equally distant from reward but belonging to longer schedules (referred to as "schedule length effect". This violates the principles of reward maximization and invariance and cannot be predicted by the standard methods of Reinforcement Learning, such as the method of temporal differences. We develop a heuristic model that accounts for all of the properties of the behavior in the reinforcement schedule task but whose predictions are not different from those of the standard temporal difference model in choice tasks. In the modification of temporal difference learning introduced here, the effect of schedule length emerges spontaneously from the sensitivity to the immediately preceding trial. We also introduce a policy for general Markov Decision Processes, where the decision made at each node is conditioned on the motivation to perform an instrumental action, and show that the application of our model to the reinforcement schedule task and the choice task are special cases of this general theoretical framework. Within this framework, Reinforcement Learning can approach contextual learning with the mixture of empirical findings and principled assumptions that seem to coexist in the best descriptions of animal behavior. As examples, we discuss two phenomena observed in humans that often derive from the violation of the principle of invariance: "framing," wherein equivalent options are treated differently depending on the context in which they are presented, and the "sunk cost" effect, the greater tendency to continue an endeavor once an investment in money, effort, or time has been made. The schedule length effect might be a manifestation of these
Solving cross-disciplinary problems by mathematical modelling
Panfilov, D. A.; Romanchikov, V. V.; Krupin, K. N.
2018-03-01
The article deals with the creation of a human tibia 3D model by means of “Autodesk Revit-2016” PC based on tomogram data. The model was imported into “Lira- SAPR2013 R4” software system. To assess the possibility of education and the nature of bone fracture (and their visualization), the Finite Element Analysis (FEA) method was used. The geometric parameters of the BBK model corresponded to the physical parameters of the individual. The compact plate different thickness is modeled by rigidity properties of the finite elements in accordance with the parameters on the roentgenogram. The BBK model included parameters of the outer compact plate and the spongy substance having a more developed structure of the epiphysic region. In the “Lira-SAPR2013 R4” software system, mathematical modeling of the traumatic effect was carried out and the analysis of the stress-strain state of the finite element model of the tibia was made to assess fracture conditions.
A method to solve the aircraft magnetic field model basing on geomagnetic environment simulation
International Nuclear Information System (INIS)
Lin, Chunsheng; Zhou, Jian-jun; Yang, Zhen-yu
2015-01-01
In aeromagnetic survey, it is difficult to solve the aircraft magnetic field model by flying for some unman controlled or disposable aircrafts. So a model solving method on the ground is proposed. The method simulates the geomagnetic environment where the aircraft is flying and creates the background magnetic field samples which is the same as the magnetic field arose by aircraft’s maneuvering. Then the aircraft magnetic field model can be solved by collecting the magnetic field samples. The method to simulate the magnetic environment and the method to control the errors are presented as well. Finally, an experiment is done for verification. The result shows that the model solving precision and stability by the method is well. The calculated model parameters by the method in one district can be used in worldwide districts as well. - Highlights: • A method to solve the aircraft magnetic field model on the ground is proposed. • The method solves the model by simulating dynamic geomagnetic environment as in the real flying. • The way to control the error of the method was analyzed. • An experiment is done for verification
A note on a model for quay crane scheduling with non-crossing constraints
DEFF Research Database (Denmark)
Santini, Alberto; Friberg, Henrik Alsing; Røpke, Stefan
2015-01-01
This article studies the quay crane scheduling problem with non-crossing constraints, which is an operational problem that arises in container terminals. An enhancement to a mixed integer programming model for the problem is proposed and a new class of valid inequalities is introduced. Computatio......This article studies the quay crane scheduling problem with non-crossing constraints, which is an operational problem that arises in container terminals. An enhancement to a mixed integer programming model for the problem is proposed and a new class of valid inequalities is introduced...
de Guzman, Niño Jose P.; Belecina, Rene R.
2012-01-01
The teaching of mathematics involves problem solving skills which prove to be difficult on the part of the pupils due to misrepresentation of the word problems. Oftentimes, pupils tend to represent the phrase "more than" as addition and the word difference as "- ". This paper aims to address the problem solving skills of grade…
Stamovlasis, Dimitrios; Tsaparlis, Georgios
2012-01-01
In this study, we test an information-processing model (IPM) of problem solving in science education, namely the working memory overload model, by applying catastrophe theory. Changes in students' achievement were modeled as discontinuities within a cusp catastrophe model, where working memory capacity was implemented as asymmetry and the degree…
Reliable gain-scheduled control of discrete-time systems and its application to CSTR model
Sakthivel, R.; Selvi, S.; Mathiyalagan, K.; Shi, Y.
2016-10-01
This paper is focused on reliable gain-scheduled controller design for a class of discrete-time systems with randomly occurring nonlinearities and actuator fault. Further, the nonlinearity in the system model is assumed to occur randomly according to a Bernoulli distribution with measurable time-varying probability in real time. The main purpose of this paper is to design a gain-scheduled controller by implementing a probability-dependent Lyapunov function and linear matrix inequality (LMI) approach such that the closed-loop discrete-time system is stochastically stable for all admissible randomly occurring nonlinearities. The existence conditions for the reliable controller is formulated in terms of LMI constraints. Finally, the proposed reliable gain-scheduled control scheme is applied on continuously stirred tank reactor model to demonstrate the effectiveness and applicability of the proposed design technique.
Aspects if stochastic models for short-term hydropower scheduling and bidding
Energy Technology Data Exchange (ETDEWEB)
Belsnes, Michael Martin [Sintef Energy, Trondheim (Norway); Follestad, Turid [Sintef Energy, Trondheim (Norway); Wolfgang, Ove [Sintef Energy, Trondheim (Norway); Fosso, Olav B. [Dep. of electric power engineering NTNU, Trondheim (Norway)
2012-07-01
This report discusses challenges met when turning from deterministic to stochastic decision support models for short-term hydropower scheduling and bidding. The report describes characteristics of the short-term scheduling and bidding problem, different market and bidding strategies, and how a stochastic optimization model can be formulated. A review of approaches for stochastic short-term modelling and stochastic modelling for the input variables inflow and market prices is given. The report discusses methods for approximating the predictive distribution of uncertain variables by scenario trees. Benefits of using a stochastic over a deterministic model are illustrated by a case study, where increased profit is obtained to a varying degree depending on the reservoir filling and price structure. Finally, an approach for assessing the effect of using a size restricted scenario tree to approximate the predictive distribution for stochastic input variables is described. The report is a summary of the findings of Work package 1 of the research project #Left Double Quotation Mark#Optimal short-term scheduling of wind and hydro resources#Right Double Quotation Mark#. The project aims at developing a prototype for an operational stochastic short-term scheduling model. Based on the investigations summarized in the report, it is concluded that using a deterministic equivalent formulation of the stochastic optimization problem is convenient and sufficient for obtaining a working prototype. (author)
Solving large linear systems in an implicit thermohaline ocean model
de Niet, Arie Christiaan
2007-01-01
The climate on earth is largely determined by the global ocean circulation. Hence it is important to predict how the flow will react to perturbation by for example melting icecaps. To answer questions about the stability of the global ocean flow, a computer model has been developed that is able to
Finding Deadlocks of Event-B Models by Constraint Solving
DEFF Research Database (Denmark)
Hallerstede, Stefan; Leuschel, Michael
we propose a constraint-based approach to nding deadlocks employing the ProB constraint solver to nd values for the constants and variables of formal models that describe a deadlocking state. We discuss the principles of the technique implemented in ProB's Prolog kernel and present some results...
Solving vertical transport and chemistry in air pollution models
Berkvens, P.J.F.; Bochev, M.A.; Krol, M.C.; Peters, W.; Verwer, J.G.; Chock, David P.; Carmichael, Gregory R.; Brick, Patricia
2002-01-01
For the time integration of stiff transport-chemistry problems from air pollution modelling, standard ODE solvers are not feasible due to the large number of species and the 3D nature. The popular alternative, standard operator splitting, introduces artificial transients for short-lived species.
Solving Vertical Transport and Chemistry in Air Pollution Models
Berkvens, P.J.F.; Bochev, M.A.; Verwer, J.G.; Krol, M.C.; Peters, W.
For the time integration of stiff transport-chemistry problems from air pollution modelling, standard ODE solvers are not feasible due to the large number of species and the 3D nature. The popular alternative, standard operator splitting, introduces artificial transients for short-lived species.
Mathematical model for scheduling irrigation for swamp rice in Port ...
African Journals Online (AJOL)
While the mother model indicated that the planted crops will be under severe water stress because the values of their d2 were below the allowable range of water depletion except in weeks 1,7,10,16 and 17 with their d2 values to be; 178.50mm, 181.47mm, 162.11mm, 198.80mm and 187.60mm respectively. Water ...
Discrete gradient methods for solving variational image regularisation models
International Nuclear Information System (INIS)
Grimm, V; McLachlan, Robert I; McLaren, David I; Quispel, G R W; Schönlieb, C-B
2017-01-01
Discrete gradient methods are well-known methods of geometric numerical integration, which preserve the dissipation of gradient systems. In this paper we show that this property of discrete gradient methods can be interesting in the context of variational models for image processing, that is where the processed image is computed as a minimiser of an energy functional. Numerical schemes for computing minimisers of such energies are desired to inherit the dissipative property of the gradient system associated to the energy and consequently guarantee a monotonic decrease of the energy along iterations, avoiding situations in which more computational work might lead to less optimal solutions. Under appropriate smoothness assumptions on the energy functional we prove that discrete gradient methods guarantee a monotonic decrease of the energy towards stationary states, and we promote their use in image processing by exhibiting experiments with convex and non-convex variational models for image deblurring, denoising, and inpainting. (paper)
Solar energy in buildings solved by building information modeling
Chudikova, B.; Faltejsek, M.
2018-03-01
Building lead us to use renewable energy sources for all types of buildings. The use of solar energy is the alternatives that can be applied in a good ratio of space, price, and resultant benefits. Building Information Modelling is a modern and effective way of dealing with buildings with regard to all aspects of the life cycle. The basis is careful planning and simulation in the pre-investment phase, where it is possible to determine the effective result and influence the lifetime of the building and the cost of its operation. By simulating, analysing and insert a building model into its future environment where climate conditions and surrounding buildings play a role, it is possible to predict the usability of the solar energy and establish an ideal model. Solar systems also very affect the internal layout of buildings. Pre-investment phase analysis, with a view to future aspects, will ensure that the resulting building will be both low-energy and environmentally friendly.
Directory of Open Access Journals (Sweden)
Shayna Stein
2018-01-01
Full Text Available Human primary glioblastomas (GBM often harbor mutations within the epidermal growth factor receptor (EGFR. Treatment of EGFR-mutant GBM cell lines with the EGFR/HER2 tyrosine kinase inhibitor lapatinib can effectively induce cell death in these models. However, EGFR inhibitors have shown little efficacy in the clinic, partly because of inappropriate dosing. Here, we developed a computational approach to model the in vitro cellular dynamics of the EGFR-mutant cell line SF268 in response to different lapatinib concentrations and dosing schedules. We then used this approach to identify an effective treatment strategy within the clinical toxicity limits of lapatinib, and developed a partial differential equation modeling approach to study the in vivo GBM treatment response by taking into account the heterogeneous and diffusive nature of the disease. Despite the inability of lapatinib to induce tumor regressions with a continuous daily schedule, our modeling approach consistently predicts that continuous dosing remains the best clinically feasible strategy for slowing down tumor growth and lowering overall tumor burden, compared to pulsatile schedules currently known to be tolerated, even when considering drug resistance, reduced lapatinib tumor concentrations due to the blood brain barrier, and the phenotypic switch from proliferative to migratory cell phenotypes that occurs in hypoxic microenvironments. Our mathematical modeling and statistical analysis platform provides a rational method for comparing treatment schedules in search for optimal dosing strategies for glioblastoma and other cancer types.
Solving Defender-Attacker-Defender Models for Infrastructure Defense
2011-01-01
persons]; bpp is the total supply of travelers originating at p; cdij length of arc (i, j)∈A under defense option d [kilometers]; qdij “equivalent travel...ensure that all bpp travelers originating at each p∈N arrive at appropriate destinations. The second set of constraints in Y (w) requires that all...1. Node data for DAD modeling of the Königsberg transportation network. Nodes p∈N Supply bpp (persons) Demand −bpi (persons) Aa, Ab, Ac, Ae, 200
Energy Technology Data Exchange (ETDEWEB)
Jafarzadeh, Hassan; Moradinasab, Nazanin; Gerami, Ali
2017-07-01
Adjusted discrete Multi-Objective Invasive Weed Optimization (DMOIWO) algorithm, which uses fuzzy dominant approach for ordering, has been proposed to solve No-wait two-stage flexible flow shop scheduling problem. Design/methodology/approach: No-wait two-stage flexible flow shop scheduling problem by considering sequence-dependent setup times and probable rework in both stations, different ready times for all jobs and rework times for both stations as well as unrelated parallel machines with regards to the simultaneous minimization of maximum job completion time and average latency functions have been investigated in a multi-objective manner. In this study, the parameter setting has been carried out using Taguchi Method based on the quality indicator for beater performance of the algorithm. Findings: The results of this algorithm have been compared with those of conventional, multi-objective algorithms to show the better performance of the proposed algorithm. The results clearly indicated the greater performance of the proposed algorithm. Originality/value: This study provides an efficient method for solving multi objective no-wait two-stage flexible flow shop scheduling problem by considering sequence-dependent setup times, probable rework in both stations, different ready times for all jobs, rework times for both stations and unrelated parallel machines which are the real constraints.
International Nuclear Information System (INIS)
Jafarzadeh, Hassan; Moradinasab, Nazanin; Gerami, Ali
2017-01-01
Adjusted discrete Multi-Objective Invasive Weed Optimization (DMOIWO) algorithm, which uses fuzzy dominant approach for ordering, has been proposed to solve No-wait two-stage flexible flow shop scheduling problem. Design/methodology/approach: No-wait two-stage flexible flow shop scheduling problem by considering sequence-dependent setup times and probable rework in both stations, different ready times for all jobs and rework times for both stations as well as unrelated parallel machines with regards to the simultaneous minimization of maximum job completion time and average latency functions have been investigated in a multi-objective manner. In this study, the parameter setting has been carried out using Taguchi Method based on the quality indicator for beater performance of the algorithm. Findings: The results of this algorithm have been compared with those of conventional, multi-objective algorithms to show the better performance of the proposed algorithm. The results clearly indicated the greater performance of the proposed algorithm. Originality/value: This study provides an efficient method for solving multi objective no-wait two-stage flexible flow shop scheduling problem by considering sequence-dependent setup times, probable rework in both stations, different ready times for all jobs, rework times for both stations and unrelated parallel machines which are the real constraints.
Solving vertical transport and chemistry in air pollution models
International Nuclear Information System (INIS)
Berkvens, P.J.F.; Botchev, M.A.; Verwer, J.G.; Krol, M.C.; Peters, W.
2000-01-01
For the time integration of stiff transport-chemistry problems from air pollution modelling, standard ODE solvers are not feasible due to the large number of species and the 3D nature. The popular alternative, standard operator splitting, introduces artificial transients for short-lived species. This complicates the chemistry solution, easily causing large errors for such species. In the framework of an operational global air pollution model, we focus on the problem formed by chemistry and vertical transport, which is based on diffusion, cloud-related vertical winds, and wet deposition. Its specific nature leads to full Jacobian matrices, ruling out standard implicit integration. We compare Strang operator splitting with two alternatives: source splitting and an (unsplit) Rosenbrock method with approximate matrix factorization, all having equal computational cost. The comparison is performed with real data. All methods are applied with half-hour time steps, and give good accuracies. Rosenbrock is the most accurate, and source splitting is more accurate than Strang splitting. Splitting errors concentrate in short-lived species sensitive to solar radiation and species with strong emissions and depositions. 30 refs
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.
Improving Students’ Scientific Reasoning and Problem-Solving Skills by The 5E Learning Model
Directory of Open Access Journals (Sweden)
Sri Mulyani Endang Susilowati
2017-12-01
Full Text Available Biology learning in MA (Madrasah Aliyah Khas Kempek was still dominated by teacher with low students’ involvement. This study would analyze the effectiveness of the 5E (Engagement, Exploration, Explanation, Elaboration, Evaluation learning model in improving scientific knowledge and problems solving. It also explained the relationship between students’ scientific reasoning with their problem-solving abilities. This was a pre-experimental research with one group pre-test post-test. Sixty students of MA Khas Kempek from XI MIA 3 and XI MIA 4 involved in this study. The learning outcome of the students was collected by the test of reasoning and problem-solving. The results showed that the rises of students’ scientific reasoning ability were 69.77% for XI MIA 3 and 66.27% for XI MIA 4, in the medium category. The problem-solving skills were 63.40% for XI MIA 3, 61.67% for XI MIA 4, and classified in the moderate category. The simple regression test found a linear correlation between students’ scientific reasoning and problem-solving ability. This study affirms that reasoning ability is needed in problem-solving. It is found that application of 5E learning model was effective to improve scientific reasoning and problem-solving ability of students.
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....
Game theory at work: OR models and algorythms to solve multi-actor heterogeneous decision problems
Sáiz Pérez, M.E.
2007-01-01
Key words: Game theory, operations research, optimisation methods, algorithms. The objective of this thesis is to explore the potential of combining Game Theory (GT) models with Operations Research (OR) modelling. This includes development of algorithms to solve these complex OR models for
How, when, and for what reasons does land use modelling contribute to societal problem solving?
Sterk, B.; Ittersum, van M.K.; Leeuwis, C.
2011-01-01
This paper reports and reflects on the contributions of land use models to societal problem solving. Its purpose is to inform model development and application and thus to increase chances for societal benefit of the modelling work. The key question is: How, when, and for what reasons does land use
Investigating and Developing Engineering Students' Mathematical Modelling and Problem-Solving Skills
Wedelin, Dag; Adawi, Tom; Jahan, Tabassum; Andersson, Sven
2015-01-01
How do engineering students approach mathematical modelling problems and how can they learn to deal with such problems? In the context of a course in mathematical modelling and problem solving, and using a qualitative case study approach, we found that the students had little prior experience of mathematical modelling. They were also inexperienced…
Directory of Open Access Journals (Sweden)
Lianfei Yu
2017-01-01
Full Text Available Efficient scheduling for the supporting operations of aircrafts in flight deck is critical to the aircraft carrier, and even several seconds’ improvement may lead to totally converse outcome of a battle. In the paper, we ameliorate the supporting operations of carrier-based aircrafts and investigate three simultaneous operation relationships during the supporting process, including precedence constraints, parallel operations, and sequence flexibility. Furthermore, multifunctional aircrafts have to take off synergistically and participate in a combat cooperatively. However, their takeoff order must be restrictively prioritized during the scheduling period accorded by certain operational regulations. To efficiently prioritize the takeoff order while minimizing the total time budget on the whole takeoff duration, we propose a novel mixed integer liner programming formulation (MILP for the flight deck scheduling problem. Motivated by the hardness of MILP, we design an improved differential evolution algorithm combined with typical local search strategies to improve computational efficiency. We numerically compare the performance of our algorithm with the classical genetic algorithm and normal differential evolution algorithm and the results show that our algorithm obtains better scheduling schemes that can meet both the operational relations and the takeoff priority requirements.
DEFF Research Database (Denmark)
Yang, Jingwei; Zhang, Ning; Kang, Chongqing
2017-01-01
The rapid deployment of gas-fired generating units makes the power system more vulnerable to failures in the natural gas system. To reduce the risk of gas system failure and to guarantee the security of power system operation, it is necessary to take the security constraints of natural gas...... accurately, they are hard to be embedded into the power system scheduling model, which consists of algebraic equations and inequations. This paper addresses this dilemma by proposing an algebraic transient model of natural gas network which is similar to the branch-node model of power network. Based...... pipelines into account in the day-ahead power generation scheduling model. However, the minute- and hour-level dynamic characteristics of gas systems prevents an accurate decision-making simply with the steady-state gas flow model. Although the partial differential equations depict the dynamics of gas flow...
Hemmati, Reza; Saboori, Hedayat
2016-05-01
Energy storage systems (ESSs) have experienced a very rapid growth in recent years and are expected to be a promising tool in order to improving power system reliability and being economically efficient. The ESSs possess many potential benefits in various areas in the electric power systems. One of the main benefits of an ESS, especially a bulk unit, relies on smoothing the load pattern by decreasing on-peak and increasing off-peak loads, known as load leveling. These devices require new methods and tools in order to model and optimize their effects in the power system studies. In this respect, this paper will model bulk ESSs based on the several technical characteristics, introduce the proposed model in the thermal unit commitment (UC) problem, and analyze it with respect to the various sensitive parameters. The technical limitations of the thermal units and transmission network constraints are also considered in the model. The proposed model is a Mixed Integer Linear Programming (MILP) which can be easily solved by strong commercial solvers (for instance CPLEX) and it is appropriate to be used in the practical large scale networks. The results of implementing the proposed model on a test system reveal that proper load leveling through optimum storage scheduling leads to considerable operation cost reduction with respect to the storage system characteristics.
Hemmati, Reza; Saboori, Hedayat
2016-01-01
Energy storage systems (ESSs) have experienced a very rapid growth in recent years and are expected to be a promising tool in order to improving power system reliability and being economically efficient. The ESSs possess many potential benefits in various areas in the electric power systems. One of the main benefits of an ESS, especially a bulk unit, relies on smoothing the load pattern by decreasing on-peak and increasing off-peak loads, known as load leveling. These devices require new methods and tools in order to model and optimize their effects in the power system studies. In this respect, this paper will model bulk ESSs based on the several technical characteristics, introduce the proposed model in the thermal unit commitment (UC) problem, and analyze it with respect to the various sensitive parameters. The technical limitations of the thermal units and transmission network constraints are also considered in the model. The proposed model is a Mixed Integer Linear Programming (MILP) which can be easily solved by strong commercial solvers (for instance CPLEX) and it is appropriate to be used in the practical large scale networks. The results of implementing the proposed model on a test system reveal that proper load leveling through optimum storage scheduling leads to considerable operation cost reduction with respect to the storage system characteristics. PMID:27222741
Performance comparison of some evolutionary algorithms on job shop scheduling problems
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.
The Effect of Problem Solving and Problem Posing Models and Innate Ability to Students Achievement
Directory of Open Access Journals (Sweden)
Ratna Kartika Irawati
2015-04-01
Full Text Available Pengaruh Model Problem Solving dan Problem Posing serta Kemampuan Awal terhadap Hasil Belajar Siswa Abstract: Chemistry concepts understanding features abstract quality and requires higher order thinking skills. Yet, the learning on chemistry has not boost the higher order thinking skills of the students. The use of the learning model of Problem Solving and Problem Posing in observing the innate ability of the student is expected to resolve the issue. This study aims to determine the learning model which is effective to improve the study of the student with different level of innate ability. This study used the quasi-experimental design. The research data used in this research is the quiz/test of the class which consist of 14 multiple choice questions and 5 essay questions. The data analysis used is ANOVA Two Ways. The results showed that Problem Posing is more effective to improve the student compared to Problem Solving, students with high level of innate ability have better outcomes in learning rather than the students with low level of innate ability after being applied with the Problem solving and Problem posing model, further, Problem Solving and Problem Posing is more suitable to be applied to the students with high level of innate ability. Key Words: problem solving, problem posing, higher order thinking skills, innate ability, learning outcomes Abstrak: Pemahaman konsep-konsep kimia yang bersifat abstrak membutuhkan keterampilan berpikir tingkat tinggi. Pembelajaran kimia belum mendorong siswa melakukan keterampilan berpikir tingkat tinggi. Penggunaan model pembelajaran Problem Solving dan Problem Posing dengan memperhatikan kemampuan awal siswa diduga dapat mengatasi masalah tersebut. Penelitian ini bertujuan untuk mengetahui model pembelajaran yang efektif dalam meningkatkan hasil belajar dengan kemampuan awal siswa yang berbeda. Penelitian ini menggunakan rancangan eksperimen semu. Data penelitian menggunakan tes hasil belajar
A Statistical Model for Uplink Intercell Interference with Power Adaptation and Greedy Scheduling
Tabassum, Hina
2012-10-03
This paper deals with the statistical modeling of uplink inter-cell interference (ICI) considering greedy scheduling with power adaptation based on channel conditions. The derived model is implicitly generalized for any kind of shadowing and fading environments. More precisely, we develop a generic model for the distribution of ICI based on the locations of the allocated users and their transmit powers. The derived model is utilized to evaluate important network performance metrics such as ergodic capacity, average fairness and average power preservation numerically. Monte-Carlo simulation details are included to support the analysis and show the accuracy of the derived expressions. In parallel to the literature, we show that greedy scheduling with power adaptation reduces the ICI, average power consumption of users, and enhances the average fairness among users, compared to the case without power adaptation. © 2012 IEEE.
A Statistical Model for Uplink Intercell Interference with Power Adaptation and Greedy Scheduling
Tabassum, Hina; Yilmaz, Ferkan; Dawy, Zaher; Alouini, Mohamed-Slim
2012-01-01
This paper deals with the statistical modeling of uplink inter-cell interference (ICI) considering greedy scheduling with power adaptation based on channel conditions. The derived model is implicitly generalized for any kind of shadowing and fading environments. More precisely, we develop a generic model for the distribution of ICI based on the locations of the allocated users and their transmit powers. The derived model is utilized to evaluate important network performance metrics such as ergodic capacity, average fairness and average power preservation numerically. Monte-Carlo simulation details are included to support the analysis and show the accuracy of the derived expressions. In parallel to the literature, we show that greedy scheduling with power adaptation reduces the ICI, average power consumption of users, and enhances the average fairness among users, compared to the case without power adaptation. © 2012 IEEE.
Use of model analysis to analyse Thai students’ attitudes and approaches to physics problem solving
Rakkapao, S.; Prasitpong, S.
2018-03-01
This study applies the model analysis technique to explore the distribution of Thai students’ attitudes and approaches to physics problem solving and how those attitudes and approaches change as a result of different experiences in physics learning. We administered the Attitudes and Approaches to Problem Solving (AAPS) survey to over 700 Thai university students from five different levels, namely students entering science, first-year science students, and second-, third- and fourth-year physics students. We found that their inferred mental states were generally mixed. The largest gap between physics experts and all levels of the students was about the role of equations and formulas in physics problem solving, and in views towards difficult problems. Most participants of all levels believed that being able to handle the mathematics is the most important part of physics problem solving. Most students’ views did not change even though they gained experiences in physics learning.
Menshikh, V.; Samorokovskiy, A.; Avsentev, O.
2018-03-01
The mathematical model of optimizing the allocation of resources to reduce the time for management decisions and algorithms to solve the general problem of resource allocation. The optimization problem of choice of resources in organizational systems in order to reduce the total execution time of a job is solved. This problem is a complex three-level combinatorial problem, for the solving of which it is necessary to implement the solution to several specific problems: to estimate the duration of performing each action, depending on the number of performers within the group that performs this action; to estimate the total execution time of all actions depending on the quantitative composition of groups of performers; to find such a distribution of the existing resource of performers in groups to minimize the total execution time of all actions. In addition, algorithms to solve the general problem of resource allocation are proposed.
A mediational model of self-esteem and social problem-solving in anorexia nervosa.
Paterson, Gillian; Power, Kevin; Collin, Paula; Greirson, David; Yellowlees, Alex; Park, Katy
2011-01-01
Poor problem-solving and low self-esteem are frequently cited as significant factors in the development and maintenance of anorexia nervosa. The current study examines the multi-dimensional elements of these measures and postulates a model whereby self-esteem mediates the relationship between social problems-solving and anorexic pathology and considers the implications of this pathway. Fifty-five inpatients with a diagnosis of anorexia nervosa and 50 non-clinical controls completed three standardised multi-dimensional questionnaires pertaining to social problem-solving, self-esteem and eating pathology. Significant differences were yielded between clinical and non-clinical samples on all measures. Within the clinical group, elements of social problem-solving most significant to anorexic pathology were positive problem orientation, negative problem orientation and avoidance. Components of self-esteem most significant to anorexic pathology were eating, weight and shape concern but not eating restraint. The mediational model was upheld with social problem-solving impacting on anorexic pathology through the existence of low self-esteem. Problem orientation, that is, the cognitive processes of social problem-solving appear to be more significant than problem-solving methods in individuals with anorexia nervosa. Negative perceptions of eating, weight and shape appear to impact on low self-esteem but level of restriction does not. Finally, results indicate that self-esteem is a significant factor in the development and execution of positive or negative social problem-solving in individuals with anorexia nervosa by mediating the relationship between those two variables. Copyright © 2010 John Wiley & Sons, Ltd and Eating Disorders Association.
A Problem Solving Model for Use in Science Student Teacher Supervision.
Cavallo, Ann M. L.; Tice, Craig J.
1993-01-01
Describes and suggests the use of a problem-solving model that improves communication between student teachers and supervisors through the student teaching practicum. The aim of the model is to promote experimentation with various teaching techniques and to stimulate thinking among student teachers about their teaching experiences. (PR)
The Model Method: Singapore Children's Tool for Representing and Solving Algebraic Word Problems
Ng, Swee Fong; Lee, Kerry
2009-01-01
Solving arithmetic and algebraic word problems is a key component of the Singapore elementary mathematics curriculum. One heuristic taught, the model method, involves drawing a diagram to represent key information in the problem. We describe the model method and a three-phase theoretical framework supporting its use. We conducted 2 studies to…
Healthcare Scheduling by Data Mining: Literature Review and Future Directions
Directory of Open Access Journals (Sweden)
Maria M. Rinder
2012-01-01
Full Text Available This article presents a systematic literature review of the application of industrial engineering methods in healthcare scheduling, with a focus on the role of patient behavior in scheduling. Nine articles that used mathematical programming, data mining, genetic algorithms, and local searches for optimum schedules were obtained from an extensive search of literature. These methods are new approaches to solve the problems in healthcare scheduling. Some are adapted from areas such as manufacturing and transportation. Key findings from these studies include reduced time for scheduling, capability of solving more complex problems, and incorporation of more variables and constraints simultaneously than traditional scheduling methods. However, none of these methods modeled no-show and walk-ins patient behavior. Future research should include more variables related to patient and/or environment.
Real-Time Robust Adaptive Modeling and Scheduling for an Electronic Commerce Server
Du, Bing; Ruan, Chun
With the increasing importance and pervasiveness of Internet services, it is becoming a challenge for the proliferation of electronic commerce services to provide performance guarantees under extreme overload. This paper describes a real-time optimization modeling and scheduling approach for performance guarantee of electronic commerce servers. We show that an electronic commerce server may be simulated as a multi-tank system. A robust adaptive server model is subject to unknown additive load disturbances and uncertain model matching. Overload control techniques are based on adaptive admission control to achieve timing guarantees. We evaluate the performance of the model using a complex simulation that is subjected to varying model parameters and massive overload.
Two pricing methods for solving an integrated commercial fishery ...
African Journals Online (AJOL)
In this paper, we develop two novel pricing methods for solving an integer program. We demonstrate the methods by solving an integrated commercial fishery planning model (IFPM). In this problem, a fishery manager must schedule fishing trawlers (determine when and where the trawlers should go fishing, and when the ...
The triangle scheduling problem
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
Personnel scheduling using an integer programming model- an application at Avanti Blue-Nile Hotels.
Kassa, Biniyam Asmare; Tizazu, Anteneh Eshetu
2013-01-01
In this paper, we report perhaps a first of its kind application of management science in the Ethiopian hotel industry. Avanti Blue Nile Hotels, a newly established five star hotel in Bahir Dar, is the company for which we developed an integer programming model that determines an optimal weekly shift schedule for the Hotel's engineering department personnel while satisfying several constraints including weekly rest requirements per employee, rest requirements between working shifts per employee, required number of personnel per shift, and other constraints. The model is implemented on an excel solver routine. The model enables the company's personnel department management to develop a fair personnel schedule as needed and to effectively utilize personnel resources while satisfying several technical, legal and economic requirements. These encouraging achievements make us optimistic about the gains other Ethiopian organizations can amass by introducing management science approaches in their management planning and decision making systems.
Rosmartina
2011-01-01
Mathematical modeling is a complex mathematical activity, the teaching and learning of modeling and applications involves many aspects, of mathematical thinking and learning. Mathematical model is not use only in mathematics learning and natural sciences (such as physics, biology, earth science, meteorology and engineering) but also in the social sciences (such as economic, psychology, sociology and political science). Mathematical modeling in mathematical learning and problem solving involve...
Peningkatan Keterampilan Bertanya Dan Menjawab Pertanyaan Melalui Model Pembelajaran Problem Solving
Saputra, Rendi; Diawati, Chansyanah; Rudibyani, Ratu Betta
2013-01-01
The aim of this research is to describe the effectiveness of the learning model of problem solving in reaction rate concept to improving asking and answering question skill which includes the answering question and cite the example skill.Â The effectiveness of the learning model of problem solving in this research indicated the presence of n-Gain difference significant between the control and a experiment class.Â The population this research is all students of class XI Science SMAN 7 Bandar...
Galindo-Garre, Francisca; Hidalgo, María Dolores; Guilera, Georgina; Pino, Oscar; Rojo, J Emilio; Gómez-Benito, Juana
2015-03-01
The World Health Organization Disability Assessment Schedule II (WHO-DAS II) is a multidimensional instrument developed for measuring disability. It comprises six domains (getting around, self-care, getting along with others, life activities and participation in society). The main purpose of this paper is the evaluation of the psychometric properties for each domain of the WHO-DAS II with parametric and non-parametric Item Response Theory (IRT) models. A secondary objective is to assess whether the WHO-DAS II items within each domain form a hierarchy of invariantly ordered severity indicators of disability. A sample of 352 patients with a schizophrenia spectrum disorder is used in this study. The 36 items WHO-DAS II was administered during the consultation. Partial Credit and Mokken scale models are used to study the psychometric properties of the questionnaire. The psychometric properties of the WHO-DAS II scale are satisfactory for all the domains. However, we identify a few items that do not discriminate satisfactorily between different levels of disability and cannot be invariantly ordered in the scale. In conclusion the WHO-DAS II can be used to assess overall disability in patients with schizophrenia, but some domains are too general to assess functionality in these patients because they contain items that are not applicable to this pathology. Copyright © 2014 John Wiley & Sons, Ltd.
Yulindar, A.; Setiawan, A.; Liliawati, W.
2018-05-01
This study aims to influence the enhancement of problem solving ability before and after learning using Real Engagement in Active Problem Solving (REAPS) model on the concept of heat transfer. The research method used is quantitative method with 35 high school students in Pontianak as sample. The result of problem solving ability of students is obtained through the test in the form of 3 description questions. The instrument has tested the validity by the expert judgment and field testing that obtained the validity value of 0.84. Based on data analysis, the value of N-Gain is 0.43 and the enhancement of students’ problem solving ability is in medium category. This was caused of students who are less accurate in calculating the results of answers and they also have limited time in doing the questions given.
Job shop scheduling model for non-identic machine with fixed delivery time to minimize tardiness
Kusuma, K. K.; Maruf, A.
2016-02-01
Scheduling non-identic machines problem with low utilization characteristic and fixed delivery time are frequent in manufacture industry. This paper propose a mathematical model to minimize total tardiness for non-identic machines in job shop environment. This model will be categorized as an integer linier programming model and using branch and bound algorithm as the solver method. We will use fixed delivery time as main constraint and different processing time to process a job. The result of this proposed model shows that the utilization of production machines can be increase with minimal tardiness using fixed delivery time as constraint.
Solving large test-day models by iteration on data and preconditioned conjugate gradient.
Lidauer, M; Strandén, I; Mäntysaari, E A; Pösö, J; Kettunen, A
1999-12-01
A preconditioned conjugate gradient method was implemented into an iteration on a program for data estimation of breeding values, and its convergence characteristics were studied. An algorithm was used as a reference in which one fixed effect was solved by Gauss-Seidel method, and other effects were solved by a second-order Jacobi method. Implementation of the preconditioned conjugate gradient required storing four vectors (size equal to number of unknowns in the mixed model equations) in random access memory and reading the data at each round of iteration. The preconditioner comprised diagonal blocks of the coefficient matrix. Comparison of algorithms was based on solutions of mixed model equations obtained by a single-trait animal model and a single-trait, random regression test-day model. Data sets for both models used milk yield records of primiparous Finnish dairy cows. Animal model data comprised 665,629 lactation milk yields and random regression test-day model data of 6,732,765 test-day milk yields. Both models included pedigree information of 1,099,622 animals. The animal model ¿random regression test-day model¿ required 122 ¿305¿ rounds of iteration to converge with the reference algorithm, but only 88 ¿149¿ were required with the preconditioned conjugate gradient. To solve the random regression test-day model with the preconditioned conjugate gradient required 237 megabytes of random access memory and took 14% of the computation time needed by the reference algorithm.
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.
Cognitive Work Analysis: Preliminary Data for a Model of Problem Solving Strategies
Rothmayer, Mark; Blue, Jennifer
2007-10-01
Investigations into problem solving strategies are part of the field of physics education research where investigators seek to improve physics instruction by conducting basic research of problem solving abilities among students, differences in knowledge representations between experts and novices, and how to transfer knowledge structures more effectively onto novices. We developed a new conceptual research tool in our laboratory, where we could potentially map the step by step flow of problem solving strategies among experts and novices. This model is derived from the theory of Cognitive Work Analysis, which is grounded in ecological psychology, and as far as we know it has never been applied to a knowledge domain like physics. We collected survey data from 140 undergraduates enrolled in an algebra based introductory physics course at Miami University as part of a larger study aimed to test the validity of the model. Preliminary data will be presented and discussed.
Directory of Open Access Journals (Sweden)
J.K. Jolayemi
2014-01-01
Full Text Available A zero-one mixed integer linear programming model is developed for the scheduling of projects under the condition of inflation and under penalty and reward arrangements. The effects of inflation on time-cost trade-off curves are illustrated and a modified approach to time-cost trade-off analysis presented. Numerical examples are given to illustrate the model and its properties. The examples show that misleading schedules and inaccurate project-cost estimates will be produced if the inflation factor is neglected in an environment of high inflation. They also show that award of penalty or bonus is a catalyst for early completion of a project, just as it can be expected.
Directory of Open Access Journals (Sweden)
Michael J. Pelosi
2014-12-01
Full Text Available Development teams and programmers must retain critical information about their work during work intervals and gaps in order to improve future performance when work resumes. Despite time lapses, project managers want to maximize coding efficiency and effectiveness. By developing a mathematically justified, practically useful, and computationally tractable quantitative and cognitive model of learning and memory retention, this study establishes calculations designed to maximize scheduling payoff and optimize developer efficiency and effectiveness.
Using the Multilayer Free-Surface Flow Model to Solve Wave Problems
Energy Technology Data Exchange (ETDEWEB)
Prokof’ev, V. A., E-mail: ProkofyevVA@vniig.ru [B. E. Vedeneev All-Russia Research Institute of Hydraulic Engineering (VNIIG) (Russian Federation)
2017-01-15
A method is presented for changing over from a single-layer shallow-water model to a multilayer model with hydrostatic pressure profile and, then, to a multilayer model with nonhydrostatic pressure profile. The method does not require complex procedures for solving the discrete Poisson’s equation and features high computation efficiency. The results of validating the algorithm against experimental data critical for the numerical dissipation of the numerical scheme are presented. Examples are considered.
Lu, Lingbo; Li, Jingshan; Gisler, Paula
2011-06-01
Radiology tests, such as MRI, CT-scan, X-ray and ultrasound, are cost intensive and insurance pre-approvals are necessary to get reimbursement. In some cases, tests may be denied for payments by insurance companies due to lack of pre-approvals, inaccurate or missing necessary information. This can lead to substantial revenue losses for the hospital. In this paper, we present a simulation study of a centralized scheduling process for outpatient radiology tests at a large community hospital (Central Baptist Hospital in Lexington, Kentucky). Based on analysis of the central scheduling process, a simulation model of information flow in the process has been developed. Using such a model, the root causes of financial losses associated with errors and omissions in this process were identified and analyzed, and their impacts were quantified. In addition, "what-if" analysis was conducted to identify potential process improvement strategies in the form of recommendations to the hospital leadership. Such a model provides a quantitative tool for continuous improvement and process control in radiology outpatient test scheduling process to reduce financial losses associated with process error. This method of analysis is also applicable to other departments in the hospital.
Liu, Weihua; Yang, Yi; Wang, Shuqing; Liu, Yang
2014-01-01
Order insertion often occurs in the scheduling process of logistics service supply chain (LSSC), which disturbs normal time scheduling especially in the environment of mass customization logistics service. This study analyses order similarity coefficient and order insertion operation process and then establishes an order insertion scheduling model of LSSC with service capacity and time factors considered. This model aims to minimize the average unit volume operation cost of logistics service integrator and maximize the average satisfaction degree of functional logistics service providers. In order to verify the viability and effectiveness of our model, a specific example is numerically analyzed. Some interesting conclusions are obtained. First, along with the increase of completion time delay coefficient permitted by customers, the possible inserting order volume first increases and then trends to be stable. Second, supply chain performance reaches the best when the volume of inserting order is equal to the surplus volume of the normal operation capacity in mass service process. Third, the larger the normal operation capacity in mass service process is, the bigger the possible inserting order's volume will be. Moreover, compared to increasing the completion time delay coefficient, improving the normal operation capacity of mass service process is more useful.
Directory of Open Access Journals (Sweden)
Li Dawei
2014-08-01
Full Text Available Servicing is applied periodically in practice with the aim of restoring the system state and prolonging the lifetime. It is generally seen as an imperfect maintenance action which has a chief influence on the maintenance strategy. In order to model the maintenance effect of servicing, this study analyzes the deterioration characteristics of system under scheduled servicing. And then the deterioration model is established from the failure mechanism by compound Poisson process. On the basis of the system damage value and failure mechanism, the failure rate refresh factor is proposed to describe the maintenance effect of servicing. A maintenance strategy is developed which combines the benefits of scheduled servicing and preventive maintenance. Then the optimization model is given to determine the optimal servicing period and preventive maintenance time, with an objective to minimize the system expected life-cycle cost per unit time and a constraint on system survival probability for the duration of mission time. Subject to mission time, it can control the ability of accomplishing the mission at any time so as to ensure the high dependability. An example of water pump rotor relating to scheduled servicing is introduced to illustrate the failure rate refresh factor and the proposed maintenance strategy. Compared with traditional methods, the numerical results show that the failure rate refresh factor can describe the maintenance effect of servicing more intuitively and objectively. It also demonstrates that this maintenance strategy can prolong the lifetime, reduce the total lifetime maintenance cost and guarantee the dependability of system.
Morin, Lisa L.; Watson, Silvana M. R.; Hester, Peggy; Raver, Sharon
2017-01-01
For students with mathematics difficulties (MD), math word problem solving is especially challenging. The purpose of this study was to examine the effects of a problem-solving strategy, bar model drawing, on the mathematical problem-solving skills of students with MD. The study extended previous research that suggested that schematic-based…
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...
Directory of Open Access Journals (Sweden)
Paweł Sitek
2016-01-01
Full Text Available This paper presents a hybrid method for modeling and solving supply chain optimization problems with soft, hard, and logical constraints. Ability to implement soft and logical constraints is a very important functionality for supply chain optimization models. Such constraints are particularly useful for modeling problems resulting from commercial agreements, contracts, competition, technology, safety, and environmental conditions. Two programming and solving environments, mathematical programming (MP and constraint logic programming (CLP, were combined in the hybrid method. This integration, hybridization, and the adequate multidimensional transformation of the problem (as a presolving method helped to substantially reduce the search space of combinatorial models for supply chain optimization problems. The operation research MP and declarative CLP, where constraints are modeled in different ways and different solving procedures are implemented, were linked together to use the strengths of both. This approach is particularly important for the decision and combinatorial optimization models with the objective function and constraints, there are many decision variables, and these are summed (common in manufacturing, supply chain management, project management, and logistic problems. The ECLiPSe system with Eplex library was proposed to implement a hybrid method. Additionally, the proposed hybrid transformed model is compared with the MILP-Mixed Integer Linear Programming model on the same data instances. For illustrative models, its use allowed finding optimal solutions eight to one hundred times faster and reducing the size of the combinatorial problem to a significant extent.
Hall, Kimberly R.; Rushing, Jeri Lynn; Khurshid, Ayesha
2011-01-01
Problem-focused interventions are considered to be one of the most effective group counseling strategies with adolescents. This article describes a problem-focused group counseling model, Solving Problems Together (SPT), that focuses on working with students who struggle with negative peer pressure. Adapted from the teaching philosophy of…
Große, Cornelia S.
2015-01-01
The application of mathematics to real-world problems is moving more and more in the focus of attention of mathematics education; however, many learners experience huge difficulties in relating "pure" mathematics to everyday contents. In order to solve "modeling problems", it is first necessary to find a transition from a…
Asymptotic solving method for sea-air coupled oscillator ENSO model
International Nuclear Information System (INIS)
Zhou Xian-Chun; Yao Jing-Sun; Mo Jia-Qi
2012-01-01
The ENSO is an interannual phenomenon involved in the tropical Pacific ocean-atmosphere interaction. In this article, we create an asymptotic solving method for the nonlinear system of the ENSO model. The asymptotic solution is obtained. And then we can furnish weather forecasts theoretically and other behaviors and rules for the atmosphere-ocean oscillator of the ENSO. (general)
Lee, Chwee Beng
2010-01-01
This study examines the interactions between problem solving and conceptual change in an elementary science class where students build system dynamic models as a form of problem representations. Through mostly qualitative findings, we illustrate the interplay of three emerging intervening conditions (epistemological belief, structural knowledge…
Energy Technology Data Exchange (ETDEWEB)
1979-01-01
The booklet presents the full text of 13 contributions to a Colloquium held at Karlsruhe in Sept. 1979. The main topics of the papers are the evaluation of mathematical models to solve flow problems in tide water, seas, rivers, groundwater and in the earth atmosphere. See further hints under relevant topics.
Probabilities and Predictions: Modeling the Development of Scientific Problem-Solving Skills
2005-01-01
The IMMEX (Interactive Multi-Media Exercises) Web-based problem set platform enables the online delivery of complex, multimedia simulations, the rapid collection of student performance data, and has already been used in several genetic simulations. The next step is the use of these data to understand and improve student learning in a formative manner. This article describes the development of probabilistic models of undergraduate student problem solving in molecular genetics that detailed the spectrum of strategies students used when problem solving, and how the strategic approaches evolved with experience. The actions of 776 university sophomore biology majors from three molecular biology lecture courses were recorded and analyzed. Each of six simulations were first grouped by artificial neural network clustering to provide individual performance measures, and then sequences of these performances were probabilistically modeled by hidden Markov modeling to provide measures of progress. The models showed that students with different initial problem-solving abilities choose different strategies. Initial and final strategies varied across different sections of the same course and were not strongly correlated with other achievement measures. In contrast to previous studies, we observed no significant gender differences. We suggest that instructor interventions based on early student performances with these simulations may assist students to recognize effective and efficient problem-solving strategies and enhance learning. PMID:15746978
Solving a discrete model of the lac operon using Z3
Gutierrez, Natalia A.
2014-05-01
A discrete model for the Lcac Operon is solved using the SMT-solver Z3. Traditionally the Lac Operon is formulated in a continuous math model. This model is a system of ordinary differential equations. Here, it was considerated as a discrete model, based on a Boolean red. The biological problem of Lac Operon is enunciated as a problem of Boolean satisfiability, and it is solved using an STM-solver named Z3. Z3 is a powerful solver that allows understanding the basic dynamic of the Lac Operon in an easier and more efficient way. The multi-stability of the Lac Operon can be easily computed with Z3. The code that solves the Boolean red can be written in Python language or SMT-Lib language. Both languages were used in local version of the program as online version of Z3. For future investigations it is proposed to solve the Boolean red of Lac Operon using others SMT-solvers as cvc4, alt-ergo, mathsat and yices.
Agent-Based Modeling of Collaborative Problem Solving. Research Report. ETS RR-16-27
Bergner, Yoav; Andrews, Jessica J.; Zhu, Mengxiao; Gonzales, Joseph E.
2016-01-01
Collaborative problem solving (CPS) is a critical competency in a variety of contexts, including the workplace, school, and home. However, only recently have assessment and curriculum reformers begun to focus to a greater extent on the acquisition and development of CPS skill. One of the major challenges in psychometric modeling of CPS is…
Anggrianto, Desi; Churiyah, Madziatul; Arief, Mohammad
2016-01-01
This research was conducted in order to know the effect of Logan Avenue Problem Solving (LAPS)-Heuristic learning model towards critical thinking skills of students of class X Office Administration (APK) in SMK Negeri 1 Ngawi, East Java, Indonesia on material curve and equilibrium of demand and supply, subject Introduction to Economics and…
Directory of Open Access Journals (Sweden)
Susi Fatikhah Setiyawati
2015-10-01
Full Text Available Penelitian ini bertujuan: (1 menghasilkan buku pedoman guru untuk pembelajaran fisika SMA menggunakan model problem solving sesuai level inkuiri yang layak digunakan; (2 mendeskripsikan keberhasilan pembelajaran fisika menggunakan model problem solving (MPS sesuai dengan level inkuiri sesuai dengan buku pedoman terhadap peningkatan aktivitas peserta didik dan kemampuan berpikir kritis peserta didik. Penelitian ini merupakan penelitian pengembangan, sesuai langkah yang dikembangkan oleh Borg & Gall. Subjek coba menggunakan delapan kelas. Pengumpulan data menggunakan angket respon peserta didik, lembar observasi keterlaksanaan proses pembelajaran, lembar observasi aktivitas belajar dan tes kemampuan berfikir kritis peserta didik. Teknik analisis data menggunakan uji multivariat (Manova. Hasil penelitian menunjukkan bahwa produk yang dikembangkan ditinjau dari aspek materi, petunjuk umum buku, RPP & LKPD, dan perangkat penilaiam pembelajaran menurut ahli materi dan ahli media berkategori baik dan terdapat perbedaan peningkatan kemampuan berfikir kritis dan aktivitas belajar peserta didik yang signifikan antara keenam level inkuiri yang diujicobakan. Kata Kunci: model problem solving, level inkuiri, kemampuan berfikir kritis, aktivitas belajar DEVELOPING A HANDBOOK FOR TEACHER IN TEACHERS HIGH SCHOOL LEVEL PHYSICS USE THE MODEL OF PROBLEM SOLVING LEVEL OF INQUIRY Abstract This study aims to: (1 to produce a handbook for teachers high school level physics use a model of problem solving with level of inquiry fit for use; (2 to determine the successful learning of physics using a model of problem solving in accordance with the level of inquiry to increase learning activities of learners and critical thinking abilities of learners. This research is the development, which refers to measures developed by Borg & Gall. The subject try consists of eight classes. Data collection using the questionnaire responses of learners, observation sheets learning
Numerical Simulation of Different Models of Heat Pipe Heat Exchanger Using AcuSolve
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Zainal Nurul Amira
2017-01-01
Full Text Available In this paper, a numerical simulation of heat pipe heat exchanger (HPHE is computed by using CFD solver program i.e. AcuSolve. Two idealized model of HPHE are created with different variant of entry’s dimension set to be case 1 and case 2. The geometry of HPHE is designed in SolidWorks and imported to AcuSolve to simulate the fluid flow numerically. The design of HPHE is the key to provide a heat exchanger system to work proficient as expected. Finally, the result is used to optimize and improving heat recovery systems of the increasing demand for energy efficiency in industry.
DEMONSTRATION COMPUTER MODELS USE WHILE SOLVING THE BUILDING OF THE CUT OF THE CYLINDER
Directory of Open Access Journals (Sweden)
Inna O. Gulivata
2010-10-01
Full Text Available Relevance of material presented in the article is the use of effective methods to illustrate the geometric material for the development of spatial imagination of students. As one of the ways to improve problem solving offer to illustrate the use of display computer model (DCM investigated objects created by the software environment PowerPoint. The technique of applying DCM while solving the problems to build a section of the cylinder makes it allows to build effective learning process and promotes the formation of spatial representations of students taking into account their individual characteristics and principles of differentiated instruction.
Effective methods of solving of model equations of certain class of thermal systems
International Nuclear Information System (INIS)
Lach, J.
1985-01-01
A number of topics connected with solving of model equations of certain class of thermal systems by the method of successive approximations is touched. A system of partial differential equations of the first degree, appearing most frequently in practical applications of heat and mass transfer theory is reduced to an equivalent system of Volterra integral equations of the second kind. Among a few sample applications the thermal processes appearing in the fuel channel of nuclear reactor are solved. The theoretical analysis is illustrated by the results of numerical calculations given in tables and diagrams. 111 refs., 17 figs., 16 tabs. (author)
Ozmutlu, H. Cenk
2014-01-01
We developed mixed integer programming (MIP) models and hybrid genetic-local search algorithms for the scheduling problem of unrelated parallel machines with job sequence and machine-dependent setup times and with job splitting property. The first contribution of this paper is to introduce novel algorithms which make splitting and scheduling simultaneously with variable number of subjobs. We proposed simple chromosome structure which is constituted by random key numbers in hybrid genetic-local search algorithm (GAspLA). Random key numbers are used frequently in genetic algorithms, but it creates additional difficulty when hybrid factors in local search are implemented. We developed algorithms that satisfy the adaptation of results of local search into the genetic algorithms with minimum relocation operation of genes' random key numbers. This is the second contribution of the paper. The third contribution of this paper is three developed new MIP models which are making splitting and scheduling simultaneously. The fourth contribution of this paper is implementation of the GAspLAMIP. This implementation let us verify the optimality of GAspLA for the studied combinations. The proposed methods are tested on a set of problems taken from the literature and the results validate the effectiveness of the proposed algorithms. PMID:24977204
Eroglu, Duygu Yilmaz; Ozmutlu, H Cenk
2014-01-01
We developed mixed integer programming (MIP) models and hybrid genetic-local search algorithms for the scheduling problem of unrelated parallel machines with job sequence and machine-dependent setup times and with job splitting property. The first contribution of this paper is to introduce novel algorithms which make splitting and scheduling simultaneously with variable number of subjobs. We proposed simple chromosome structure which is constituted by random key numbers in hybrid genetic-local search algorithm (GAspLA). Random key numbers are used frequently in genetic algorithms, but it creates additional difficulty when hybrid factors in local search are implemented. We developed algorithms that satisfy the adaptation of results of local search into the genetic algorithms with minimum relocation operation of genes' random key numbers. This is the second contribution of the paper. The third contribution of this paper is three developed new MIP models which are making splitting and scheduling simultaneously. The fourth contribution of this paper is implementation of the GAspLAMIP. This implementation let us verify the optimality of GAspLA for the studied combinations. The proposed methods are tested on a set of problems taken from the literature and the results validate the effectiveness of the proposed algorithms.
International Nuclear Information System (INIS)
Gene Golub; Kwok Ko
2009-01-01
The solutions of sparse eigenvalue problems and linear systems constitute one of the key computational kernels in the discretization of partial differential equations for the modeling of linear accelerators. The computational challenges faced by existing techniques for solving those sparse eigenvalue problems and linear systems call for continuing research to improve on the algorithms so that ever increasing problem size as required by the physics application can be tackled. Under the support of this award, the filter algorithm for solving large sparse eigenvalue problems was developed at Stanford to address the computational difficulties in the previous methods with the goal to enable accelerator simulations on then the world largest unclassified supercomputer at NERSC for this class of problems. Specifically, a new method, the Hemitian skew-Hemitian splitting method, was proposed and researched as an improved method for solving linear systems with non-Hermitian positive definite and semidefinite matrices.
Developing material for promoting problem-solving ability through bar modeling technique
Widyasari, N.; Rosiyanti, H.
2018-01-01
This study aimed at developing material for enhancing problem-solving ability through bar modeling technique with thematic learning. Polya’s steps of problem-solving were chosen as the basis of the study. The methods of the study were research and development. The subject of this study were five teen students of the fifth grade of Lab-school FIP UMJ elementary school. Expert review and student’ response analysis were used to collect the data. Furthermore, the data were analyzed using qualitative descriptive and quantitative. The findings showed that material in theme “Selalu Berhemat Energi” was categorized as valid and practical. The validity was measured by using the aspect of language, contents, and graphics. Based on the expert comments, the materials were easy to implement in the teaching-learning process. In addition, the result of students’ response showed that material was both interesting and easy to understand. Thus, students gained more understanding in learning problem-solving.
The Vessel Schedule Recovery Problem (VSRP) – A MIP model for handling disruptions in liner shipping
DEFF Research Database (Denmark)
Brouer, Berit Dangaard; Dirksen, Jakob; Pisinger, David
2013-01-01
or even omitting one. We present the Vessel Schedule Recovery Problem (VSRP) to evaluate a given disruption scenario and to select a recovery action balancing the trade off between increased bunker consumption and the impact on cargo in the remaining network and the customer service level. It is proven...... due to adverse weather conditions, port contingencies, and many other issues. A common scenario for recovering a schedule is to either increase the speed at the cost of a significant increase in the fuel consumption or delaying cargo. Advanced recovery options might exist by swapping two port calls...... that the VSRP is NP-hard. The model is applied to four real life cases from Maersk Line and results are achieved in less than 5seconds with solutions comparable or superior to those chosen by operations managers in real life. Cost savings of up to 58% may be achieved by the suggested solutions compared...
Directory of Open Access Journals (Sweden)
Gholamreza Norouzi
2015-01-01
Full Text Available In project management context, time management is one of the most important factors affecting project success. This paper proposes a new method to solve research project scheduling problems (RPSP containing Fuzzy Graphical Evaluation and Review Technique (FGERT networks. Through the deliverables of this method, a proper estimation of project completion time (PCT and success probability can be achieved. So algorithms were developed to cover all features of the problem based on three main parameters “duration, occurrence probability, and success probability.” These developed algorithms were known as PR-FGERT (Parallel and Reversible-Fuzzy GERT networks. The main provided framework includes simplifying the network of project and taking regular steps to determine PCT and success probability. Simplifications include (1 equivalent making of parallel and series branches in fuzzy network considering the concepts of probabilistic nodes, (2 equivalent making of delay or reversible-to-itself branches and impact of changing the parameters of time and probability based on removing related branches, (3 equivalent making of simple and complex loops, and (4 an algorithm that was provided to resolve no-loop fuzzy network, after equivalent making. Finally, the performance of models was compared with existing methods. The results showed proper and real performance of models in comparison with existing methods.
Development of syntax of intuition-based learning model in solving mathematics problems
Yeni Heryaningsih, Nok; Khusna, Hikmatul
2018-01-01
The aim of the research was to produce syntax of Intuition Based Learning (IBL) model in solving mathematics problem for improving mathematics students’ achievement that valid, practical and effective. The subject of the research were 2 classes in grade XI students of SMAN 2 Sragen, Central Java. The type of the research was a Research and Development (R&D). Development process adopted Plomp and Borg & Gall development model, they were preliminary investigation step, design step, realization step, evaluation and revision step. Development steps were as follow: (1) Collected the information and studied of theories in Preliminary Investigation step, studied about intuition, learning model development, students condition, and topic analysis, (2) Designed syntax that could bring up intuition in solving mathematics problem and then designed research instruments. They were several phases that could bring up intuition, Preparation phase, Incubation phase, Illumination phase and Verification phase, (3) Realized syntax of Intuition Based Learning model that has been designed to be the first draft, (4) Did validation of the first draft to the validator, (5) Tested the syntax of Intuition Based Learning model in the classrooms to know the effectiveness of the syntax, (6) Conducted Focus Group Discussion (FGD) to evaluate the result of syntax model testing in the classrooms, and then did the revision on syntax IBL model. The results of the research were produced syntax of IBL model in solving mathematics problems that valid, practical and effective. The syntax of IBL model in the classroom were, (1) Opening with apperception, motivations and build students’ positive perceptions, (2) Teacher explains the material generally, (3) Group discussion about the material, (4) Teacher gives students mathematics problems, (5) Doing exercises individually to solve mathematics problems with steps that could bring up students’ intuition: Preparations, Incubation, Illumination, and
An Optimization of Manufacturing Systems using a Feedback Control Scheduling Model
Ikome, John M.; Kanakana, Grace M.
2018-03-01
In complex production system that involves multiple process, unplanned disruption often turn to make the entire production system vulnerable to a number of problems which leads to customer’s dissatisfaction. However, this problem has been an ongoing problem that requires a research and methods to streamline the entire process or develop a model that will address it, in contrast to this, we have developed a feedback scheduling model that can minimize some of this problem and after a number of experiment, it shows that some of this problems can be eliminated if the correct remedial actions are implemented on time.
Methodologic model to scheduling on service systems: a software engineering approach
Directory of Open Access Journals (Sweden)
Eduyn Ramiro Lopez-Santana
2016-06-01
Full Text Available This paper presents an approach of software engineering to a research proposal to make an Expert System to scheduling on service systems using methodologies and processes of software development. We use the adaptive software development as methodology for the software architecture based on the description as a software metaprocess that characterizes the research process. We make UML’s diagrams (Unified Modeling Language to provide a visual modeling that describes the research methodology in order to identify the actors, elements and interactions in the research process.
Schedule-induced polydipsia: a rat model of obsessive-compulsive disorder.
Platt, Brian; Beyer, Chad E; Schechter, Lee E; Rosenzweig-Lipson, Sharon
2008-04-01
Obsessive-compulsive disorder (OCD) is difficult to model in animals due to the involvement of both mental (obsessions) and physical (compulsions) symptoms. Due to limitations of using animals to evaluate obsessions, OCD models are limited to evaluation of the compulsive and repetitive behaviors of animals. Of these, models of adjunctive behaviors offer the most value in regard to predicting efficacy of anti-OCD drugs in the clinic. Adjunctive behaviors are those that are maintained indirectly by the variables that control another behavior, rather than directly by their own typical controlling variables. Schedule-induced polydipsia (SIP) is an adjunctive model in which rats exhibit exaggerated drinking behavior (polydipsia) when presented with food pellets under a fixed-time schedule. The polydipsic response is an excessive manifestation of a normal behavior (drinking), providing face validity to the model. Furthermore, clinically effective drugs for the treatment of OCD decrease SIP. This protocol describes a rat SIP model of OCD and provides preclinical data for drugs that decrease polydipsia and are clinically effective in the treatment of OCD.
Jewpanich, Chaiwat; Piriyasurawong, Pallop
2015-01-01
This research aims to 1) develop the project-based learning using discussion and lesson-learned methods via social media model (PBL-DLL SoMe Model) used for enhancing problem solving skills of undergraduate in education student, and 2) evaluate the PBL-DLL SoMe Model used for enhancing problem solving skills of undergraduate in education student.…
Flaxion: a minimal extension to solve puzzles in the standard model
Energy Technology Data Exchange (ETDEWEB)
Ema, Yohei [Department of Physics,The University of Tokyo, Tokyo 133-0033 (Japan); Hamaguchi, Koichi; Moroi, Takeo; Nakayama, Kazunori [Department of Physics,The University of Tokyo, Tokyo 133-0033 (Japan); Kavli Institute for the Physics and Mathematics of the Universe (Kavli IPMU),University of Tokyo, Kashiwa 277-8583 (Japan)
2017-01-23
We propose a minimal extension of the standard model which includes only one additional complex scalar field, flavon, with flavor-dependent global U(1) symmetry. It not only explains the hierarchical flavor structure in the quark and lepton sector (including neutrino sector), but also solves the strong CP problem by identifying the CP-odd component of the flavon as the QCD axion, which we call flaxion. Furthermore, the flaxion model solves the cosmological puzzles in the standard model, i.e., origin of dark matter, baryon asymmetry of the universe, and inflation. We show that the radial component of the flavon can play the role of inflaton without isocurvature nor domain wall problems. The dark matter abundance can be explained by the flaxion coherent oscillation, while the baryon asymmetry of the universe is generated through leptogenesis.
Planning and Scheduling for Fleets of Earth Observing Satellites
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.
A simple rule based model for scheduling farm management operations in SWAT
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
Saleh, H.; Suryadi, D.; Dahlan, J. A.
2018-01-01
The aim of this research was to find out whether 7E learning cycle under hypnoteaching model can enhance students’ mathematical problem-solving skill. This research was quasi-experimental study. The design of this study was pretest-posttest control group design. There were two groups of sample used in the study. The experimental group was given 7E learning cycle under hypnoteaching model, while the control group was given conventional model. The population of this study was the student of mathematics education program at one university in Tangerang. The statistical analysis used to test the hypothesis of this study were t-test and Mann-Whitney U. The result of this study show that: (1) The students’ achievement of mathematical problem solving skill who obtained 7E learning cycle under hypnoteaching model are higher than the students who obtained conventional model; (2) There are differences in the students’ enhancement of mathematical problem-solving skill based on students’ prior mathematical knowledge (PMK) category (high, middle, and low).
A model of alcohol drinking under an intermittent access schedule using group-housed mice.
Directory of Open Access Journals (Sweden)
Magdalena Smutek
Full Text Available Here, we describe a new model of voluntary alcohol drinking by group-housed mice. The model employs sensor-equipped cages that track the behaviors of the individual animals via implanted radio chips. After the animals were allowed intermittent access to alcohol (three 24 h intervals every week for 4 weeks, the proportions of licks directed toward bottles containing alcohol were 50.9% and 39.6% for the male and female mice, respectively. We used three approaches (i.e., quinine adulteration, a progressive ratio schedule and a schedule involving a risk of punishment to test for symptoms of compulsive alcohol drinking. The addition of 0.01% quinine to the alcohol solution did not significantly affect intake, but 0.03% quinine induced a greater than 5-fold reduction in the number of licks on the alcohol bottles. When the animals were required to perform increasing numbers of instrumental responses to obtain access to the bottle with alcohol (i.e., a progressive ratio schedule, they frequently reached a maximum of 21 responses irrespective of the available reward. Although the mice rarely achieved higher response criteria, the number of attempts was ∼ 10 times greater in case of alcohol than water. We have developed an approach for mapping social interactions among animals that is based on analysis of the sequences of entries into the cage corners. This approach allowed us to identify the mice that followed other animals in non-random fashions. Approximately half of the mice displayed at least one interaction of this type. We have not yet found a clear correlation between imitative behavior and relative alcohol preference. In conclusion, the model we describe avoids the limitations associated with testing isolated animals and reliably leads to stable alcohol drinking. Therefore, this model may be well suited to screening for the effects of genetic mutations or pharmacological treatments on alcohol-induced behaviors.
Fasni, N.; Turmudi, T.; Kusnandi, K.
2017-09-01
This research background of this research is the importance of student problem solving abilities. The purpose of this study is to find out whether there are differences in the ability to solve mathematical problems between students who have learned mathematics using Ang’s Framework for Mathematical Modelling Instruction (AFFMMI) and students who have learned using scientific approach (SA). The method used in this research is a quasi-experimental method with pretest-postest control group design. Data analysis of mathematical problem solving ability using Indepent Sample Test. The results showed that there was a difference in the ability to solve mathematical problems between students who received learning with Ang’s Framework for Mathematical Modelling Instruction and students who received learning with a scientific approach. AFFMMI focuses on mathematical modeling. This modeling allows students to solve problems. The use of AFFMMI is able to improve the solving ability.
International Nuclear Information System (INIS)
Kiger, W.S. III; Newton, T.H.; Palmer, M.R.
2000-01-01
Separate compartmental models have been derived for the concentration of 10 B resulting from BPA-F infusion in the central vascular space (i.e., blood or, more appropriately, plasma) and in glioblastoma multiforme and normal brain. By coupling the model for the temporal variation of 10 B concentration in the central vascular space with that for tissue, the dynamic behavior of the 10 B concentration and the resulting dosimetry in the relevant tissues and blood may be predicted for arbitrary infusion schedules. This coupled model may be used as a tool for identifying the optimal time for BNCT irradiation and optimal BPA-F infusion schedule (i.e., temporal targeting) in humans without the need for expensive and time-consuming pharmacokinetic studies for every infusion schedule considered. This model was used to analyze the concentration profiles resulting from a wide range of infusion schedules and their implications for dosimetry. (author)
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...
Directory of Open Access Journals (Sweden)
Ellianawati -
2012-01-01
Full Text Available Model pelaksanaan praktikum fisika yang selama ini dilakukan adalah model resep masakan, yaitu semua hal yang berkaitandengan praktikum mulai petunjuk praktikum sampai alat telah disediakan oleh laboran. Model tersebut memiliki kelemahan yaitusemangat untuk menggali pengetahuan mahasiswa menjadi rendah, karena apapun yang dibutuhkan dalam praktikum telahdisajikan.Tujuan dari penelitian ini adalah menerapkan model praktikum problem solving laboratory untuk meningkatkan kualitaspelaksanaan praktikum Fisika Dasar di Jurusan Fisika UNNES. Rancangan penelitian ini menggunakan penelitian tindakankelas(action research yang dilakukan dalam 3 siklus. Masing-masing siklus terdiri dari langkah: perencanaan, implementasi,evaluasi dan refleksi yang mengadopsi Model Spiral dari Kemmis dan MC Taggart. Pada saat pelaksanaan pembelajaran, siswadiberikan masalah yang berkaitan dengan konsep yang harus dikuasai. Masalah yang diberikan kepada mahasiswa akandiselesaikan oleh mahasiswa melalui kegiatan praktikum. Melalui penerapan model praktikum problem solving laboratory telahberhasil meningkatkan kualitas pelaksanaan praktikum Fisika Dasar 1. Indikator dari meningkatnya kualitas praktikum tercermindari peningkatan hasil belajar mahasiswa dan aktivitas belajarnya. Berdasarkan hasil pengamatan pelaksanaan praktikum fisikadasar terlihat pada saat kegiatan praktikum pada setiap siklusnya terjadi peningkatan aktivitasnya, baik untuk kegiatan prapraktikum, pada saat praktikum dan presentasi hasilnya. Lembar kegiatan praktikum mahasiswa mampu diselesaikan dengan baikoleh tiap-tiap kelompok praktikum. Kesimpulan dari penelitian ini adalah 1 telah terjadi peningkatkan kualitas pelaksanaanpraktikum Fisika Dasar 1 di Jurusan Fisika UNNES dengan penerapan model praktikum problem solving laboratory. 2 telah terjadiperbaikan pelaksanaan praktikum Fisika Dasar 1 di Jurusan Fisika UNNES dengan penerapan model praktikum problem solvinglaboratory. Hal ini ditandai dengan kemampuan
Handayani, I.; Januar, R. L.; Purwanto, S. E.
2018-01-01
This research aims to know the influence of Missouri Mathematics Project Learning Model to Mathematical Problem-solving Ability of Students at Junior High School. This research is a quantitative research and uses experimental research method of Quasi Experimental Design. The research population includes all student of grade VII of Junior High School who are enrolled in the even semester of the academic year 2016/2017. The Sample studied are 76 students from experimental and control groups. The sampling technique being used is cluster sampling method. The instrument is consisted of 7 essay questions whose validity, reliability, difficulty level and discriminating power have been tested. Before analyzing the data by using t-test, the data has fulfilled the requirement for normality and homogeneity. The result of data shows that there is the influence of Missouri mathematics project learning model to mathematical problem-solving ability of students at junior high school with medium effect.
Teaching genetics using hands-on models, problem solving, and inquiry-based methods
Hoppe, Stephanie Ann
Teaching genetics can be challenging because of the difficulty of the content and misconceptions students might hold. This thesis focused on using hands-on model activities, problem solving, and inquiry-based teaching/learning methods in order to increase student understanding in an introductory biology class in the area of genetics. Various activities using these three methods were implemented into the classes to address any misconceptions and increase student learning of the difficult concepts. The activities that were implemented were shown to be successful based on pre-post assessment score comparison. The students were assessed on the subjects of inheritance patterns, meiosis, and protein synthesis and demonstrated growth in all of the areas. It was found that hands-on models, problem solving, and inquiry-based activities were more successful in learning concepts in genetics and the students were more engaged than tradition styles of lecture.
A novel modeling approach for job shop scheduling problem under uncertainty
Directory of Open Access Journals (Sweden)
Behnam Beheshti Pur
2013-11-01
Full Text Available When aiming on improving efficiency and reducing cost in manufacturing environments, production scheduling can play an important role. Although a common workshop is full of uncertainties, when using mathematical programs researchers have mainly focused on deterministic problems. After briefly reviewing and discussing popular modeling approaches in the field of stochastic programming, this paper proposes a new approach based on utility theory for a certain range of problems and under some practical assumptions. Expected utility programming, as the proposed approach, will be compared with the other well-known methods and its meaningfulness and usefulness will be illustrated via a numerical examples and a real case.
Scheduling of power generation a large-scale mixed-variable model
Prékopa, András; Strazicky, Beáta; Deák, István; Hoffer, János; Németh, Ágoston; Potecz, Béla
2014-01-01
The book contains description of a real life application of modern mathematical optimization tools in an important problem solution for power networks. The objective is the modelling and calculation of optimal daily scheduling of power generation, by thermal power plants, to satisfy all demands at minimum cost, in such a way that the generation and transmission capacities as well as the demands at the nodes of the system appear in an integrated form. The physical parameters of the network are also taken into account. The obtained large-scale mixed variable problem is relaxed in a smart, practical way, to allow for fast numerical solution of the problem.
Sitek, Paweł; Wikarek, Jarosław
2016-01-01
This paper proposes a hybrid programming framework for modeling and solving of constraint satisfaction problems (CSPs) and constraint optimization problems (COPs). Two paradigms, CLP (constraint logic programming) and MP (mathematical programming), are integrated in the framework. The integration is supplemented with the original method of problem transformation, used in the framework as a presolving method. The transformation substantially reduces the feasible solution space. The framework a...
Application of differential transformation method for solving dengue transmission mathematical model
Ndii, Meksianis Z.; Anggriani, Nursanti; Supriatna, Asep K.
2018-03-01
The differential transformation method (DTM) is a semi-analytical numerical technique which depends on Taylor series and has application in many areas including Biomathematics. The aim of this paper is to employ the differential transformation method (DTM) to solve system of non-linear differential equations for dengue transmission mathematical model. Analytical and numerical solutions are determined and the results are compared to that of Runge-Kutta method. We found a good agreement between DTM and Runge-Kutta method.
Students’ errors in solving combinatorics problems observed from the characteristics of RME modeling
Meika, I.; Suryadi, D.; Darhim
2018-01-01
This article was written based on the learning evaluation results of students’ errors in solving combinatorics problems observed from the characteristics of Realistic Mathematics Education (RME); that is modeling. Descriptive method was employed by involving 55 students from two international-based pilot state senior high schools in Banten. The findings of the study suggested that the students still committed errors in simplifying the problem as much 46%; errors in making mathematical model (horizontal mathematization) as much 60%; errors in finishing mathematical model (vertical mathematization) as much 65%; and errors in interpretation as well as validation as much 66%.
Formation of model-free motor memories during motor adaptation depends on perturbation schedule.
Orban de Xivry, Jean-Jacques; Lefèvre, Philippe
2015-04-01
Motor adaptation to an external perturbation relies on several mechanisms such as model-based, model-free, strategic, or repetition-dependent learning. Depending on the experimental conditions, each of these mechanisms has more or less weight in the final adaptation state. Here we focused on the conditions that lead to the formation of a model-free motor memory (Huang VS, Haith AM, Mazzoni P, Krakauer JW. Neuron 70: 787-801, 2011), i.e., a memory that does not depend on an internal model or on the size or direction of the errors experienced during the learning. The formation of such model-free motor memory was hypothesized to depend on the schedule of the perturbation (Orban de Xivry JJ, Ahmadi-Pajouh MA, Harran MD, Salimpour Y, Shadmehr R. J Neurophysiol 109: 124-136, 2013). Here we built on this observation by directly testing the nature of the motor memory after abrupt or gradual introduction of a visuomotor rotation, in an experimental paradigm where the presence of model-free motor memory can be identified (Huang VS, Haith AM, Mazzoni P, Krakauer JW. Neuron 70: 787-801, 2011). We found that relearning was faster after abrupt than gradual perturbation, which suggests that model-free learning is reduced during gradual adaptation to a visuomotor rotation. In addition, the presence of savings after abrupt introduction of the perturbation but gradual extinction of the motor memory suggests that unexpected errors are necessary to induce a model-free motor memory. Overall, these data support the hypothesis that different perturbation schedules do not lead to a more or less stabilized motor memory but to distinct motor memories with different attributes and neural representations. Copyright © 2015 the American Physiological Society.
Developing an agent-based model on how different individuals solve complex problems
Directory of Open Access Journals (Sweden)
Ipek Bozkurt
2015-01-01
Full Text Available Purpose: Research that focuses on the emotional, mental, behavioral and cognitive capabilities of individuals has been abundant within disciplines such as psychology, sociology, and anthropology, among others. However, when facing complex problems, a new perspective to understand individuals is necessary. The main purpose of this paper is to develop an agent-based model and simulation to gain understanding on the decision-making and problem-solving abilities of individuals. Design/Methodology/approach: The micro-level analysis modeling and simulation paradigm Agent-Based Modeling Through the use of Agent-Based Modeling, insight is gained on how different individuals with different profiles deal with complex problems. Using previous literature from different bodies of knowledge, established theories and certain assumptions as input parameters, a model is built and executed through a computer simulation. Findings: The results indicate that individuals with certain profiles have better capabilities to deal with complex problems. Moderate profiles could solve the entire complex problem, whereas profiles within extreme conditions could not. This indicates that having a strong predisposition is not the ideal way when approaching complex problems, and there should always be a component from the other perspective. The probability that an individual may use these capabilities provided by the opposite predisposition provides to be a useful option. Originality/value: The originality of the present research stems from how individuals are profiled, and the model and simulation that is built to understand how they solve complex problems. The development of the agent-based model adds value to the existing body of knowledge within both social sciences, and modeling and simulation.
On the Modelling of the Mobile WiMAX (IEEE 802.16e Uplink Scheduler
Directory of Open Access Journals (Sweden)
Darmawaty Mohd Ali
2010-01-01
Full Text Available Packet scheduling has drawn a great deal of attention in the field of wireless networks as it plays an important role in distributing shared resources in a network. The process involves allocating the bandwidth among users and determining their transmission order. In this paper an uplink (UL scheduling algorithm for the Mobile Worldwide Interoperability for Microwave Access (WiMAX network based on the cyclic polling model is proposed. The model in this study consists of five queues (UGS, ertPS, rtPS, nrtPS, and BE visited by a single server. A threshold policy is imposed to the nrtPS queue to ensure that the delay constraint of real time traffic (UGS, ertPS, and rtPS is not violated making this approach original in comparison to the existing contributions. A mathematical model is formulated for the weighted sum of the mean waiting time of each individual queues based on the pseudo-conservation law. The results of the analysis are useful in obtaining or testing approximation for individual mean waiting time especially when queues are asymmetric (where each queue may have different stochastic characteristic such as arrival rate and service time distribution and when their number is large (more than 2 queues.
A Model-Driven Co-Design Framework for Fusing Control and Scheduling Viewpoints.
Sundharam, Sakthivel Manikandan; Navet, Nicolas; Altmeyer, Sebastian; Havet, Lionel
2018-02-20
Model-Driven Engineering (MDE) is widely applied in the industry to develop new software functions and integrate them into the existing run-time environment of a Cyber-Physical System (CPS). The design of a software component involves designers from various viewpoints such as control theory, software engineering, safety, etc. In practice, while a designer from one discipline focuses on the core aspects of his field (for instance, a control engineer concentrates on designing a stable controller), he neglects or considers less importantly the other engineering aspects (for instance, real-time software engineering or energy efficiency). This may cause some of the functional and non-functional requirements not to be met satisfactorily. In this work, we present a co-design framework based on timing tolerance contract to address such design gaps between control and real-time software engineering. The framework consists of three steps: controller design, verified by jitter margin analysis along with co-simulation, software design verified by a novel schedulability analysis, and the run-time verification by monitoring the execution of the models on target. This framework builds on CPAL (Cyber-Physical Action Language), an MDE design environment based on model-interpretation, which enforces a timing-realistic behavior in simulation through timing and scheduling annotations. The application of our framework is exemplified in the design of an automotive cruise control system.
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.
A Model-Driven Co-Design Framework for Fusing Control and Scheduling Viewpoints
Navet, Nicolas; Havet, Lionel
2018-01-01
Model-Driven Engineering (MDE) is widely applied in the industry to develop new software functions and integrate them into the existing run-time environment of a Cyber-Physical System (CPS). The design of a software component involves designers from various viewpoints such as control theory, software engineering, safety, etc. In practice, while a designer from one discipline focuses on the core aspects of his field (for instance, a control engineer concentrates on designing a stable controller), he neglects or considers less importantly the other engineering aspects (for instance, real-time software engineering or energy efficiency). This may cause some of the functional and non-functional requirements not to be met satisfactorily. In this work, we present a co-design framework based on timing tolerance contract to address such design gaps between control and real-time software engineering. The framework consists of three steps: controller design, verified by jitter margin analysis along with co-simulation, software design verified by a novel schedulability analysis, and the run-time verification by monitoring the execution of the models on target. This framework builds on CPAL (Cyber-Physical Action Language), an MDE design environment based on model-interpretation, which enforces a timing-realistic behavior in simulation through timing and scheduling annotations. The application of our framework is exemplified in the design of an automotive cruise control system. PMID:29461489
A Model-Driven Co-Design Framework for Fusing Control and Scheduling Viewpoints
Directory of Open Access Journals (Sweden)
Sakthivel Manikandan Sundharam
2018-02-01
Full Text Available Model-Driven Engineering (MDE is widely applied in the industry to develop new software functions and integrate them into the existing run-time environment of a Cyber-Physical System (CPS. The design of a software component involves designers from various viewpoints such as control theory, software engineering, safety, etc. In practice, while a designer from one discipline focuses on the core aspects of his field (for instance, a control engineer concentrates on designing a stable controller, he neglects or considers less importantly the other engineering aspects (for instance, real-time software engineering or energy efficiency. This may cause some of the functional and non-functional requirements not to be met satisfactorily. In this work, we present a co-design framework based on timing tolerance contract to address such design gaps between control and real-time software engineering. The framework consists of three steps: controller design, verified by jitter margin analysis along with co-simulation, software design verified by a novel schedulability analysis, and the run-time verification by monitoring the execution of the models on target. This framework builds on CPAL (Cyber-Physical Action Language, an MDE design environment based on model-interpretation, which enforces a timing-realistic behavior in simulation through timing and scheduling annotations. The application of our framework is exemplified in the design of an automotive cruise control system.
Kobak, B. V.; Zhukovskiy, A. G.; Kuzin, A. P.
2018-05-01
This paper considers one of the classical NP complete problems - an inhomogeneous minimax problem. When solving such large-scale problem, there appear difficulties in obtaining an exact solution. Therefore, let us propose getting an optimum solution in an acceptable time. Among a wide range of genetic algorithm models, let us choose the modified Goldberg model, which earlier was successfully used by authors in solving NP complete problems. The classical Goldberg model uses a single-point crossover and a singlepoint mutation, which somewhat decreases the accuracy of the obtained results. In the article, let us propose using a full two-point crossover with various mutations previously researched. In addition, the work studied the necessary probability to apply it to the crossover in order to obtain results that are more accurate. Results of the computation experiment showed that the higher the probability of a crossover, the higher the quality of both the average results and the best solutions. In addition, it was found out that the higher the values of the number of individuals and the number of repetitions, the closer both the average results and the best solutions to the optimum. The paper shows how the use of a full two-point crossover increases the accuracy of solving an inhomogeneous minimax problem, while the time for getting the solution increases, but remains polynomial.
Artificial Immune Algorithm for Subtask Industrial Robot Scheduling in Cloud Manufacturing
Suma, T.; Murugesan, R.
2018-04-01
The current generation of manufacturing industry requires an intelligent scheduling model to achieve an effective utilization of distributed manufacturing resources, which motivated us to work on an Artificial Immune Algorithm for subtask robot scheduling in cloud manufacturing. This scheduling model enables a collaborative work between the industrial robots in different manufacturing centers. This paper discussed two optimizing objectives which includes minimizing the cost and load balance of industrial robots through scheduling. To solve these scheduling problems, we used the algorithm based on Artificial Immune system. The parameters are simulated with MATLAB and the results compared with the existing algorithms. The result shows better performance than existing.
Sherry, Lance; Ferguson, John; Hoffman, Karla; Donohue, George; Beradino, Frank
2012-01-01
This report describes the Airline Fleet, Route, and Schedule Optimization Model (AFRS-OM) that is designed to provide insights into airline decision-making with regards to markets served, schedule of flights on these markets, the type of aircraft assigned to each scheduled flight, load factors, airfares, and airline profits. The main inputs to the model are hedged fuel prices, airport capacity limits, and candidate markets. Embedded in the model are aircraft performance and associated cost factors, and willingness-to-pay (i.e. demand vs. airfare curves). Case studies demonstrate the application of the model for analysis of the effects of increased capacity and changes in operating costs (e.g. fuel prices). Although there are differences between airports (due to differences in the magnitude of travel demand and sensitivity to airfare), the system is more sensitive to changes in fuel prices than capacity. Further, the benefits of modernization in the form of increased capacity could be undermined by increases in hedged fuel prices
International Nuclear Information System (INIS)
Grscic, Z.
1989-01-01
Models for solving transport and dispersion problems of radioactive pollutants through atmosphere are briefly shown. These models are the base for solving and some special problems such as: estimating effective and physical heights of radioactive sources, computation of radioactive concentration distribution from multiple sources etc (author)
Solving a bi-objective mathematical programming model for bloodmobiles location routing problem
Directory of Open Access Journals (Sweden)
Masoud Rabbani
2017-01-01
Full Text Available Perishability of platelets, uncertainty of donors’ arrival and conflicting views in platelet supply chain have made platelet supply chain planning a problematic issue. In this paper, mobile blood collection system for platelet production is investigated. Two mathematical models are presented to cover the bloodmobile collection planning problem. The first model is a multi-objective fuzzy mathematical programming in which the bloodmobiles locations are considered with the aim of maximizing potential amount of blood collection and minimizing the operational cost. The second model is a vehicle routing problem with time windows which studies the shuttles routing problem. To tackle the first model, it is reformulated as a crisp multi objective linear programming model and then solved through a fuzzy multi objective programming approach. Several sensitivity analysis are conducted on important parameters to demonstrate the applicability of the proposed model. The proposed model is then solved by using a tailored Simulated Annealing (SA algorithm. The numerical results demonstrate promising efficiency of the proposed solution method.
A continuous time model for a short-term multiproduct batch process scheduling
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Jenny Díaz Ramírez
2018-01-01
Full Text Available In the chemical industry, it is common to find production systems characterized by having a single stage or a previously identified bottleneck stage, with multiple non-identical parallel stations and with setup costs that depend on the production sequence. This paper proposes a mixed integer production-scheduling model that identifies lot size and product sequence that maximize profit. It considers multiple typical industry conditions, such as penalties for noncompliance or out of service periods of the productive units (or stations for preventive maintenance activities. The model was validated with real data from an oil chemical company. Aiming to analyze its performance, we applied the model to 155 instances of production, which were obtained using Monte Carlo technique on the historical production data of the same company. We obtained an average 12 % reduction in the total cost of production and a 19 % increase in the estimated profit.
Three hybridization models based on local search scheme for job shop scheduling problem
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.
New Mathematical Model and Algorithm for Economic Lot Scheduling Problem in Flexible Flow Shop
Directory of Open Access Journals (Sweden)
H. Zohali
2018-03-01
Full Text Available This paper addresses the lot sizing and scheduling problem for a number of products in flexible flow shop with identical parallel machines. The production stages are in series, while separated by finite intermediate buffers. The objective is to minimize the sum of setup and inventory holding costs per unit of time. The available mathematical model of this problem in the literature suffers from huge complexity in terms of size and computation. In this paper, a new mixed integer linear program is developed for delay with the huge dimentions of the problem. Also, a new meta heuristic algorithm is developed for the problem. The results of the numerical experiments represent a significant advantage of the proposed model and algorithm compared with the available models and algorithms in the literature.
Integrated model for pricing, delivery time setting, and scheduling in make-to-order environments
Garmdare, Hamid Sattari; Lotfi, M. M.; Honarvar, Mahboobeh
2018-03-01
Usually, in make-to-order environments which work only in response to the customer's orders, manufacturers for maximizing the profits should offer the best price and delivery time for an order considering the existing capacity and the customer's sensitivity to both the factors. In this paper, an integrated approach for pricing, delivery time setting and scheduling of new arrival orders are proposed based on the existing capacity and accepted orders in system. In the problem, the acquired market demands dependent on the price and delivery time of both the manufacturer and its competitors. A mixed-integer non-linear programming model is presented for the problem. After converting to a pure non-linear model, it is validated through a case study. The efficiency of proposed model is confirmed by comparing it to both the literature and the current practice. Finally, sensitivity analysis for the key parameters is carried out.
Energy Storage Scheduling with an Advanced Battery Model: A Game–Theoretic Approach
Directory of Open Access Journals (Sweden)
Matthias Pilz
2017-11-01
Full Text Available Energy storage systems will play a key role for individual users in the future smart grid. They serve two purposes: (i handling the intermittent nature of renewable energy resources for a more reliable and efficient system; and (ii preventing the impact of blackouts on users and allowing for more independence from the grid, while saving money through load-shifting. In this paper we investigate the latter scenario by looking at a neighbourhood of 25 households whose demand is satisfied by one utility company. Assuming the users possess lithium-ion batteries, we answer the question of how each household can make the best use of their individual storage system given a real-time pricing policy. To this end, each user is modelled as a player of a non-cooperative scheduling game. The novelty of the game lies in the advanced battery model, which incorporates charging and discharging characteristics of lithium-ion batteries. The action set for each player comprises day-ahead schedules of their respective battery usage. We analyse different user behaviour and are able to obtain a realistic and applicable understanding of the potential of these systems. As a result, we show the correlation between the efficiency of the battery and the outcome of the game.
Directory of Open Access Journals (Sweden)
F. Nazari
2017-03-01
Full Text Available By increasing the use of distributed generation (DG in the distribution network operation, an entity called virtual power plant (VPP has been introduced to control, dispatch and aggregate the generation of DGs, enabling them to participate either in the electricity market or the distribution network operation. The participation of VPPs in the electricity market has made challenges to fairly allocate payments and benefits between VPPs and distribution network operator (DNO. This paper presents a bilevel scheduling approach to model the energy transaction between VPPs and DNO. The upper level corresponds to the decision making of VPPs which bid their long- term contract prices so that their own profits are maximized and the lower level represents the DNO decision making to supply electricity demand of the network by minimizing its overall cost. The proposed bilevel scheduling approach is transformed to a single level optimizing problem using its Karush-Kuhn-Tucker (KKT optimality conditions. Several scenarios are applied to scrutinize the effectiveness and usefulness of the proposed model.
Model-based verification method for solving the parameter uncertainty in the train control system
International Nuclear Information System (INIS)
Cheng, Ruijun; Zhou, Jin; Chen, Dewang; Song, Yongduan
2016-01-01
This paper presents a parameter analysis method to solve the parameter uncertainty problem for hybrid system and explore the correlation of key parameters for distributed control system. For improving the reusability of control model, the proposed approach provides the support for obtaining the constraint sets of all uncertain parameters in the abstract linear hybrid automata (LHA) model when satisfying the safety requirements of the train control system. Then, in order to solve the state space explosion problem, the online verification method is proposed to monitor the operating status of high-speed trains online because of the real-time property of the train control system. Furthermore, we construct the LHA formal models of train tracking model and movement authority (MA) generation process as cases to illustrate the effectiveness and efficiency of the proposed method. In the first case, we obtain the constraint sets of uncertain parameters to avoid collision between trains. In the second case, the correlation of position report cycle and MA generation cycle is analyzed under both the normal and the abnormal condition influenced by packet-loss factor. Finally, considering stochastic characterization of time distributions and real-time feature of moving block control system, the transient probabilities of wireless communication process are obtained by stochastic time petri nets. - Highlights: • We solve the parameters uncertainty problem by using model-based method. • We acquire the parameter constraint sets by verifying linear hybrid automata models. • Online verification algorithms are designed to monitor the high-speed trains. • We analyze the correlation of key parameters and uncritical parameters. • The transient probabilities are obtained by using reliability analysis.
Brook, Anna; Polinova, Maria; Housh, Mashor
2016-04-01
Agriculture and agricultural landscapes are increasingly under pressure to meet the demands of a constantly increasing human population and globally changing food patterns. At the same time, there is rising concern that climate change and food security will harm agriculture in many regions of the world (Nelson et al., 2009). Facing those treats, majority of Mediterranean countries had chosen irrigated agriculture. For crop plants water is one of the most important inputs, as it is responsible for crop growth, production and it ensures the efficiency of other inputs (e.g. seeds, fertilizers and pesticide) but its use is in competition with other local sectors (e.g. industry, urban human use). Thus, well-timed availability of water is vital to agriculture for ensured yields. The increasing demand for irrigation has necessitated the need for optimal irrigation scheduling techniques that coordinate the timing and amount of irrigation to optimally manage the water use in agriculture systems. The irrigation scheduling problem can be challenging as farmers try to deal with different conflicting objectives of maximizing their yield while minimizing irrigation water use. Another challenge in the irrigation scheduling problem is attributed to the uncertain factors involved in the plant growth process during the growing season. Most notable, the climatic factors such as evapotranspiration and rainfall, these uncertain factors add a third objective to the farmer perspective, namely, minimizing the risk associated with these uncertain factors. Nevertheless, advancements in weather forecasting reduced the uncertainty level associated with future climatic data. Thus, climatic forecasts can be reliably employed to guide optimal irrigation schedule scheme when coupled with stochastic optimization models (Housh et al., 2012). Many studies have concluded that optimal irrigation decisions can provide substantial economic value over conventional irrigation decisions (Wang and Cai 2009
Solving Problem of Graph Isomorphism by Membrane-Quantum Hybrid Model
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Artiom Alhazov
2015-10-01
Full Text Available This work presents the application of new parallelization methods based on membrane-quantum hybrid computing to graph isomorphism problem solving. Applied membrane-quantum hybrid computational model was developed by authors. Massive parallelism of unconventional computing is used to implement classic brute force algorithm efficiently. This approach does not suppose any restrictions of considered graphs types. The estimated performance of the model is less then quadratic that makes a very good result for the problem of \\textbf{NP} complexity.
The software package for solving problems of mathematical modeling of isothermal curing process
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S. G. Tikhomirov
2016-01-01
Full Text Available Summary. On the basis of the general laws of sulfur vulcanization diene rubbers the principles of the effective cross-linking using a multi-component agents was discussed. It is noted that the description of the mechanism of action of the complex cross-linking systems are complicated by the diversity of interactions of components and the influence of each of them on the curing kinetics, leading to a variety technological complications of real technology and affects on the quality and technical and economic indicators of the production of rubber goods. Based on the known theoretical approaches the system analysis of isothermal curing process was performed. It included the integration of different techniques and methods into a single set of. During the analysis of the kinetics of vulcanization it was found that the formation of the spatial grid parameters vulcanizates depend on many factors, to assess which requires special mathematical and algorithmic support. As a result of the stratification of the object were identified the following major subsystems. A software package for solving direct and inverse kinetic problems isothermal curing process was developed. Information support “Isothermal vulcanization” is a set of applications of mathematical modeling of isothermal curing. It is intended for direct and inverse kinetic problems. When solving the problem of clarifying the general scheme of chemical transformations used universal mechanism including secondary chemical reactions. Functional minimization algorithm with constraints on the unknown parameters was used for solving the inverse kinetic problem. Shows a flowchart of the program. An example of solving the inverse kinetic problem with the program was introduced. Dataware was implemented in the programming language C ++. Universal dependence to determine the initial concentration of the curing agent was applied . It allowing the use of a model with different properties of multicomponent
Yusriski, R.; Sukoyo; Samadhi, T. M. A. A.; Halim, A. H.
2018-03-01
This research deals with a single machine batch scheduling model considering the influenced of learning, forgetting, and machine deterioration effects. The objective of the model is to minimize total inventory holding cost, and the decision variables are the number of batches (N), batch sizes (Q[i], i = 1, 2, .., N) and the sequence of processing the resulting batches. The parts to be processed are received at the right time and the right quantities, and all completed parts must be delivered at a common due date. We propose a heuristic procedure based on the Lagrange method to solve the problem. The effectiveness of the procedure is evaluated by comparing the resulting solution to the optimal solution obtained from the enumeration procedure using the integer composition technique and shows that the average effectiveness is 94%.
Al-Ma'shumah, Fathimah; Permana, Dony; Sidarto, Kuntjoro Adji
2015-12-01
Customer Lifetime Value is an important and useful concept in marketing. One of its benefits is to help a company for budgeting marketing expenditure for customer acquisition and customer retention. Many mathematical models have been introduced to calculate CLV considering the customer retention/migration classification scheme. A fairly new class of these models which will be described in this paper uses Markov Chain Models (MCM). This class of models has the major advantage for its flexibility to be modified to several different cases/classification schemes. In this model, the probabilities of customer retention and acquisition play an important role. From Pfeifer and Carraway, 2000, the final formula of CLV obtained from MCM usually contains nonlinear form of the transition probability matrix. This nonlinearity makes the inverse problem of CLV difficult to solve. This paper aims to solve this inverse problem, yielding the approximate transition probabilities for the customers, by applying metaheuristic optimization algorithm developed by Yang, 2013, Flower Pollination Algorithm. The major interpretation of obtaining the transition probabilities are to set goals for marketing teams in keeping the relative frequencies of customer acquisition and customer retention.
Comparative Study on a Solving Model and Algorithm for a Flush Air Data Sensing System
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Yanbin Liu
2014-05-01
Full Text Available With the development of high-performance aircraft, precise air data are necessary to complete challenging tasks such as flight maneuvering with large angles of attack and high speed. As a result, the flush air data sensing system (FADS was developed to satisfy the stricter control demands. In this paper, comparative stuides on the solving model and algorithm for FADS are conducted. First, the basic principles of FADS are given to elucidate the nonlinear relations between the inputs and the outputs. Then, several different solving models and algorithms of FADS are provided to compute the air data, including the angle of attck, sideslip angle, dynamic pressure and static pressure. Afterwards, the evaluation criteria of the resulting models and algorithms are discussed to satisfy the real design demands. Futhermore, a simulation using these algorithms is performed to identify the properites of the distinct models and algorithms such as the measuring precision and real-time features. The advantages of these models and algorithms corresponding to the different flight conditions are also analyzed, furthermore, some suggestions on their engineering applications are proposed to help future research.
Solving the flavour problem in supersymmetric Standard Models with three Higgs families
International Nuclear Information System (INIS)
Howl, R.; King, S.F.
2010-01-01
We show how a non-Abelian family symmetry Δ 27 can be used to solve the flavour problem of supersymmetric Standard Models containing three Higgs families such as the Exceptional Supersymmetric Standard Model (E 6 SSM). The three 27-dimensional families of the E 6 SSM, including the three families of Higgs fields, transform in a triplet representation of the Δ 27 family symmetry, allowing the family symmetry to commute with a possible high energy E 6 symmetry. The Δ 27 family symmetry here provides a high energy understanding of the Z 2 H symmetry of the E 6 SSM, which solves the flavour changing neutral current problem of the three families of Higgs fields. The main phenomenological predictions of the model are tri-bi-maximal mixing for leptons, two almost degenerate LSPs and two almost degenerate families of colour triplet D-fermions, providing a clear prediction for the LHC. In addition the model predicts PGBs with masses below the TeV scale, and possibly much lighter, which appears to be a quite general and robust prediction of all models based on the D-term vacuum alignment mechanism.
The Dreyfus model of clinical problem-solving skills acquisition: a critical perspective.
Peña, Adolfo
2010-06-14
The Dreyfus model describes how individuals progress through various levels in their acquisition of skills and subsumes ideas with regard to how individuals learn. Such a model is being accepted almost without debate from physicians to explain the 'acquisition' of clinical skills. This paper reviews such a model, discusses several controversial points, clarifies what kind of knowledge the model is about, and examines its coherence in terms of problem-solving skills. Dreyfus' main idea that intuition is a major aspect of expertise is also discussed in some detail. Relevant scientific evidence from cognitive science, psychology, and neuroscience is reviewed to accomplish these aims. Although the Dreyfus model may partially explain the 'acquisition' of some skills, it is debatable if it can explain the acquisition of clinical skills. The complex nature of clinical problem-solving skills and the rich interplay between the implicit and explicit forms of knowledge must be taken into consideration when we want to explain 'acquisition' of clinical skills. The idea that experts work from intuition, not from reason, should be evaluated carefully.
A hybrid flow shop model for an ice cream production scheduling problem
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Imma Ribas Vila
2009-07-01
Full Text Available Normal 0 21 false false false ES X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Taula 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:10.0pt; font-family:"Times New Roman","serif";} In this paper we address the scheduling problem that comes from an ice cream manufacturing company. This production system can be modelled as a three stage nowait hybrid flow shop with batch dependent setup costs. To contribute reducing the gap between theory and practice we have considered the real constraints and the criteria used by planners. The problem considered has been formulated as a mixed integer programming. Further, two competitive heuristic procedures have been developed and one of them will be proposed to schedule in the ice cream factory.
GeoGebra Assist Discovery Learning Model for Problem Solving Ability and Attitude toward Mathematics
Murni, V.; Sariyasa, S.; Ardana, I. M.
2017-09-01
This study aims to describe the effet of GeoGebra utilization in the discovery learning model on mathematical problem solving ability and students’ attitude toward mathematics. This research was quasi experimental and post-test only control group design was used in this study. The population in this study was 181 of students. The sampling technique used was cluster random sampling, so the sample in this study was 120 students divided into 4 classes, 2 classes for the experimental class and 2 classes for the control class. Data were analyzed by using one way MANOVA. The results of data analysis showed that the utilization of GeoGebra in discovery learning can lead to solving problems and attitudes towards mathematics are better. This is because the presentation of problems using geogebra can assist students in identifying and solving problems and attracting students’ interest because geogebra provides an immediate response process to students. The results of the research are the utilization of geogebra in the discovery learning can be applied in learning and teaching wider subject matter, beside subject matter in this study.
Bastani, Ali Foroush; Dastgerdi, Maryam Vahid; Mighani, Abolfazl
2018-06-01
The main aim of this paper is the analytical and numerical study of a time-dependent second-order nonlinear partial differential equation (PDE) arising from the endogenous stochastic volatility model, introduced in [Bensoussan, A., Crouhy, M. and Galai, D., Stochastic equity volatility related to the leverage effect (I): equity volatility behavior. Applied Mathematical Finance, 1, 63-85, 1994]. As the first step, we derive a consistent set of initial and boundary conditions to complement the PDE, when the firm is financed by equity and debt. In the sequel, we propose a Newton-based iteration scheme for nonlinear parabolic PDEs which is an extension of a method for solving elliptic partial differential equations introduced in [Fasshauer, G. E., Newton iteration with multiquadrics for the solution of nonlinear PDEs. Computers and Mathematics with Applications, 43, 423-438, 2002]. The scheme is based on multilevel collocation using radial basis functions (RBFs) to solve the resulting locally linearized elliptic PDEs obtained at each level of the Newton iteration. We show the effectiveness of the resulting framework by solving a prototypical example from the field and compare the results with those obtained from three different techniques: (1) a finite difference discretization; (2) a naive RBF collocation and (3) a benchmark approximation, introduced for the first time in this paper. The numerical results confirm the robustness, higher convergence rate and good stability properties of the proposed scheme compared to other alternatives. We also comment on some possible research directions in this field.
Manufacturing scheduling systems an integrated view on models, methods and tools
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...
Directory of Open Access Journals (Sweden)
Maoyuan Feng
2014-01-01
Full Text Available This study proposes a mixed integer linear programming (MILP model to optimize the spillways scheduling for reservoir flood control. Unlike the conventional reservoir operation model, the proposed MILP model specifies the spillways status (including the number of spillways to be open and the degree of the spillway opened instead of reservoir release, since the release is actually controlled by using the spillway. The piecewise linear approximation is used to formulate the relationship between the reservoir storage and water release for a spillway, which should be open/closed with a status depicted by a binary variable. The control order and symmetry rules of spillways are described and incorporated into the constraints for meeting the practical demand. Thus, a MILP model is set up to minimize the maximum reservoir storage. The General Algebraic Modeling System (GAMS and IBM ILOG CPLEX Optimization Studio (CPLEX software are used to find the optimal solution for the proposed MILP model. The China’s Three Gorges Reservoir, whose spillways are of five types with the total number of 80, is selected as the case study. It is shown that the proposed model decreases the flood risk compared with the conventional operation and makes the operation more practical by specifying the spillways status directly.
International Nuclear Information System (INIS)
Strigari, Lidia; Pedicini, Piernicola; D’Andrea, Marco; Pinnarò, Paola; Marucci, Laura; Giordano, Carolina; Benassi, Marcello
2012-01-01
Purpose: One of the worst radiation-induced acute effects in treating head-and-neck (HN) cancer is grade 3 or higher acute (oral and pharyngeal) mucosal toxicity (AMT), caused by the killing/depletion of mucosa cells. Here we aim to testing a predictive model of the AMT in HN cancer patients receiving different radiotherapy schedules. Methods and Materials: Various radiotherapeutic schedules have been reviewed and classified as tolerable or intolerable based on AMT severity. A modified normal tissue complication probability (NTCP) model has been investigated to describe AMT data in radiotherapy regimens, both conventional and altered in dose and overall treatment time (OTT). We tested the hypothesis that such a model could also be applied to identify intolerable treatment and to predict AMT. This AMT NTCP model has been compared with other published predictive models to identify schedules that are either tolerable or intolerable. The area under the curve (AUC) was calculated for all models, assuming treatment tolerance as the gold standard. The correlation between AMT and the predicted toxicity rate was assessed by a Pearson correlation test. Results: The AMT NTCP model was able to distinguish between acceptable and intolerable schedules among the data available for the study (AUC = 0.84, 95% confidence interval = 0.75-0.92). In the equivalent dose at 2 Gy/fraction (EQD2) vs OTT space, the proposed model shows a trend similar to that of models proposed by other authors, but was superior in detecting some intolerable schedules. Moreover, it was able to predict the incidence of ≥G3 AMT. Conclusion: The proposed model is able to predict ≥G3 AMT after HN cancer radiotherapy, and could be useful for designing altered/hypofractionated schedules to reduce the incidence of AMT.
Work Scheduling by Use of Worker Model in Consideration of Learning by On-The-Job Training
Tateno, Toshitake; Shimizu, Keiko
This paper deals with a method of scheduling manual work in consideration of learning by on-the-job training (OJT). In skilled work such as maintenance of trains and airplanes, workers must learn many tasks by OJT. While the work processing time of novice workers is longer than that of experts, the time will be reduced with repeated OJT. Therefore, OJT is important for maintaining the skill level and the long-term work efficiency of an organization. In order to devise a schedule considering OJT, the scheduler must incorporate a management function of workers to trace dynamically changing work experience. In this paper, after the relationship between scheduling problems and worker management problems is defined, a simulation method, in which a worker model and an agent-based mechanism are utilized, is proposed to derive the optimal OJT strategy toward high long-term performance. Finally, we present some case studies showing the effectiveness of OJT planning based on the simulation.
A three-stage heuristic for harvest scheduling with access road network development
Mark M. Clark; Russell D. Meller; Timothy P. McDonald
2000-01-01
In this article we present a new model for the scheduling of forest harvesting with spatial and temporal constraints. Our approach is unique in that we incorporate access road network development into the harvest scheduling selection process. Due to the difficulty of solving the problem optimally, we develop a heuristic that consists of a solution construction stage...
Job shop scheduling with makespan objective: A heuristic approach
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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.
A theory of solving TAP equations for Ising models with general invariant random matrices
DEFF Research Database (Denmark)
Opper, Manfred; Çakmak, Burak; Winther, Ole
2016-01-01
We consider the problem of solving TAP mean field equations by iteration for Ising models with coupling matrices that are drawn at random from general invariant ensembles. We develop an analysis of iterative algorithms using a dynamical functional approach that in the thermodynamic limit yields...... the iteration dependent on a Gaussian distributed field only. The TAP magnetizations are stable fixed points if a de Almeida–Thouless stability criterion is fulfilled. We illustrate our method explicitly for coupling matrices drawn from the random orthogonal ensemble....
King, Michael S
2008-12-01
Increasingly courts are using new approaches that promote a more comprehensive resolution of legal problems, minimise any negative effects that legal processes have on participant wellbeing and/or that use legal processes to promote participant wellbeing. Therapeutic jurisprudence, restorative justice, mediation and problem-solving courts are examples. This article suggests a model for the use of these processes in the coroner's court to minimise negative effects of coroner's court processes on the bereaved and to promote a more comprehensive resolution of matters at issue, including the determination of the cause of death and the public health and safety promotion role of the coroner.
Modeling digital pulse waveforms by solving one-dimensional Navier-stokes equations.
Fedotov, Aleksandr A; Akulova, Anna S; Akulov, Sergey A
2016-08-01
Mathematical modeling for composition distal arterial pulse wave in the blood vessels of the upper limbs was considered. Formation of distal arterial pulse wave is represented as a composition of forward and reflected pulse waves propagating along the arterial vessels. The formal analogy between pulse waves propagation along the human arterial system and the propagation of electrical oscillations in electrical transmission lines with distributed parameters was proposed. Dependencies of pulse wave propagation along the human arterial system were obtained by solving the one-dimensional Navier-Stokes equations for a few special cases.
Optimal scheduling of coproduction with a storage
International Nuclear Information System (INIS)
Ravn, H.F.; Rygard, J.M.
1993-02-01
We consider the problem of optimal scheduling of a system with combined heat and heat (CHP) units and a heat storege. The purpose of the heat storage is to permit a partial decoupling of the variations in the demand for heat and electrical power. We formulate the problem of optimal scheduling as that of minimizing the total costs over the planning period. The heat demand from the district heating system and the ''shadow prices'' for the electrical power system are taken as externally given parameters. The resulting model is solved by dynamic programming. We describe implementation details and we give examples of result of the optimization. (au) (12 refs.)
Basic problems solving for two-dimensional discrete 3 × 4 order hidden markov model
International Nuclear Information System (INIS)
Wang, Guo-gang; Gan, Zong-liang; Tang, Gui-jin; Cui, Zi-guan; Zhu, Xiu-chang
2016-01-01
A novel model is proposed to overcome the shortages of the classical hypothesis of the two-dimensional discrete hidden Markov model. In the proposed model, the state transition probability depends on not only immediate horizontal and vertical states but also on immediate diagonal state, and the observation symbol probability depends on not only current state but also on immediate horizontal, vertical and diagonal states. This paper defines the structure of the model, and studies the three basic problems of the model, including probability calculation, path backtracking and parameters estimation. By exploiting the idea that the sequences of states on rows or columns of the model can be seen as states of a one-dimensional discrete 1 × 2 order hidden Markov model, several algorithms solving the three questions are theoretically derived. Simulation results further demonstrate the performance of the algorithms. Compared with the two-dimensional discrete hidden Markov model, there are more statistical characteristics in the structure of the proposed model, therefore the proposed model theoretically can more accurately describe some practical problems.
On the modeling of uplink inter-cell interference based on proportional fair scheduling
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.
Mathematical Model and Algorithm for the Reefer Mechanic Scheduling Problem at Seaports
Directory of Open Access Journals (Sweden)
Jiantong Zhang
2017-01-01
Full Text Available With the development of seaborne logistics, the international trade of goods transported in refrigerated containers is growing fast. Refrigerated containers, also known as reefers, are used in transportation of temperature sensitive cargo, such as perishable fruits. This trend brings new challenges to terminal managers, that is, how to efficiently arrange mechanics to plug and unplug power for the reefers (i.e., tasks at yards. This work investigates the reefer mechanics scheduling problem at container ports. To minimize the sum of the total tardiness of all tasks and the total working distance of all mechanics, we formulate a mathematical model. For the resolution of this problem, we propose a DE algorithm which is combined with efficient heuristics, local search strategies, and parameter adaption scheme. The proposed algorithm is tested and validated through numerical experiments. Computational results demonstrate the effectiveness and efficiency of the proposed algorithm.
Scheduling Model for Renewable Energy Sources Integration in an Insular Power System
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Gerardo J. Osório
2018-01-01
Full Text Available Insular power systems represent an asset and an excellent starting point for the development and analysis of innovative tools and technologies. The integration of renewable energy resources that has taken place in several islands in the south of Europe, particularly in Portugal, has brought more uncertainty to production management. In this work, an innovative scheduling model is proposed, which considers the integration of wind and solar resources in an insular power system in Portugal, with a strong conventional generation basis. This study aims to show the benefits of increasing the integration of renewable energy resources in this insular power system, and the objectives are related to minimizing the time for which conventional generation is in operation, maximizing profits, reducing production costs, and consequently, reducing greenhouse gas emissions.
On the modeling of uplink inter-cell interference based on proportional fair scheduling
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.
An adaptive time-stepping strategy for solving the phase field crystal model
International Nuclear Information System (INIS)
Zhang, Zhengru; Ma, Yuan; Qiao, Zhonghua
2013-01-01
In this work, we will propose an adaptive time step method for simulating the dynamics of the phase field crystal (PFC) model. The numerical simulation of the PFC model needs long time to reach steady state, and then large time-stepping method is necessary. Unconditionally energy stable schemes are used to solve the PFC model. The time steps are adaptively determined based on the time derivative of the corresponding energy. It is found that the use of the proposed time step adaptivity cannot only resolve the steady state solution, but also the dynamical development of the solution efficiently and accurately. The numerical experiments demonstrate that the CPU time is significantly saved for long time simulations
Investigating and developing engineering students' mathematical modelling and problem-solving skills
Wedelin, Dag; Adawi, Tom; Jahan, Tabassum; Andersson, Sven
2015-09-01
How do engineering students approach mathematical modelling problems and how can they learn to deal with such problems? In the context of a course in mathematical modelling and problem solving, and using a qualitative case study approach, we found that the students had little prior experience of mathematical modelling. They were also inexperienced problem solvers, unaware of the importance of understanding the problem and exploring alternatives, and impeded by inappropriate beliefs, attitudes and expectations. Important impacts of the course belong to the metacognitive domain. The nature of the problems, the supervision and the follow-up lectures were emphasised as contributing to the impacts of the course, where students show major development. We discuss these empirical results in relation to a framework for mathematical thinking and the notion of cognitive apprenticeship. Based on the results, we argue that this kind of teaching should be considered in the education of all engineers.
Solving bi-level optimization problems in engineering design using kriging models
Xia, Yi; Liu, Xiaojie; Du, Gang
2018-05-01
Stackelberg game-theoretic approaches are applied extensively in engineering design to handle distributed collaboration decisions. Bi-level genetic algorithms (BLGAs) and response surfaces have been used to solve the corresponding bi-level programming models. However, the computational costs for BLGAs often increase rapidly with the complexity of lower-level programs, and optimal solution functions sometimes cannot be approximated by response surfaces. This article proposes a new method, namely the optimal solution function approximation by kriging model (OSFAKM), in which kriging models are used to approximate the optimal solution functions. A detailed example demonstrates that OSFAKM can obtain better solutions than BLGAs and response surface-based methods, and at the same time reduce the workload of computation remarkably. Five benchmark problems and a case study of the optimal design of a thin-walled pressure vessel are also presented to illustrate the feasibility and potential of the proposed method for bi-level optimization in engineering design.
Self-management model in the scheduling of successive appointments in rheumatology.
Castro Corredor, David; Cuadra Díaz, José Luis; Mateos Rodríguez, Javier José; Anino Fernández, Joaquín; Mínguez Sánchez, María Dolores; de Lara Simón, Isabel María; Tébar, María Ángeles; Añó, Encarnación; Sanz, María Dolores; Ballester, María Nieves
2018-01-08
The rheumatology service of Ciudad Real Hospital, located in an autonomous community of that same name that is nearly in the center of Spain, implemented a self-management model of successive appointments more than 10 years ago. Since then, the physicians of the department schedule follow-up visits for their patients depending on the disease, its course and ancillary tests. The purpose of this study is to evaluate and compare the self-management model for successive appointments in the rheumatology service of Ciudad Real Hospital versus the model of external appointment management implemented in 8 of the hospital's 15 medical services. A comparative and multivariate analysis was performed to identify variables with statistically significant differences, in terms of activity and/or performance indicators and quality perceived by users. The comparison involved the self-management model for successive appointments employed in the rheumatology service of Ciudad Real Hospital and the model for external appointment management used in 8 hospital medical services between January 1 and May 31, 2016. In a database with more than 100,000 records of appointments involving the set of services included in the study, the mean waiting time and the numbers of non-appearances and rescheduling of follow-up visits in the rheumatology department were significantly lower than in the other services. The number of individuals treated in outpatient rheumatology services was 7,768, and a total of 280 patients were surveyed (response rate 63.21%). They showed great overall satisfaction, and the incidence rate of claims was low. Our results show that the self-management model of scheduling appointments has better results in terms of activity indicators and in quality perceived by users, despite the intense activity. Thus, this study could be fundamental for decision making in the management of health care organizations. Copyright © 2017 Elsevier España, S.L.U. and Sociedad Española de
Liao, F.
2016-01-01
Multi-state supernetworks have been advanced recently for modeling individual activity-travel scheduling decisions. The main advantage is that multi-dimensional choice facets are modeled simultaneously within an integral framework, supporting systematic assessments of a large spectrum of policies
Using genetic algorithm to solve a new multi-period stochastic optimization model
Zhang, Xin-Li; Zhang, Ke-Cun
2009-09-01
This paper presents a new asset allocation model based on the CVaR risk measure and transaction costs. Institutional investors manage their strategic asset mix over time to achieve favorable returns subject to various uncertainties, policy and legal constraints, and other requirements. One may use a multi-period portfolio optimization model in order to determine an optimal asset mix. Recently, an alternative stochastic programming model with simulated paths was proposed by Hibiki [N. Hibiki, A hybrid simulation/tree multi-period stochastic programming model for optimal asset allocation, in: H. Takahashi, (Ed.) The Japanese Association of Financial Econometrics and Engineering, JAFFE Journal (2001) 89-119 (in Japanese); N. Hibiki A hybrid simulation/tree stochastic optimization model for dynamic asset allocation, in: B. Scherer (Ed.), Asset and Liability Management Tools: A Handbook for Best Practice, Risk Books, 2003, pp. 269-294], which was called a hybrid model. However, the transaction costs weren't considered in that paper. In this paper, we improve Hibiki's model in the following aspects: (1) The risk measure CVaR is introduced to control the wealth loss risk while maximizing the expected utility; (2) Typical market imperfections such as short sale constraints, proportional transaction costs are considered simultaneously. (3) Applying a genetic algorithm to solve the resulting model is discussed in detail. Numerical results show the suitability and feasibility of our methodology.
Directory of Open Access Journals (Sweden)
Yin Luo
2012-01-01
Full Text Available Traditional pump scheduling models neglect the operation reliability which directly relates with the unscheduled maintenance cost and the wear cost during the operation. Just for this, based on the assumption that the vibration directly relates with the operation reliability and the degree of wear, it could express the operation reliability as the normalization of the vibration level. The characteristic of the vibration with the operation point was studied, it could be concluded that idealized flow versus vibration plot should be a distinct bathtub shape. There is a narrow sweet spot (80 to 100 percent BEP to obtain low vibration levels in this shape, and the vibration also follows similar law with the square of the rotation speed without resonance phenomena. Then, the operation reliability could be modeled as the function of the capacity and rotation speed of the pump and add this function to the traditional model to form the new. And contrast with the tradition method, the result shown that the new model could fix the result produced by the traditional, make the pump operate in low vibration, then the operation reliability could increase and the maintenance cost could decrease.
A prediction model to forecast the cost impact from a break in the production schedule
Delionback, L. M.
1977-01-01
The losses which are experienced after a break or stoppage in sequence of a production cycle portends an extremely complex situation and involves numerous variables, some of uncertain quantity and quality. There are no discrete formulas to define the losses during a gap in production. The techniques which are employed are therefore related to a prediction or forecast of the losses that take place, based on the conditions which exist in the production environment. Such parameters as learning curve slope, number of predecessor units, and length of time the production sequence is halted are utilized in formulating a prediction model. The pertinent current publications related to this subject are few in number, but are reviewed to provide an understanding of the problem. Example problems are illustrated together with appropriate trend curves to show the approach. Solved problems are also given to show the application of the models to actual cases or production breaks in the real world.
Moreno-Camacho, Carlos A.; Montoya-Torres, Jairo R.; Vélez-Gallego, Mario C.
2018-06-01
Only a few studies in the available scientific literature address the problem of having a group of workers that do not share identical levels of productivity during the planning horizon. This study considers a workforce scheduling problem in which the actual processing time is a function of the scheduling sequence to represent the decline in workers' performance, evaluating two classical performance measures separately: makespan and maximum tardiness. Several mathematical models are compared with each other to highlight the advantages of each approach. The mathematical models are tested with randomly generated instances available from a public e-library.
A simple but accurate procedure for solving the five-parameter model
International Nuclear Information System (INIS)
Mares, Oana; Paulescu, Marius; Badescu, Viorel
2015-01-01
Highlights: • A new procedure for extracting the parameters of the one-diode model is proposed. • Only the basic information listed in the datasheet of PV modules are required. • Results demonstrate a simple, robust and accurate procedure. - Abstract: The current–voltage characteristic of a photovoltaic module is typically evaluated by using a model based on the solar cell equivalent circuit. The complexity of the procedure applied for extracting the model parameters depends on data available in manufacture’s datasheet. Since the datasheet is not detailed enough, simplified models have to be used in many cases. This paper proposes a new procedure for extracting the parameters of the one-diode model in standard test conditions, using only the basic data listed by all manufactures in datasheet (short circuit current, open circuit voltage and maximum power point). The procedure is validated by using manufacturers’ data for six commercially crystalline silicon photovoltaic modules. Comparing the computed and measured current–voltage characteristics the determination coefficient is in the range 0.976–0.998. Thus, the proposed procedure represents a feasible tool for solving the five-parameter model applied to crystalline silicon photovoltaic modules. The procedure is described in detail, to guide potential users to derive similar models for other types of photovoltaic modules.
Numerical simulation of the two-phase flows in a hydraulic coupling by solving VOF model
International Nuclear Information System (INIS)
Luo, Y; Zuo, Z G; Liu, S H; Fan, H G; Zhuge, W L
2013-01-01
The flow in a partially filled hydraulic coupling is essentially a gas-liquid two-phase flow, in which the distribution of two phases has significant influence on its characteristics. The interfaces between the air and the liquid, and the circulating flows inside the hydraulic coupling can be simulated by solving the VOF two-phase model. In this paper, PISO algorithm and RNG k–ε turbulence model were employed to simulate the phase distribution and the flow field in a hydraulic coupling with 80% liquid fill. The results indicate that the flow forms a circulating movement on the torus section with decreasing speed ratio. In the pump impeller, the air phase mostly accumulates on the suction side of the blades, while liquid on the pressure side; in turbine runner, air locates in the middle of the flow passage. Flow separations appear near the blades and the enclosing boundaries of the hydraulic coupling
International Nuclear Information System (INIS)
Gelß, Patrick; Matera, Sebastian; Schütte, Christof
2016-01-01
In multiscale modeling of heterogeneous catalytic processes, one crucial point is the solution of a Markovian master equation describing the stochastic reaction kinetics. Usually, this is too high-dimensional to be solved with standard numerical techniques and one has to rely on sampling approaches based on the kinetic Monte Carlo method. In this study we break the curse of dimensionality for the direct solution of the Markovian master equation by exploiting the Tensor Train Format for this purpose. The performance of the approach is demonstrated on a first principles based, reduced model for the CO oxidation on the RuO 2 (110) surface. We investigate the complexity for increasing system size and for various reaction conditions. The advantage over the stochastic simulation approach is illustrated by a problem with increased stiffness.
Gelß, Patrick; Matera, Sebastian; Schütte, Christof
2016-06-01
In multiscale modeling of heterogeneous catalytic processes, one crucial point is the solution of a Markovian master equation describing the stochastic reaction kinetics. Usually, this is too high-dimensional to be solved with standard numerical techniques and one has to rely on sampling approaches based on the kinetic Monte Carlo method. In this study we break the curse of dimensionality for the direct solution of the Markovian master equation by exploiting the Tensor Train Format for this purpose. The performance of the approach is demonstrated on a first principles based, reduced model for the CO oxidation on the RuO2(110) surface. We investigate the complexity for increasing system size and for various reaction conditions. The advantage over the stochastic simulation approach is illustrated by a problem with increased stiffness.
Energy Technology Data Exchange (ETDEWEB)
Gelß, Patrick, E-mail: p.gelss@fu-berlin.de; Matera, Sebastian, E-mail: matera@math.fu-berlin.de; Schütte, Christof, E-mail: schuette@mi.fu-berlin.de
2016-06-01
In multiscale modeling of heterogeneous catalytic processes, one crucial point is the solution of a Markovian master equation describing the stochastic reaction kinetics. Usually, this is too high-dimensional to be solved with standard numerical techniques and one has to rely on sampling approaches based on the kinetic Monte Carlo method. In this study we break the curse of dimensionality for the direct solution of the Markovian master equation by exploiting the Tensor Train Format for this purpose. The performance of the approach is demonstrated on a first principles based, reduced model for the CO oxidation on the RuO{sub 2}(110) surface. We investigate the complexity for increasing system size and for various reaction conditions. The advantage over the stochastic simulation approach is illustrated by a problem with increased stiffness.
Data analysis with the DIANA meta-scheduling approach
International Nuclear Information System (INIS)
Anjum, A; McClatchey, R; Willers, I
2008-01-01
The concepts, design and evaluation of the Data Intensive and Network Aware (DIANA) meta-scheduling approach for solving the challenges of data analysis being faced by CERN experiments are discussed in this paper. Our results suggest that data analysis can be made robust by employing fault tolerant and decentralized meta-scheduling algorithms supported in our DIANA meta-scheduler. The DIANA meta-scheduler supports data intensive bulk scheduling, is network aware and follows a policy centric meta-scheduling. In this paper, we demonstrate that a decentralized and dynamic meta-scheduling approach is an effective strategy to cope with increasing numbers of users, jobs and datasets. We present 'quality of service' related statistics for physics analysis through the application of a policy centric fair-share scheduling model. The DIANA meta-schedulers create a peer-to-peer hierarchy of schedulers to accomplish resource management that changes with evolving loads and is dynamic and adapts to the volatile nature of the resources
Beautiful Models: 70 Years of Exactly Solved Quantum Many-Body Problems
International Nuclear Information System (INIS)
Batchelor, M T
2005-01-01
A key element of theoretical physics is the conceptualisation of physical phenomena in terms of models, which are then investigated by the tools at hand. For quantum many-body systems, some models can be exactly solved, i.e., their physical properties can be calculated in an exact fashion. There is often a deep underlying reason why this can be done-the theory of integrability-which manifests itself in many guises. In Beautiful models, Bill Sutherland looks at exactly solved models in quantum many-body systems, a well established field dating back to Bethe's 1931 exact solution of the spin-1/2 Heisenberg chain. This field is enjoying a renaissance due to the ongoing and striking experimental advances in low-dimensional quantum physics, which includes the manufacture of quasi one-dimensional quantum gases. Apart from the intrinsic beauty of the subject material, Beautiful Models is written by a pioneering master of the field. Sutherland has aimed to provide a broad textbook style introduction to the subject for graduate students and interested non-experts. An important point here is the 'language' of the book. In Sutherland's words, the subject of exactly solved models 'belongs to the realm of mathematical physics-too mathematical to be 'respectable' physics, yet not rigorous enough to be 'real' mathematics. ...there are perennial attempts to translate this body of work into either respectable physics or real mathematics; this is not that sort of book.' Rather, Sutherland discusses the models and their solutions in terms of their 'intrinisic' language, which is largely as found in the physics literature. The book begins with a helpful overview of the contents and then moves on to the foundation material, which is the chapter on integrability and non-diffraction. As is shown, these two concepts go hand in hand. The topics covered in later chapters include models with δ-function potentials, the Heisenberg spin chain, the Hubbard model, exchange models, the Calogero
Beautiful Models: 70 Years of Exactly Solved Quantum Many-Body Problems
Energy Technology Data Exchange (ETDEWEB)
Batchelor, M T [Department of Theoretical Physics, RSPSE and Department of Mathematics, MSI, Australian National University, Canberra ACT 0200 (Australia)
2005-04-08
A key element of theoretical physics is the conceptualisation of physical phenomena in terms of models, which are then investigated by the tools at hand. For quantum many-body systems, some models can be exactly solved, i.e., their physical properties can be calculated in an exact fashion. There is often a deep underlying reason why this can be done-the theory of integrability-which manifests itself in many guises. In Beautiful models, Bill Sutherland looks at exactly solved models in quantum many-body systems, a well established field dating back to Bethe's 1931 exact solution of the spin-1/2 Heisenberg chain. This field is enjoying a renaissance due to the ongoing and striking experimental advances in low-dimensional quantum physics, which includes the manufacture of quasi one-dimensional quantum gases. Apart from the intrinsic beauty of the subject material, Beautiful Models is written by a pioneering master of the field. Sutherland has aimed to provide a broad textbook style introduction to the subject for graduate students and interested non-experts. An important point here is the 'language' of the book. In Sutherland's words, the subject of exactly solved models 'belongs to the realm of mathematical physics-too mathematical to be 'respectable' physics, yet not rigorous enough to be 'real' mathematics. ...there are perennial attempts to translate this body of work into either respectable physics or real mathematics; this is not that sort of book.' Rather, Sutherland discusses the models and their solutions in terms of their 'intrinisic' language, which is largely as found in the physics literature. The book begins with a helpful overview of the contents and then moves on to the foundation material, which is the chapter on integrability and non-diffraction. As is shown, these two concepts go hand in hand. The topics covered in later chapters include models with {delta}-function potentials, the
International Nuclear Information System (INIS)
Ju, Liwei; Li, Huanhuan; Zhao, Junwei; Chen, Kangting; Tan, Qingkun; Tan, Zhongfu
2016-01-01
Highlights: • Our research focuses on virtual power plant. • Electric vehicle group and demand response are integrated into virtual power plant. • Stochastic chance constraint planning is applied to overcome uncertainties. • A multi-objective stochastic scheduling model is proposed for virtual power plant. • A three-stage hybrid intelligent solution algorithm is proposed for solving the model. - Abstract: A stochastic chance-constrained planning method is applied to build a multi-objective optimization model for virtual power plant scheduling. Firstly, the implementation cost of demand response is calculated using the system income difference. Secondly, a wind power plant, photovoltaic power, an electric vehicle group and a conventional power plant are aggregated into a virtual power plant. A stochastic scheduling model is proposed for the virtual power plant, considering uncertainties under three objective functions. Thirdly, a three-stage hybrid intelligent solution algorithm is proposed, featuring the particle swarm optimization algorithm, the entropy weight method and the fuzzy satisfaction theory. Finally, the Yunnan distributed power demonstration project in China is utilized for example analysis. Simulation results demonstrate that when considering uncertainties, the system will reduce the grid connection of the wind power plant and photovoltaic power to decrease the power shortage punishment cost. The average reduction of the system power shortage punishment cost and the operation revenue of virtual power plant are 61.5% and 1.76%, respectively, while the average increase of the system abandoned energy cost is 40.4%. The output of the virtual power plant exhibits a reverse distribution with the confidence degree of the uncertainty variable. The proposed algorithm rapidly calculates a global optimal set. The electric vehicle group could provide spinning reserve to ensure stability of the output of the virtual power plant. Demand response could
Procedure to Solve Network DEA Based on a Virtual Gap Measurement Model
Directory of Open Access Journals (Sweden)
Fuh-hwa Franklin Liu
2017-01-01
Full Text Available Network DEA models assess production systems that contain a set of network-structured subsystems. Each subsystem has input and output measures from and to the external network and has intermediate measures that link to other subsystems. Most published studies demonstrate how to employ DEA models to establish network DEA models. Neither static nor dynamic network DEA models adjust the links. This paper applies the virtual gap measurement (VGM model to construct a mixed integer program to solve dynamic network DEA problems. The mixed integer program sets the total numbers of “as-input” and “as-output” equal to the total number of links in the objective function. To obtain the best-practice efficiency, each DMU determines a set of weights for inputs, outputs, and links. The links are played either “as-input” or “as-output.” Input and as-input measures reduce slack, whereas output and as-output measures increase slacks to attain their target on the production frontier.
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.
Tan, Kian Lam; Lim, Chen Kim
2017-10-01
With the explosive growth of online information such as email messages, news articles, and scientific literature, many institutions and museums are converting their cultural collections from physical data to digital format. However, this conversion resulted in the issues of inconsistency and incompleteness. Besides, the usage of inaccurate keywords also resulted in short query problem. Most of the time, the inconsistency and incompleteness are caused by the aggregation fault in annotating a document itself while the short query problem is caused by naive user who has prior knowledge and experience in cultural heritage domain. In this paper, we presented an approach to solve the problem of inconsistency, incompleteness and short query by incorporating the Term Similarity Matrix into the Language Model. Our approach is tested on the Cultural Heritage in CLEF (CHiC) collection which consists of short queries and documents. The results show that the proposed approach is effective and has improved the accuracy in retrieval time.
OL-DEC-MDP Model for Multiagent Online Scheduling with a Time-Dependent Probability of Success
Directory of Open Access Journals (Sweden)
Cheng Zhu
2014-01-01
Full Text Available Focusing on the on-line multiagent scheduling problem, this paper considers the time-dependent probability of success and processing duration and proposes an OL-DEC-MDP (opportunity loss-decentralized Markov Decision Processes model to include opportunity loss into scheduling decision to improve overall performance. The success probability of job processing as well as the process duration is dependent on the time at which the processing is started. The probability of completing the assigned job by an agent would be higher when the process is started earlier, but the opportunity loss could also be high due to the longer engaging duration. As a result, OL-DEC-MDP model introduces a reward function considering the opportunity loss, which is estimated based on the prediction of the upcoming jobs by a sampling method on the job arrival. Heuristic strategies are introduced in computing the best starting time for an incoming job by each agent, and an incoming job will always be scheduled to the agent with the highest reward among all agents with their best starting policies. The simulation experiments show that the OL-DEC-MDP model will improve the overall scheduling performance compared with models not considering opportunity loss in heavy-loading environment.
Mahoney, Kevin
2012-01-01
This research investigation examined the effects of Singapore's Model Method, also known as "model drawing" or "bar modeling" on the word problem-solving performance of American third and fourth grade students. Employing a single-case design, a researcher-designed teaching intervention was delivered to a child in third…
Approximating Preemptive Stochastic Scheduling
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...
National Research Council Canada - National Science Library
York, Michael A
2008-01-01
.... This capability is developed through the Fleet Readiness Training Plan (FRTP) where the Navy's carriers are scheduled in staggered 32-month cycles consisting of four phases of progressive readiness levels...
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.
Directory of Open Access Journals (Sweden)
Robert Matindi
2019-01-01
Full Text Available Modelling is an effective way of designing, understanding, and analysing bio-refinery supply chain systems. The supply chain is a complex process consisting of many systems interacting with each other. It requires the modelling of the processes in the presence of multiple autonomous entities (i.e. biomass producers, bio-processors and transporters, multiple performance measures and multiple objectives, both local and global, which together constitute very complex interaction effects. In this paper, simulation models for recovering biomass from the field of the biorefinery are developed and validated using some industry data and the minimum biomass recovery cost is established based on different strategies employed for recovering biomass. Energy densification techniques are evaluated for their net present worth and the technologies that offer greater returns for the industry are recommended. In addition, a new scheduling algorithm is also developed to enhance the process flow of the management of resources and the flow of biomass. The primary objective is to investigate different strategies to reach the lowest cost delivery of sugarcane harvest residue to a sugar factory through optimally located bio-refineries. A simulation /optimisation solution approach is also developed to tackle the stochastic variables in the bioenergy production system based on different statistical distributions such as Weibull and Pearson distributions. In this approach, a genetic algorithm is integrated with simulation to improve the initial solution and search the near-optimal solution. A case study is conducted to illustrate the results and to validate the applicability for the real world implementation using ExtendSIM Simulation software using some real data from Australian Mills.
Optimal Scheduling of Domestic Appliances via MILP
Directory of Open Access Journals (Sweden)
Zdenek Bradac
2014-12-01
Full Text Available This paper analyzes a consumption scheduling mechanism for domestic appliances within a home area network. The aim of the proposed scheduling is to minimize the total energy price paid by the consumer and to reduce power peaks in order to achieve a balanced daily load schedule. An exact and computationally efficient mixed-integer linear programming (MILP formulation of the problem is presented. This model is verified by several problem instances. Realistic scenarios based on the real price tariffs commercially available in the Czech Republic are calculated. The results obtained by solving the optimization problem are compared with a simulation of the ripple control service currently used by many domestic consumers in the Czech Republic.
Modeling and solving a large-scale generation expansion planning problem under uncertainty
Energy Technology Data Exchange (ETDEWEB)
Jin, Shan; Ryan, Sarah M. [Iowa State University, Department of Industrial and Manufacturing Systems Engineering, Ames (United States); Watson, Jean-Paul [Sandia National Laboratories, Discrete Math and Complex Systems Department, Albuquerque (United States); Woodruff, David L. [University of California Davis, Graduate School of Management, Davis (United States)
2011-11-15
We formulate a generation expansion planning problem to determine the type and quantity of power plants to be constructed over each year of an extended planning horizon, considering uncertainty regarding future demand and fuel prices. Our model is expressed as a two-stage stochastic mixed-integer program, which we use to compute solutions independently minimizing the expected cost and the Conditional Value-at-Risk; i.e., the risk of significantly larger-than-expected operational costs. We introduce stochastic process models to capture demand and fuel price uncertainty, which are in turn used to generate trees that accurately represent the uncertainty space. Using a realistic problem instance based on the Midwest US, we explore two fundamental, unexplored issues that arise when solving any stochastic generation expansion model. First, we introduce and discuss the use of an algorithm for computing confidence intervals on obtained solution costs, to account for the fact that a finite sample of scenarios was used to obtain a particular solution. Second, we analyze the nature of solutions obtained under different parameterizations of this method, to assess whether the recommended solutions themselves are invariant to changes in costs. The issues are critical for decision makers who seek truly robust recommendations for generation expansion planning. (orig.)
Lasker, Roz D; Weiss, Elisa S
2003-03-01
Over the last 40 years, thousands of communities-in the United States and internationally-have been working to broaden the involvement of people and organizations in addressing community-level problems related to health and other areas. Yet, in spite of this experience, many communities are having substantial difficulty achieving their collaborative objective, and many funders of community partnerships and participation initiatives are looking for ways to get more out of their investment. One of the reasons we are in this predicament is that the practitioners and researchers who are interested in community collaboration come from a variety of contexts, initiatives, and academic disciplines, and few of them have integrated their work with experiences or literatures beyond their own domain. In this article, we seek to overcome some of this fragmentation of effort by presenting a multidisciplinary model that lays out the pathways by which broadly participatory processes lead to more effective community problem solving and to improvements in community health. The model, which builds on a broad array of practical experience as well as conceptual and empirical work in multiple fields, is an outgrowth of a joint-learning work group that was organized to support nine communities in the Turning Point initiative. Following a detailed explication of the model, the article focuses on the implications of the model for research, practice, and policy. It describes how the model can help researchers answer the fundamental effectiveness and "how-to" questions related to community collaboration. In addition, the article explores differences between the model and current practice, suggesting strategies that can help the participants in, and funders of, community collaborations strengthen their efforts.
Directory of Open Access Journals (Sweden)
Alper DÖYEN
2007-01-01
Full Text Available The n-job, m-machine flow shop scheduling problem is one of the most general job scheduling problems. This study deals with the criteria of makespan minimization for the flow shop scheduling problem. Artificial Immune Systems (AIS are new intelligent problem solving techniques that are being used in scheduling problems. AIS can be defined as computational systems inspired by theoretical immunology, observed immune functions, principles and mechanisms in order to solve problems. In this research, a computational method based on clonal selection principle and affinity maturation mechanisms of the immune response is used. The operation parameters of meta-heuristics have an important role on the quality of the solution. Thus, a generic systematic procedure which bases on a multi-step experimental design approach for determining the efficient system parameters for AIS is presented. Experimental results show that, the artificial immune system algorithm is more efficient than both the classical heuristic flow shop scheduling algorithms and simulated annealing.
Diverse task scheduling for individualized requirements in cloud manufacturing
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.
Fasni, Nurli; Fatimah, Siti; Yulanda, Syerli
2017-05-01
This research aims to achieve some purposes such as: to know whether mathematical problem solving ability of students who have learned mathematics using Multiple Intelligences based teaching model is higher than the student who have learned mathematics using cooperative learning; to know the improvement of the mathematical problem solving ability of the student who have learned mathematics using Multiple Intelligences based teaching model., to know the improvement of the mathematical problem solving ability of the student who have learned mathematics using cooperative learning; to know the attitude of the students to Multiple Intelligences based teaching model. The method employed here is quasi-experiment which is controlled by pre-test and post-test. The population of this research is all of VII grade in SMP Negeri 14 Bandung even-term 2013/2014, later on two classes of it were taken for the samples of this research. A class was taught using Multiple Intelligences based teaching model and the other one was taught using cooperative learning. The data of this research were gotten from the test in mathematical problem solving, scale questionnaire of the student attitudes, and observation. The results show the mathematical problem solving of the students who have learned mathematics using Multiple Intelligences based teaching model learning is higher than the student who have learned mathematics using cooperative learning, the mathematical problem solving ability of the student who have learned mathematics using cooperative learning and Multiple Intelligences based teaching model are in intermediate level, and the students showed the positive attitude in learning mathematics using Multiple Intelligences based teaching model. As for the recommendation for next author, Multiple Intelligences based teaching model can be tested on other subject and other ability.
A Case Study of an Induction Year Teacher's Problem-Solving Using the LIBRE Model Activity
Guerra, Norma S.; Flores, Belinda Bustos; Claeys, Lorena
2009-01-01
Background: A federally-funded program at the University of Texas at San Antonio adopted a holistic problem solving mentoring approach for novice teachers participating in an accelerated teacher certification program. Aims/focus of discussion: To investigate a novice teacher's problem-solving activity through self-expression of challenges and…
A heterogeneous fleet vehicle routing model for solving the LPG distribution problem: A case study
International Nuclear Information System (INIS)
Onut, S; Kamber, M R; Altay, G
2014-01-01
Vehicle Routing Problem (VRP) is an important management problem in the field of distribution and logistics. In VRPs, routes from a distribution point to geographically distributed points are designed with minimum cost and considering customer demands. All points should be visited only once and by one vehicle in one route. Total demand in one route should not exceed the capacity of the vehicle that assigned to that route. VRPs are varied due to real life constraints related to vehicle types, number of depots, transportation conditions and time periods, etc. Heterogeneous fleet vehicle routing problem is a kind of VRP that vehicles have different capacity and costs. There are two types of vehicles in our problem. In this study, it is used the real world data and obtained from a company that operates in LPG sector in Turkey. An optimization model is established for planning daily routes and assigned vehicles. The model is solved by GAMS and optimal solution is found in a reasonable time
A heterogeneous fleet vehicle routing model for solving the LPG distribution problem: A case study
Onut, S.; Kamber, M. R.; Altay, G.
2014-03-01
Vehicle Routing Problem (VRP) is an important management problem in the field of distribution and logistics. In VRPs, routes from a distribution point to geographically distributed points are designed with minimum cost and considering customer demands. All points should be visited only once and by one vehicle in one route. Total demand in one route should not exceed the capacity of the vehicle that assigned to that route. VRPs are varied due to real life constraints related to vehicle types, number of depots, transportation conditions and time periods, etc. Heterogeneous fleet vehicle routing problem is a kind of VRP that vehicles have different capacity and costs. There are two types of vehicles in our problem. In this study, it is used the real world data and obtained from a company that operates in LPG sector in Turkey. An optimization model is established for planning daily routes and assigned vehicles. The model is solved by GAMS and optimal solution is found in a reasonable time.
Solving the quasi-static field model of the pulse-line accelerator; relationship to a circuit model
International Nuclear Information System (INIS)
Friedman, Alex
2005-01-01
The Pulse-Line Ion Accelerator (PLIA) is a promising approach to high-gradient acceleration of an ion beam at high line charge density. A recent note by R. J. Briggs suggests that a 'sheath helix' model of such a system can be solved numerically in the quasi-static limit. Such a model captures the correct macroscopic behavior from first principles without the need to time-advance the full Maxwell equations on a grid. This note describes numerical methods that may be used to effect such a solution, and their connection to the circuit model that was described in an earlier note by the author. Fine detail of the fields in the vicinity of the helix wires is not obtained by this approach, but for purposes of beam dynamics simulation such detail is not generally needed
Integrated Cost and Schedule using Monte Carlo Simulation of a CPM Model - 12419
Energy Technology Data Exchange (ETDEWEB)
Hulett, David T. [Hulett and Associates, LLC (United States); Nosbisch, Michael R. [Project Time and Cost, Inc. (United States)
2012-07-01
This discussion of the recommended practice (RP) 57R-09 of AACE International defines the integrated analysis of schedule and cost risk to estimate the appropriate level of cost and schedule contingency reserve on projects. The main contribution of this RP is to include the impact of schedule risk on cost risk and hence on the need for cost contingency reserves. Additional benefits include the prioritizing of the risks to cost, some of which are risks to schedule, so that risk mitigation may be conducted in a cost-effective way, scatter diagrams of time-cost pairs for developing joint targets of time and cost, and probabilistic cash flow which shows cash flow at different levels of certainty. Integrating cost and schedule risk into one analysis based on the project schedule loaded with costed resources from the cost estimate provides both: (1) more accurate cost estimates than if the schedule risk were ignored or incorporated only partially, and (2) illustrates the importance of schedule risk to cost risk when the durations of activities using labor-type (time-dependent) resources are risky. Many activities such as detailed engineering, construction or software development are mainly conducted by people who need to be paid even if their work takes longer than scheduled. Level-of-effort resources, such as the project management team, are extreme examples of time-dependent resources, since if the project duration exceeds its planned duration the cost of these resources will increase over their budgeted amount. The integrated cost-schedule risk analysis is based on: - A high quality CPM schedule with logic tight enough so that it will provide the correct dates and critical paths during simulation automatically without manual intervention. - A contingency-free estimate of project costs that is loaded on the activities of the schedule. - Resolves inconsistencies between cost estimate and schedule that often creep into those documents as project execution proceeds
Turnip, Betty; Wahyuni, Ida; Tanjung, Yul Ifda
2016-01-01
One of the factors that can support successful learning activity is the use of learning models according to the objectives to be achieved. This study aimed to analyze the differences in problem-solving ability Physics student learning model Inquiry Training based on Just In Time Teaching [JITT] and conventional learning taught by cooperative model…
Evolutionarily stable learning schedules and cumulative culture in discrete generation models.
Aoki, Kenichi; Wakano, Joe Yuichiro; Lehmann, Laurent
2012-06-01
Individual learning (e.g., trial-and-error) and social learning (e.g., imitation) are alternative ways of acquiring and expressing the appropriate phenotype in an environment. The optimal choice between using individual learning and/or social learning may be dictated by the life-stage or age of an organism. Of special interest is a learning schedule in which social learning precedes individual learning, because such a schedule is apparently a necessary condition for cumulative culture. Assuming two obligatory learning stages per discrete generation, we obtain the evolutionarily stable learning schedules for the three situations where the environment is constant, fluctuates between generations, or fluctuates within generations. During each learning stage, we assume that an organism may target the optimal phenotype in the current environment by individual learning, and/or the mature phenotype of the previous generation by oblique social learning. In the absence of exogenous costs to learning, the evolutionarily stable learning schedules are predicted to be either pure social learning followed by pure individual learning ("bang-bang" control) or pure individual learning at both stages ("flat" control). Moreover, we find for each situation that the evolutionarily stable learning schedule is also the one that optimizes the learned phenotype at equilibrium. Copyright © 2012 Elsevier Inc. All rights reserved.
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.
Locomotive Schedule Optimization for Da-qin Heavy Haul Railway
Directory of Open Access Journals (Sweden)
Ruiye Su
2015-01-01
Full Text Available The main difference between locomotive schedule of heavy haul railways and that of regular rail transportation is the number of locomotives utilized for one train. One heavy-loaded train usually has more than one locomotive, but a regular train only has one. This paper develops an optimization model for the multilocomotive scheduling problem (MLSP through analyzing the current locomotive schedule of Da-qin Railway. The objective function of our paper is to minimize the total number of utilized locomotives. The MLSP is nondeterministic polynomial (NP hard. Therefore, we convert the multilocomotive traction problem into a single-locomotive traction problem. Then, the single-locomotive traction problem (SLTP can be converted into an assignment problem. The Hungarian algorithm is applied to solve the model and obtain the optimal locomotive schedule. We use the variance of detention time of locomotives at stations to evaluate the stability of locomotive schedule. In order to evaluate the effectiveness of the proposed optimization model, case studies for 20 kt and 30 kt heavy-loaded combined trains on Da-qin Railway are both conducted. Compared to the current schedules, the optimal schedules from the proposed models can save 62 and 47 locomotives for 20 kt and 30 kt heavy-loaded combined trains, respectively. Therefore, the effectiveness of the proposed model and its solution algorithm are both valid.
Hai An; Ling Zhou; Hui Sun
2016-01-01
Aiming to resolve the problems of a variety of uncertainty variables that coexist in the engineering structure reliability analysis, a new hybrid reliability index to evaluate structural hybrid reliability, based on the random–fuzzy–interval model, is proposed in this article. The convergent solving method is also presented. First, the truncated probability reliability model, the fuzzy random reliability model, and the non-probabilistic interval reliability model are introduced. Then, the new...
tms-sim – Timing Models Scheduling Simulation Framework – Release 2016-07
Kluge, Florian
2016-01-01
tms-sim is a framework for the simulation and evaluation of scheduling algorithms. It is being developed to support our work on real-time task scheduling based on time-utility and history-cognisant utility functions. We publish tms-sim under the conditions of the GNU GPL to make our results reproducible and in the hope that it may be useful for others. This report describes the usage of the TMS framework libraries and how they can be used to build further simulation environments. It is not in...
tms-sim - Timing Models Scheduling Simulation Framework: Release 2014-12
Kluge, Florian
2015-01-01
tms-sim is a framework for the simulation and evaluation of scheduling algorithms. It is being developed to support our work on real-time task scheduling based on time-utility and history-cognisant utility functions. We publish tms-sim under the conditions of the GNU GPL to make our results reproducible and in the hope that it may be useful for others. This report describes the usage of the TMS framework libraries and how they can be used to build further simulation environments. It is not in...
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
Directory of Open Access Journals (Sweden)
Edwin Musdi
2016-02-01
Full Text Available This research aims to develop a mathematics instructional model based realistic mathematics education (RME to promote students' problem-solving abilities. The design research used Plomp models, which consists of preliminary phase, development or proto-typing phase and assessment phase. At this study, only the first two phases conducted. The first phase, a preliminary investigation, carried out with a literature study to examine the theory-based instructional learning RME model, characteristics of learners, learning management descriptions by junior high school mathematics teacher and relevant research. The development phase is done by developing a draft model (an early prototype model that consists of the syntax, the social system, the principle of reaction, support systems, and the impact and effects of instructional support. Early prototype model contain a draft model, lesson plans, worksheets, and assessments. Tesssmer formative evaluation model used to revise the model. In this study only phase of one to one evaluation conducted. In the ppreliminary phase has produced a theory-based learning RME model, a description of the characteristics of learners in grade VIII Junior High School Padang and the description of teacher teaching in the classroom. The result showed that most students were still not be able to solve the non-routine problem. Teachers did not optimally facilitate students to develop problem-solving skills of students. It was recommended that the model can be applied in the classroom.
A Model for Solving the Maxwell Quasi Stationary Equations in a 3-Phase Electric Reduction Furnace
Directory of Open Access Journals (Sweden)
S. Ekrann
1982-10-01
Full Text Available A computer code has been developed for the approximate computation of electric and magnetic fields within an electric reduction furnace. The paper describes the numerical methods used to solve Maxwell's quasi-stationary equations, which are the governing equations for this problem. The equations are discretized by a staggered grid finite difference technique. The resulting algebraic equations are solved by iterating between computations of electric and magnetic quantities. This 'outer' iteration converges only when the skin depth is larger or of about the same magnitude as the linear dimensions of the computational domain. In solving for electric quantities with magnetic quantities being regarded as known, and vice versa, the central computational task is the solution of a Poisson equation for a scalar potential. These equations are solved by line successive overrelaxation combined with a rebalancing technique.
an online model for assessing st for assessing st stepwise solving
African Journals Online (AJOL)
User
er formative or summative assessment. Hence, in this ... chnology, educational system, students' understanding, calculus questio ent of the ... comprehension on the instructional c ..... [8] Moses, O. A. “Design of a Problem-solving approach.
Energy Technology Data Exchange (ETDEWEB)
Morales Fusco, P.; Pedrielli, G.; Zhou, C.; Hay Lee, L.; Peng Chew, E.
2016-07-01
In most large port cities, the challenge of inter-terminal transfers (ITT) prevails due to the long distance between multiple terminals. The quantity of containers requiring movement between terminals as they connect from pre-carrier to on-carrier is increasing with the formation of the mega-alliances. The paper proposes a continuous time mathematical programming model to optimize the deployment and schedule of trucks and barges to minimize the number of operating transporters, their makespan, costs and the distance travelled by the containers by choosing the right combination of transporters and container movements while fulfilling time window restrictions imposed on reception of the containers. A multi-step routing problem is developed where transporters can travel from one terminal to another and/or load or unload containers from a specific batch at each step. The model proves successful in identifying the costless schedule and means of transportation. And a sensibility analysis over the parameters used is provided. (Author)
International Nuclear Information System (INIS)
Jones, Bleddyn; Dale, Roger G.
1999-01-01
Purpose: The use of molecular biology based therapies concurrently with radical radiotherapy is likely to offer potential benefits, but there is relatively little use of classical radiobiology in the rationale for such applications. The biological mechanisms that govern the outcomes of radiotherapy need to be completely understood before rational application and optimization of such adjuvant biotherapies with radiotherapy. Methods and Materials: Existing biomathematical models of radiotherapy can be used to explore the possible impact of biotherapies that modify tumor proliferation rates and/or radiosensitivity parameters during radiotherapy. Equations that show how to incorporate biotherapies with the linear-quadratic model of radiation cell kill are presented. Also considered are changes in tumor physiology, such as improved blood flow with enhanced delivery of biotherapy to the tumor cells and accelerated clonogen repopulation during radiotherapy. Monte Carlo random sampling methods are used to simulate these effects in heterogenous tumor populations with variation in radiosensitivities, clonogen numbers, and doubling times, as well as variations in repopulation onset rates and in vascular perfusion rates with time. Results: The time onset and duration of exposure of each type of biotherapy during radical radiotherapy can influence the predicted tumor cure probabilities in subtle ways. In general, the efficacy of biotherapies that radiosensitize will depend upon the number of radiotherapy fractions that are sensitized and the change in blood flow with time during radiotherapy. Biotherapies that control repopulation will depend not only on the duration of exposure but also, where accelerated repopulation occurs, on the time at which biotherapy is initiated during radiotherapy. From the ranges of radiobiological parameters and biotherapy efficacies assumed for exploratory examples, large changes of tumor control probability (TCP) are encountered in individual
Solving inverse problems for biological models using the collage method for differential equations.
Capasso, V; Kunze, H E; La Torre, D; Vrscay, E R
2013-07-01
In the first part of this paper we show how inverse problems for differential equations can be solved using the so-called collage method. Inverse problems can be solved by minimizing the collage distance in an appropriate metric space. We then provide several numerical examples in mathematical biology. We consider applications of this approach to the following areas: population dynamics, mRNA and protein concentration, bacteria and amoeba cells interaction, tumor growth.
maisarera, yunita; diawati, chansyanah; fadiawati, noor
2012-01-01
The aim of this research is to describe the effectiveness of problem solving learning in improving communication and inference skills in colloid system material.Â Subjects in this research were students of XIIPA1 and XI IPA2 classrooms in Persada Junior High School in Bandar Lampung in academic year 2011-2012 where students of both classrooms had the same characteristics. This research used quasi experiment method and pretest-posttest control group design. Effectiveness of problem solving le...
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%.
Edwin Musdi
2016-01-01
This research aims to develop a mathematics instructional model based realistic mathematics education (RME) to promote students' problem-solving abilities. The design research used Plomp models, which consists of preliminary phase, development or proto-typing phase and assessment phase. At this study, only the first two phases conducted. The first phase, a preliminary investigation, carried out with a literature study to examine the theory-based instructional learning RME model, characterist...
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.
Lufri, L.; Fitri, R.; Yogica, R.
2018-04-01
The purpose of this study is to produce a learning model based on problem solving and meaningful learning standards by expert assessment or validation for the course of Animal Development. This research is a development research that produce the product in the form of learning model, which consist of sub product, namely: the syntax of learning model and student worksheets. All of these products are standardized through expert validation. The research data is the level of validity of all sub products obtained using questionnaire, filled by validators from various field of expertise (field of study, learning strategy, Bahasa). Data were analysed using descriptive statistics. The result of the research shows that the problem solving and meaningful learning model has been produced. Sub products declared appropriate by expert include the syntax of learning model and student worksheet.
Gauthier, Benoit; And Others
1997-01-01
Identifies the more representative problem-solving models in environmental education. Suggests the addition of a strategy for defining a problem situation using Soft Systems Methodology to environmental education activities explicitly designed for the development of critical thinking. Contains 45 references. (JRH)
Holder, Lauren N.; Scherer, Hannah H.; Herbert, Bruce E.
2017-01-01
Engaging students in problem-solving concerning environmental issues in near-surface complex Earth systems involves developing student conceptualization of the Earth as a system and applying that scientific knowledge to the problems using practices that model those used by professionals. In this article, we review geoscience education research…
Ozmen, E. Ruya; Doganay-Bilgi, Arzu
2016-01-01
The purpose of this case study was to improve the reading accuracy and reading comprehension of a 10-year-old fourth-grade female student with reading difficulties. For that purpose, the problem- solving model was implemented in four stages. These stages included problem identification, problem analysis, intervention, and evaluation. During the…
Development of Watch Schedule Using Rules Approach
Jurkevicius, Darius; Vasilecas, Olegas
The software for schedule creation and optimization solves a difficult, important and practical problem. The proposed solution is an online employee portal where administrator users can create and manage watch schedules and employee requests. Each employee can login with his/her own account and see his/her assignments, manage requests, etc. Employees set as administrators can perform the employee scheduling online, manage requests, etc. This scheduling software allows users not only to see the initial and optimized watch schedule in a simple and understandable form, but also to create special rules and criteria and input their business. The system using rules automatically will generate watch schedule.
Automated scheduling and planning from theory to practice
Ozcan, Ender; Urquhart, Neil
2013-01-01
Solving scheduling problems has long presented a challenge for computer scientists and operations researchers. The field continues to expand as researchers and practitioners examine ever more challenging problems and develop automated methods capable of solving them. This book provides 11 case studies in automated scheduling, submitted by leading researchers from across the world. Each case study examines a challenging real-world problem by analysing the problem in detail before investigating how the problem may be solved using state of the art techniques.The areas covered include aircraft scheduling, microprocessor instruction scheduling, sports fixture scheduling, exam scheduling, personnel scheduling and production scheduling. Problem solving methodologies covered include exact as well as (meta)heuristic approaches, such as local search techniques, linear programming, genetic algorithms and ant colony optimisation.The field of automated scheduling has the potential to impact many aspects of our lives...
Directory of Open Access Journals (Sweden)
Xin Zou
2018-01-01
Full Text Available The line-of-balance (LOB technique has demonstrated many advantages in scheduling repetitive projects, one of which is that it allows more than one crew to be hired by an activity concurrently. The deadline satisfaction problem in LOB scheduling (DSPLOB aims to find an LOB schedule such that the project is completed within a given deadline and the total number of crews is minimized. Previous studies required a strict application of crew work continuity, which may lead to a decline in the competitiveness of solutions. This paper introduces work interruptions into the DSPLOB and presents a biobjective optimization model that can balance the two conflicting objectives of minimizing the total number of crews and maximizing work continuity. An efficient version of the ϵ-constraint method is customized to find all feasible tradeoff solutions. Then, these solutions are further improved by an automated procedure to reduce the number of interruptions for each activity without deteriorating the performance in both the objectives. The effectiveness and practicability of the proposed model are verified using a considerable number of instances. The results show that introducing work interruptions provides more flexibility in reducing the total number of crews under the LOB framework, especially for serial projects with a tight deadline constraint.
Gain-Scheduled Model Predictive Control of Wind Turbines using Laguerre Functions
DEFF Research Database (Denmark)
Adegas, Fabiano Daher; Wisniewski, Rafal; Larsen, Lars Finn Sloth
2014-01-01
This paper presents a systematic approach to design gain-scheduled predictive controllers for wind turbines. The predictive control law is based on Laguerre functions to parameterize control signals and a parameter-dependent cost function that is analytically determined from turbine data....... These properties facilitate the design of speed controllers by placement of the closed-loop poles (when constraints are not active) and systematic adaptation towards changes in the operating point. Vibration control of undamped modes is achieved by imposing a certain degree of stability to the closed-loop system....... The approach can be utilized to the design of new controllers and to represent existing gain-scheduled controllers as predictive controllers. The numerical example and simulations illustrate the design of a speed controller augmented with active damping of the tower fore-aft displacement....
Modelling and Scheduling Autonomous Mobile Robot for a Real-World Industrial Application
DEFF Research Database (Denmark)
Dang, Vinh Quang; Nielsen, Izabela Ewa; Bøgh, Simon
2013-01-01
proposes an approach composing of: a mobile robot system design (“Little Helper”), an appropriate and comprehensive industrial application (multiple-part feeding tasks), an implementation concept for industrial environments (the bartender concept), and a real-time heuristics integrated into Mission...... from the real-time heuristics. The results also demonstrated that the proposed real-time heuristics has capability of finding the best schedule in online production mode....
Freight railway operator timetabling and engine scheduling
DEFF Research Database (Denmark)
Bach, Lukas; Gendreau, M.; Wøhlk, Sanne
2015-01-01
In this paper we consider timetable design at a European freight railway operator. The timetable is designed by choosing the time of service for customer unit train demands among a set of discrete points. These discrete points are all found within the a time-window. The objective of the model...... is to minimize cost while adhering to constraints regarding infrastructure usage, demand coverage, and engine availability. The model is solved by a column generation scheme where feasible engine schedules are designed in a label setting algorithm with time-dependent cost and service times....
Crane scheduling for a plate storage in a shipyard: Modelling the problem
DEFF Research Database (Denmark)
Hansen, Jesper; Kristensen, Torben F.H.
2003-01-01
. These blocks are again welded together in the dock to produce a ship. Two gantry cranes move the plates into, around and out of the storage when needed in production. Different principles for organizing the storage and also different approaches for solving the problem are compared. Our results indicate...
Directory of Open Access Journals (Sweden)
Guillermo Cabrera
2013-01-01
Full Text Available We solve a novel inventory-location model with a stochastic capacity constraint based on a periodic inventory control (ILM-PR policy. The ILM-PR policy implies several changes with regard to other previous models proposed in the literature, which consider continuous review as their inventory policy. One of these changes is the inclusion of the undershoot concept, which has not been considered in previous ILM models in the literature. Based on our model, we are able to design a distribution network for a two-level supply chain, addressing both warehouse location and customer assignment decisions, whilst taking into consideration several aspects of inventory planning, in particular, evaluating the impact of the inventory control review period on the network configuration and system costs. Because the model is a very hard-to solve combinatorial nonlinear optimisation problem, we implemented two heuristics to solve it, namely, Tabu Search and Particle Swarm Optimisation. These approaches were tested over small instances in which they were able to find the optimal solution in just a few seconds. Because the model is a new one, a set of medium-size instances is provided that can be useful as a benchmark in future research. The heuristics showed a good convergence rate when applied to those instances. The results confirm that decision making over the inventory control policy has effects on the distribution network design.
Thinking about Applications: Effects on Mental Models and Creative Problem-Solving
Barrett, Jamie D.; Peterson, David R.; Hester, Kimberly S.; Robledo, Issac C.; Day, Eric A.; Hougen, Dean P.; Mumford, Michael D.
2013-01-01
Many techniques have been used to train creative problem-solving skills. Although the available techniques have often proven to be effective, creative training often discounts the value of thinking about applications. In this study, 248 undergraduates were asked to develop advertising campaigns for a new high-energy soft drink. Solutions to this…
Modelling Problem-Solving Situations into Number Theory Tasks: The Route towards Generalisation
Papadopoulos, Ioannis; Iatridou, Maria
2010-01-01
This paper examines the way two 10th graders cope with a non-standard generalisation problem that involves elementary concepts of number theory (more specifically linear Diophantine equations) in the geometrical context of a rectangle's area. Emphasis is given on how the students' past experience of problem solving (expressed through interplay…
Lifshitz, Hefziba; Weiss, Itzhak; Tzuriel, David; Tzemach, Moran
2011-01-01
The main goal of the study was to map the difficulties and cognitive processes among adolescents (aged 13-21, N = 30) and adults (aged 25-66, N = 30) with mild and moderate intellectual disability (ID) when solving analogical problems. The participants were administered the "Conceptual and Perceptual Analogical Modifiability" test. A…
Hawken, Emily R; Beninger, Richard J
2014-05-01
Amphetamine enhances dopamine (DA) transmission and induces psychotic states or exacerbates psychosis in at-risk individuals. Amphetamine sensitization of the DA system has been proposed as a rodent model of schizophrenia-like symptoms. In humans, excessive nonphysiologic drinking or primary polydipsia is significantly associated with a diagnosis of schizophrenia. In rodents, nonphysiologic drinking can be induced by intermittent presentation of food in the presence of a drinking spout to a hungry animal; this phenomenon is termed, "schedule-induced polydipsia" (SIP). This study aims to determine the effects of amphetamine sensitization on SIP. We injected rats with amphetamine (1.5 mg/kg) daily for 5 days. Following 4 weeks of withdrawal, animals were food restricted and exposed to the SIP protocol (noncontingent fixed-time 1-min food schedule) for daily 2-h sessions for 24 days. Results showed that previously amphetamine-injected animals drank more in the SIP protocol and drank more than controls when the intermittent food presentation schedule was removed. These findings suggest that hyperdopaminergia associated with schizophrenia may contribute to the development of polydipsia in this population. Whether animals that develop SIP have DA dysfunction or aberrant activity of other circuits that modulate DA activity has yet to be clearly defined.
Pujiastuti, E.; Waluya, B.; Mulyono
2018-03-01
There were many ways of solving the problem offered by the experts. The author combines various ways of solving the problem as a form of novelty. Among the learning model that was expected to support the growth of problem-solving skills was SAVI. The purpose, to obtain trace results from the analysis of the problem-solving ability of students in the Dual Integral material. The research method was a qualitative approach. Its activities include tests was filled with mathematical connections, observation, interviews, FGD, and triangulation. The results were: (1) some students were still experiencing difficulties in solving the problems. (2) The application of modification of SAVI learning model effective in supporting the growth of problem-solving abilities. (3) The strength of the students related to solving the problem, there were two students in the excellent category, there were three students in right classes and one student in the medium group.
Coordinating space telescope operations in an integrated planning and scheduling architecture
Muscettola, Nicola; Smith, Stephen F.; Cesta, Amedeo; D'Aloisi, Daniela
1992-01-01
The Heuristic Scheduling Testbed System (HSTS), a software architecture for integrated planning and scheduling, is discussed. The architecture has been applied to the problem of generating observation schedules for the Hubble Space Telescope. This problem is representative of the class of problems that can be addressed: their complexity lies in the interaction of resource allocation and auxiliary task expansion. The architecture deals with this interaction by viewing planning and scheduling as two complementary aspects of the more general process of constructing behaviors of a dynamical system. The principal components of the software architecture are described, indicating how to model the structure and dynamics of a system, how to represent schedules at multiple levels of abstraction in the temporal database, and how the problem solving machinery operates. A scheduler for the detailed management of Hubble Space Telescope operations that has been developed within HSTS is described. Experimental performance results are given that indicate the utility and practicality of the approach.
Interacting dark energy models as an approach for solving Cosmic Coincidence Problem
Shojaei, Hamed
Understanding the dark side of the Universe is one of the main tasks of physicists. As there is no thorough understanding of nature of the dark energy, this area is full of new ideas and there may be several discoveries, theoretical or experimental, in the near future. We know that dark energy, though not detected directly, exists and it is not just an exotic idea. The presence of dark energy is required by the observation of the acceleration of the universe. There are several questions regarding dark energy. What is the nature of dark energy? How does it interact with matter, baryonic or dark? Why is the density of dark energy so tiny, i.e. why rhoΛ ≈ 10--120 M4Pl ? And finally why does its density have the same order of magnitude as the density of matter does at the present time? The last question is one form of what is known as the "Cosmic Coincidence Problem" and in this work, I have been investigating one way to resolve this issue. Observations of Type Ia supernovae indicate that we are in an accelerating universe. A matter-dominated universe cannot be accelerating. A good fit is obtained if we assume that energy density parameters are O Λ = 0.7 and Om = 0.3. Here O Λ is related to dark energy, or cosmological constant in ΛCDM model. At the same time data from Wilkinson Microwave Anisotropy Probe (WMAP) satellite and supernova surveys have placed a constraint on w, the equation of state for dark energy, which is actually the ratio of pressure and energy density. Any good theory needs to explain this coincidence problem and yields a value for w between -1.1 and -0.9. I have employed an interesting approach to solve this problem by assuming that there exists an interaction between dark energy and matter in the context of holographic dark energy. This interaction converts dark energy to matter or vice versa without violating the local conservation of energy in the universe. Holographic dark energy by itself indicates that the value of dark energy is related
Joint optimization of production scheduling and machine group preventive maintenance
International Nuclear Information System (INIS)
Xiao, Lei; Song, Sanling; Chen, Xiaohui; Coit, David W.
2016-01-01
Joint optimization models were developed combining group preventive maintenance of a series system and production scheduling. In this paper, we propose a joint optimization model to minimize the total cost including production cost, preventive maintenance cost, minimal repair cost for unexpected failures and tardiness cost. The total cost depends on both the production process and the machine maintenance plan associated with reliability. For the problems addressed in this research, any machine unavailability leads to system downtime. Therefore, it is important to optimize the preventive maintenance of machines because their performance impacts the collective production processing associated with all machines. Too lengthy preventive maintenance intervals may be associated with low scheduled machine maintenance cost, but may incur expensive costs for unplanned failure due to low machine reliability. Alternatively, too frequent preventive maintenance activities may achieve the desired high reliability machines, but unacceptably high scheduled maintenance cost. Additionally, product scheduling plans affect tardiness and maintenance cost. Two results are obtained when solving the problem; the optimal group preventive maintenance interval for machines, and the assignment of each job, including the corresponding start time and completion time. To solve this non-deterministic polynomial-time problem, random keys genetic algorithms are used, and a numerical example is solved to illustrate the proposed model. - Highlights: • Group preventive maintenance (PM) planning and production scheduling are jointed. • Maintenance interval and assignment of jobs are decided by minimizing total cost. • Relationships among system age, PM, job processing time are quantified. • Random keys genetic algorithms (GA) are used to solve the NP-hard problem. • Random keys GA and Particle Swarm Optimization (PSO) are compared.
Hannan, M A; Akhtar, Mahmuda; Begum, R A; Basri, H; Hussain, A; Scavino, Edgar
2018-01-01
Waste collection widely depends on the route optimization problem that involves a large amount of expenditure in terms of capital, labor, and variable operational costs. Thus, the more waste collection route is optimized, the more reduction in different costs and environmental effect will be. This study proposes a modified particle swarm optimization (PSO) algorithm in a capacitated vehicle-routing problem (CVRP) model to determine the best waste collection and route optimization solutions. In this study, threshold waste level (TWL) and scheduling concepts are applied in the PSO-based CVRP model under different datasets. The obtained results from different datasets show that the proposed algorithmic CVRP model provides the best waste collection and route optimization in terms of travel distance, total waste, waste collection efficiency, and tightness at 70-75% of TWL. The obtained results for 1 week scheduling show that 70% of TWL performs better than all node consideration in terms of collected waste, distance, tightness, efficiency, fuel consumption, and cost. The proposed optimized model can serve as a valuable tool for waste collection and route optimization toward reducing socioeconomic and environmental impacts. Copyright © 2017 Elsevier Ltd. All rights reserved.
Directory of Open Access Journals (Sweden)
Indrati Rahayu
2014-06-01
Full Text Available AbstrakTujuan dari penelitian ini adalah untuk memperoleh hasil perangkat pembelajaran matematika model DLPS dengan pendekatan PMRI yang valid, praktis dan efektif. Perangkat pembelajaran yang dikembangkan meliputi Silabus, RPP, Buku Peserta didik, LKPD dan test kemampuan pemecahan masalah. Subyek uji coba dalam penelitian ini adalah peserta didik kelas X semester genap SMAN 4 Semarang. Variabel penelitian meliputi keaktivan (X1 dan sikap peserta didik (X2 dan kemampuan pemecahan masalah (Y. Pengembangan perangkat pembelajaran mengacu pada model Plomp, yaitu: (1 investigasi awal (prelimenary investigation, (2 perancangan (design; (3 realisasi/ kontruksi (realization/construction, (4 pengujian, evaluasi dan revisi (test, evaluation and revision, dan (5 implementasi (implementation. Hasil Penelitian menunjukkan: (1 perangkat pembelajaran yang dikembangkan telah dinyatakan valid dan (2 uji coba perangkat menghasilkan (a secara signifikan prestasi belajar peserta didik melebihi KKM = 70 dan lebih dari 80% peserta didik mencapai KKM yaitu 93,75%. Simpulan dari penelitian ini adalah model DLPS dengan Pendekatan PMRI bermuatan karakter untuk meningkatkan kemampuan pemecahan masalah materi trigonometri kelas X merupakan model pembelajaran yang valid dan efektif, dan praktis.AbstractThe purpose of this study is to obtain the results of mathematical learning DLPS models with PMRI approachment charged character that is valid, pratical and effective. The learning instruments which are developed include syllabus, lesson plan, student book, student work sheets, and problem solving abilities test. The subject of this study are the students of Senior High School 4 Semarang. The variable of this research include the activity as (X1 and the student’s attitudes as (X2. while the dependent variable is the problem solving abilities as (Y. The learning development refers to a model of Plomp i.e : (1 prelimenary investigation, (2 design, (3 realization
Elements of a cognitive model of physics problem solving: Epistemic games
Directory of Open Access Journals (Sweden)
Jonathan Tuminaro
2007-07-01
Full Text Available Although much is known about the differences between expert and novice problem solvers, knowledge of those differences typically does not provide enough detail to help instructors understand why some students seem to learn physics while solving problems and others do not. A critical issue is how students access the knowledge they have in the context of solving a particular problem. In this paper, we discuss our observations of students solving physics problems in authentic situations in an algebra-based physics class at the University of Maryland. We find that when these students are working together and interacting effectively, they often use a limited set of locally coherent resources for blocks of time of a few minutes or more. This coherence appears to provide the student with guidance as to what knowledge and procedures to access and what to ignore. Often, this leads to the students failing to apply relevant knowledge they later show they possess. In this paper, we outline a theoretical phenomenology for describing these local coherences and identify six organizational structures that we refer to as epistemic games. The hypothesis that students tend to function within the narrow confines of a fairly limited set of games provides a good description of our observations. We demonstrate how students use these games in two case studies and discuss the implications for instruction.
Research on the ITOC based scheduling system for ship piping production
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.
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Burhanudin Milama
2017-11-01
Full Text Available The aim of this study is determine the effect of search, solve, create, and share (SSCS learning model on critical thinking skills of hydrocarbons and petroleum material. The method used in this study was quasi experimental design, with research design nonequivalent control group design. The sample was taken by purposive sampling and divided into two groups consist of control group and experimental group. The data gathering techniques in this study was through 8 items of essay test instrument which is analyzed by using t-test. The results of t-test data showed that tcount ttable or 16.36 1.980 at significance level 5%, value tcount lies in the region reject H0 and accept Ha. The result shows that there are significant search, solve, create, and share (SSCS learning model on student’s critical thinking skills.
Zirconia, A.; Supriyanti, F. M. T.; Supriatna, A.
2018-04-01
This study aims to determine generic science skills enhancement of students through implementation of IDEAL problem-solving model on genetic information course. Method of this research was mixed method, with pretest-posttest nonequivalent control group design. Subjects of this study were chemistry students enrolled in biochemistry course, consisted of 22 students in the experimental class and 19 students in control class. The instrument in this study was essayed involves 6 indicators generic science skills such as indirect observation, causality thinking, logical frame, self-consistent thinking, symbolic language, and developing concept. The results showed that genetic information course using IDEAL problem-solving model have been enhancing generic science skills in low category with of 20,93%. Based on result for each indicator, showed that there are indicators of generic science skills classified in the high category.
Bradley, D. B.; Irwin, J. D.
1974-01-01
A computer simulation model for a multiprocessor computer is developed that is useful for studying the problem of matching multiprocessor's memory space, memory bandwidth and numbers and speeds of processors with aggregate job set characteristics. The model assumes an input work load of a set of recurrent jobs. The model includes a feedback scheduler/allocator which attempts to improve system performance through higher memory bandwidth utilization by matching individual job requirements for space and bandwidth with space availability and estimates of bandwidth availability at the times of memory allocation. The simulation model includes provisions for specifying precedence relations among the jobs in a job set, and provisions for specifying precedence execution of TMR (Triple Modular Redundant and SIMPLEX (non redundant) jobs.
Periodic Heterogeneous Vehicle Routing Problem With Driver Scheduling
Mardiana Panggabean, Ellis; Mawengkang, Herman; Azis, Zainal; Filia Sari, Rina
2018-01-01
The paper develops a model for the optimal management of logistic delivery of a given commodity. The company has different type of vehicles with different capacity to deliver the commodity for customers. The problem is then called Periodic Heterogeneous Vehicle Routing Problem (PHVRP). The goal is to schedule the deliveries according to feasible combinations of delivery days and to determine the scheduling of fleet and driver and routing policies of the vehicles. The objective is to minimize the sum of the costs of all routes over the planning horizon. We propose a combined approach of heuristic algorithm and exact method to solve the problem.
The Simultaneous Vehicle Scheduling and Passenger Service Problem
DEFF Research Database (Denmark)
Petersen, Hanne Løhmann; Larsen, Allan; Madsen, Oli B.G.
2013-01-01
, by modifying the timetable. The planning approach is referred to as the simultaneous vehicle scheduling and passenger service problem (SVSPSP). The SVSPSP is modelled as an integer programming problem and solved using a large neighborhood search metaheuristic. The proposed framework is tested on data inspired......Passengers using public transport systems often experience waiting times when transferring between two scheduled services. In this paper we propose a planning approach that seeks to obtain a favourable trade-off between the two contrasting objectives, passenger service and operating cost...
Liu, Shichao; Liu, Xiaoping P; El Saddik, Abdulmotaleb
2014-03-01
In this paper, we investigate the modeling and distributed control problems for the load frequency control (LFC) in a smart grid. In contrast with existing works, we consider more practical and real scenarios, where the communication topology of the smart grid changes because of either link failures or packet losses. These topology changes are modeled as a time-varying communication topology matrix. By using this matrix, a new closed-loop power system model is proposed to integrate the communication topology changes into the dynamics of a physical power system. The globally asymptotical stability of this closed-loop power system is analyzed. A distributed gain scheduling LFC strategy is proposed to compensate for the potential degradation of dynamic performance (mean square errors of state vectors) of the power system under communication topology changes. In comparison to conventional centralized control approaches, the proposed method can improve the robustness of the smart grid to the variation of the communication network as well as to reduce computation load. Simulation results show that the proposed distributed gain scheduling approach is capable to improve the robustness of the smart grid to communication topology changes. © 2013 ISA. Published by ISA. All rights reserved.
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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.
Scheduling theory, algorithms, and systems
Pinedo, Michael L
2016-01-01
This new edition of the well-established text Scheduling: Theory, Algorithms, and Systems provides an up-to-date coverage of important theoretical models in the scheduling literature as well as important scheduling problems that appear in the real world. The accompanying website includes supplementary material in the form of slide-shows from industry as well as movies that show actual implementations of scheduling systems. The main structure of the book, as per previous editions, consists of three parts. The first part focuses on deterministic scheduling and the related combinatorial problems. The second part covers probabilistic scheduling models; in this part it is assumed that processing times and other problem data are random and not known in advance. The third part deals with scheduling in practice; it covers heuristics that are popular with practitioners and discusses system design and implementation issues. All three parts of this new edition have been revamped, streamlined, and extended. The reference...
International Nuclear Information System (INIS)
Aghajani, G.R.; Shayanfar, H.A.; Shayeghi, H.
2015-01-01
Highlights: • Using DRPs to cover the uncertainties resulted from power generation by WT and PV. • Proposing the use of price-offer packages and amount of DR for implement DRPs. • Considering a multi-objective scheduling model and use of MOPSO algorithm. - Abstract: In this paper, a multi-objective energy management system is proposed in order to optimize micro-grid (MG) performance in a short-term in the presence of Renewable Energy Sources (RESs) for wind and solar energy generation with a randomized natural behavior. Considering the existence of different types of customers including residential, commercial, and industrial consumers can participate in demand response programs. As with declare their interruptible/curtailable demand rate or select from among different proposed prices so as to assist the central micro-grid control in terms of optimizing micro-grid operation and covering energy generation uncertainty from the renewable sources. In this paper, to implement Demand Response (DR) schedules, incentive-based payment in the form of offered packages of price and DR quantity collected by Demand Response Providers (DRPs) is used. In the typical micro-grid, different technologies including Wind Turbine (WT), PhotoVoltaic (PV) cell, Micro-Turbine (MT), Full Cell (FC), battery hybrid power source and responsive loads are used. The simulation results are considered in six different cases in order to optimize operation cost and emission with/without DR. Considering the complexity and non-linearity of the proposed problem, Multi-Objective Particle Swarm Optimization (MOPSO) is utilized. Also, fuzzy-based mechanism and non-linear sorting system are applied to determine the best compromise considering the set of solutions from Pareto-front space. The numerical results represented the effect of the proposed Demand Side Management (DSM) scheduling model on reducing the effect of uncertainty obtained from generation power and predicted by WT and PV in a MG.
Grant, Kathleen A; Leng, Xiaoyan; Green, Heather L; Szeliga, Kendall T; Rogers, Laura S M; Gonzales, Steven W
2008-10-01
We have developed an animal model of alcohol self-administration that initially employs schedule-induced polydipsia (SIP) to establish reliable ethanol consumption under open access (22 h/d) conditions with food and water concurrently available. SIP is an adjunctive behavior that is generated by constraining access to an important commodity (e.g., flavored food). The induction schedule and ethanol polydipsia generated under these conditions affords the opportunity to investigate the development of drinking typologies that lead to chronic, excessive alcohol consumption. Adult male cynomolgus monkeys (Macaca fascicularis) were induced to drink water and 4% (w/v in water) ethanol by a Fixed-Time 300 seconds (FT-300 seconds) schedule of banana-flavored pellet delivery. The FT-300 seconds schedule was in effect for 120 consecutive sessions, with daily induction doses increasing from 0.0 to 0.5 g/kg to 1.0 g/kg to 1.5 g/kg every 30 days. Following induction, the monkeys were allowed concurrent access to 4% (w/v) ethanol and water for 22 h/day for 12 months. Drinking typographies during the induction of drinking 1.5 g/kg ethanol emerged that were highly predictive of the daily ethanol intake over the next 12 months. Specifically, the frequency in which monkeys ingested 1.5 g/kg ethanol without a 5-minute lapse in drinking (defined as a bout of drinking) during induction strongly predicted (correlation 0.91) subsequent ethanol intake over the next 12 months of open access to ethanol. Blood ethanol during induction were highly correlated with intake and with drinking typography and ranged from 100 to 160 mg% when the monkeys drank their 1.5 g/kg dose in a single bout. Forty percent of the population became heavy drinkers (mean daily intakes >3.0 g/kg for 12 months) characterized by frequent "spree" drinking (intakes >4.0 g/kg/d). This model of ethanol self-administration identifies early alcohol drinking typographies (gulping the equivalent of 6 drinks) that evolve into
A Goal Programming Model for Selection and Scheduling of Advertisements on Online News Media
DEFF Research Database (Denmark)
Manik, Prerna; Gupta, Anshu; Jha, P. C.
2016-01-01
Digital revolution has resulted in a paradigm shift in the field of marketing with online advertising becoming increasingly popular as it offers the reach, range, scale and interactivity to organizations to influence their target customers. Moreover, web advertisement is the primary revenue stream...... for several websites that provide free services to internet users. The website management team needs to do a lot of planning and optimally schedule various advertisements (ads) to maximize revenue, taking care of advertisers' needs under system constraints. In this paper, we have considered the case of news...... websites that provide news to its viewers for free with ads as the primary source of their revenue. The considered news website consists of many webpages with different banners for advertisement. Each banner consists of different number of partitions and cost per partition varies for different rectangular...
A non-permutation flowshop scheduling problem with lot streaming: A Mathematical model
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Daniel Rossit
2016-06-01
Full Text Available In this paper we investigate the use of lot streaming in non-permutation flowshop scheduling problems. The objective is to minimize the makespan subject to the standard flowshop constraints, but where it is now permitted to reorder jobs between machines. In addition, the jobs can be divided into manageable sublots, a strategy known as lot streaming. Computational experiments show that lot streaming reduces the makespan up to 43% for a wide range of instances when compared to the case in which no job splitting is applied. The benefits grow as the number of stages in the production process increases but reach a limit. Beyond a certain point, the division of jobs into additional sublots does not improve the solution.
Cost-efficient scheduling of FAST observations
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.
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
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
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.
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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.
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S. N. Plotnikov
2017-01-01
Full Text Available The model of passage of vessels through a section of the waterway is considered, which independently determines the order of passage of vessels with limited capacity of sections of the track. Such a model will consist of a number of standard algorithmic networks. When composing the schedule in the model, the following preference rules were used: first-come-first-served (that is, if the ship occupied the workplace, this decision is not canceled; The rule of the shortest operation; For the swamps the priority of vessels going downstream (the direction of flow from the source to the drain. An algorithmic network that implements the search for an acceptable schedule must implement the following for conflicting operations: the operation that has started is not interrupted; If several operations simultaneously claim for one workplace (port, reach and their number is greater than its throughput, then the conflict resolution is carried out in accordance with predefined preference rules or based on the user's decision; If the operation is waiting for the release of the workplace, it does not occupy the resource; The resource is returned immediately after the operation is completed. The considered design of algorithmic networks allows to resolve the conflict, with a simultaneous resource request, to take the resource once, remember that it was received and return it after the end of the operation, then the resource receives a contra-controlling operation for execution. However, the use of this design introduces redundancy into the model, even if it is used only for conflicting operations. The model is presented in the language of algorithmic networks and is implemented in the system of modeling automation KOGNITRON.
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Hai An
2016-08-01
Full Text Available Aiming to resolve the problems of a variety of uncertainty variables that coexist in the engineering structure reliability analysis, a new hybrid reliability index to evaluate structural hybrid reliability, based on the random–fuzzy–interval model, is proposed in this article. The convergent solving method is also presented. First, the truncated probability reliability model, the fuzzy random reliability model, and the non-probabilistic interval reliability model are introduced. Then, the new hybrid reliability index definition is presented based on the random–fuzzy–interval model. Furthermore, the calculation flowchart of the hybrid reliability index is presented and it is solved using the modified limit-step length iterative algorithm, which ensures convergence. And the validity of convergent algorithm for the hybrid reliability model is verified through the calculation examples in literature. In the end, a numerical example is demonstrated to show that the hybrid reliability index is applicable for the wear reliability assessment of mechanisms, where truncated random variables, fuzzy random variables, and interval variables coexist. The demonstration also shows the good convergence of the iterative algorithm proposed in this article.
A Distributed Particle Swarm Optimization Zlgorithmfor Flexible Job-hop Scheduling Problem
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LIU Sheng--hui
2017-06-01
Full Text Available According to the characteristics of the Flexible job shop scheduling problem the minimum makespan as measures we proposed a distributed particle swarm optimization algorithm aiming to solve flexible job shop scheduling problem. The algorithm adopts the method of distributed ideas to solve problems and we are established for two multi agent particle swarm optimization model in this algorithm it can solve the traditional particle swarm optimization algorithm when making decisions in real time according to the emergencies. Finally some benthmark problems were experimented and the results are compared with the traditional algorithm. Experimental results proved that the developed distributed PSO is enough effective and efficient to solve the FJSP and it also verified the reasonableness of the multi}gent particle swarm optimization model.
Practical quantum appointment scheduling
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.
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Mehdi Alinaghian
2014-08-01
Full Text Available In the field of health losses resulting from failure to establish the facilities in a suitable location and the required number, beyond the cost and quality of service will result in an increase in mortality and the spread of diseases. So the facility location models have special importance in this area. In this paper, a successively inclusive hierarchical model for location of health centers in term of the transfer of patients from a lower level to a higher level of health centers has been developed. Since determination the exact number of demand for health care in the future is difficult and in order to make the model close to the real conditions of demand uncertainty, a fuzzy programming model based on credibility theory is considered. To evaluate the proposed model, several numerical examples are solved in small size. In order to solve large scale problems, a meta-heuristic algorithm based on harmony search algorithm was developed in conjunction with the GAMS software which indicants the performance of the proposed algorithm.
Saleem, M. Rehan; Ali, Ishtiaq; Qamar, Shamsul
2018-03-01
In this article, a reduced five-equation two-phase flow model is numerically investigated. The formulation of the model is based on the conservation and energy exchange laws. The model is non-conservative and the governing equations contain two equations for the mass conservation, one for the over all momentum and one for the total energy. The fifth equation is the energy equation for one of the two phases that includes a source term on the right hand side for incorporating energy exchange between the two fluids in the form of mechanical and thermodynamical works. A Runge-Kutta discontinuous Galerkin finite element method is applied to solve the model equations. The main attractive features of the proposed method include its formal higher order accuracy, its nonlinear stability, its ability to handle complicated geometries, and its ability to capture sharp discontinuities or strong gradients in the solutions without producing spurious oscillations. The proposed method is robust and well suited for large-scale time-dependent computational problems. Several case studies of two-phase flows are presented. For validation and comparison of the results, the same model equations are also solved by using a staggered central scheme. It was found that discontinuous Galerkin scheme produces better results as compared to the staggered central scheme.
Davis, Jeffrey R.; Richard, Eliabeth E.; Fogarty, Jennifer A.; Rando, Cynthia M.
2011-01-01
This slide presentation reviews the Space Life Sciences Directorate (SLSD) new business model for problem solving, with emphasis on open collaboration and innovation. The topics that are discussed are: an overview of the work of the Space Life Sciences Directorate and the strategic initiatives that arrived at the new business model. A new business model was required to infuse open collaboration/innovation tools into existing models for research, development and operations (research announcements, procurements, SBIR/STTR etc). This new model involves use of several open innovation partnerships: InnoCentive, Yet2.com, TopCoder and NASA@work. There is also a new organizational structure developed to facilitate the joint collaboration with other NASA centers, international partners, other U.S. Governmental organizations, Academia, Corporate, and Non-Profit organizations: the NASA Human Health and Performance Center (NHHPC).
Selection and scheduling of jobs with time-dependent duration
DM Seegmuller; SE Visagie; HC de Kock; WJ Pienaar
2007-01-01
In this paper two mathematical programming models, both with multiple objective functions, are proposed to solve four related categories of job scheduling problems. All four of these categories have the property that the duration of the jobs is dependent on the time of implementation and in some cases the preceding job. Furthermore, some jobs (restricted to subsets of the total pool of jobs) can, to different extents, run in parallel. In addition, not all the jobs need necessarily be implemen...
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Huan-huan Li
2015-01-01
Full Text Available Wind power has the characteristics of randomness and intermittence, which influences power system safety and stable operation. To alleviate the effect of wind power grid connection and improve power system’s wind power consumptive capability, this paper took emission trading and energy storage system into consideration and built an optimization model for thermal-wind power system and energy storage systems collaborative scheduling. A simulation based on 10 thermal units and wind farms with 2800 MW installed capacity verified the correctness of the models put forward by this paper. According to the simulation results, the introduction of carbon emission trading can improve wind power consumptive capability and cut down the average coal consumption per unit of power. The introduction of energy storage system can smooth wind power output curve and suppress power fluctuations. The optimization effects achieve the best when both of carbon emission trading and energy storage system work at the same time.
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Ricardo Ferrari Pacheco
1999-04-01
Full Text Available Este artigo propõe uma classificação hierarquizada dos modelos utilizados na solução do problema de programação da produção intermitente do tipo job shop, incluindo tanto os que fornecem solução ótima, quanto os modelos heurísticos mais recentes baseados em métodos de busca estendida. Por meio dessa classificação obteve-se um painel amplo dos modelos existentes, evidenciando as diferentes abordagens do problema e suas soluções, com o objetivo de proporcionar uma orientação preliminar na escolha do modelo de job shop scheduling mais adequado.This paper proposes a hierarchical model classification used in the job shop scheduling problem, including those that provide an optimal solution and the more recent ones based on heuristics, called extended search methods. A panel with the existing models is obtained by this classification, and solutions and approach differences are highlighted with the aim of a preliminary orientation on the choice of a more adequate job shop scheduling model.
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George Cristian Gruia
2013-05-01
Full Text Available In the aviation industry, propeller motor engines have a lifecycle of several thousand hours of flight and the maintenance is an important part of their lifecycle. The present article considers a multi-resource, priority-based case scheduling problem, which is applied in a Romanian manufacturing company, that repairs and maintains helicopter and airplane engines at a certain quality level imposed by the aviation standards. Given a reduced budget constraint, the management’s goal is to maximize the utilization of their resources (financial, material, space, workers, by maintaining a prior known priority rule. An Off-Line Dual Maximum Resource Bin Packing model, based on a Mixed Integer Programming model is thus presented. The obtained results show an increase with approx. 25% of the Just in Time shipping of the engines to the customers and approx. 12,5% increase in the utilization of the working area.
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GEORGE CRISTIAN GRUIA
2013-05-01
Full Text Available In the aviation industry, propeller motor engines have a lifecycle of several thousand hours of flight and the maintenance is an important part of their lifecycle. The present article considers a multi-resource, priority-based case scheduling problem, which is applied in a Romanian manufacturing company, that repairs and maintains helicopter and airplane engines at a certain quality level imposed by the aviation standards. Given a reduced budget constraint, the management’s goal is to maximize the utilization of their resources (financial, material, space, workers, by maintaining a prior known priority rule. An Off-Line Dual Maximum Resource Bin Packing model, based on a Mixed Integer Programing model is thus presented. The obtained results show an increase with approx. 25% of the Just in Time shipping of the engines to the customers and approx. 12,5% increase in the utilization of the working area.
Directory of Open Access Journals (Sweden)
Chih-Kun Ke
2012-01-01
Full Text Available In business enterprises, especially the manufacturing industry, various problem situations may occur during the production process. A situation denotes an evaluation point to determine the status of a production process. A problem may occur if there is a discrepancy between the actual situation and the desired one. Thus, a problem-solving process is often initiated to achieve the desired situation. In the process, how to determine an action need to be taken to resolve the situation becomes an important issue. Therefore, this work uses a selection approach for optimized problem-solving process to assist workers in taking a reasonable action. A grey relational utility model and a multicriteria decision analysis are used to determine the optimal selection order of candidate actions. The selection order is presented to the worker as an adaptive recommended solution. The worker chooses a reasonable problem-solving action based on the selection order. This work uses a high-tech company’s knowledge base log as the analysis data. Experimental results demonstrate that the proposed selection approach is effective.
Donoue, George; Hoffman, Karla; Sherry, Lance; Ferguson, John; Kara, Abdul Qadar
2010-01-01
The air transportation system is a significant driver of the U.S. economy, providing safe, affordable, and rapid transportation. During the past three decades airspace and airport capacity has not grown in step with demand for air transportation; the failure to increase capacity at the same rate as the growth in demand results in unreliable service and systemic delay. This report describes the results of an analysis of airline strategic decision-making that affects geographic access, economic access, and airline finances, extending the analysis of these factors using historic data (from Part 1 of the report). The Airline Schedule Optimization Model (ASOM) was used to evaluate how exogenous factors (passenger demand, airline operating costs, and airport capacity limits) affect geographic access (markets-served, scheduled flights, aircraft size), economic access (airfares), airline finances (profit), and air transportation efficiency (aircraft size). This analysis captures the impact of the implementation of airport capacity limits, as well as the effect of increased hedged fuel prices, which serve as a proxy for increased costs per flight that might occur if auctions or congestion pricing are imposed; also incorporated are demand elasticity curves based on historical data that provide information about how passenger demand is affected by airfare changes.
A dynamic approach to vehicle scheduling
D. Huisman (Dennis); R. Freling (Richard); A.P.M. Wagelmans (Albert)
2001-01-01
textabstractThis paper presents a dynamic approach to the vehicle scheduling problem. We discuss the potential benefit of our approach compared to the traditional one, where the vehicle scheduling problem is solved only once for a whole period and the travel times are assumed to be fixed. In our
Flow shop scheduling with heterogeneous workers
Benavides, Alexander J.; Ritt, Marcus; Miralles Insa, Cristóbal Javier
2014-01-01
We propose an extension to the flow shop scheduling problem named Heterogeneous Flow Shop Scheduling Problem (Het-FSSP), where two simultaneous issues have to be resolved: finding the best worker assignment to the workstations, and solving the corresponding scheduling problem. This problem is motivated by Sheltered Work centers for Disabled, whose main objective is the labor integration of persons with disabilities, an important aim not only for these centers but for any company d...
International Nuclear Information System (INIS)
Ballesteros, Guillermo; Ringwald, Andreas; Tamarit, Carlos
2016-10-01
We present a minimal extension of the Standard Model (SM) providing a consistent picture of particle physics from the electroweak scale to the Planck scale and of cosmology from inflation until today. Three right-handed neutrinos N_i, a new color triplet Q and a complex SM-singlet scalar σ, whose vacuum expectation value υ_σ∝10"1"1 GeV breaks lepton number and a Peccei-Quinn symmetry simultaneously, are added to the SM. At low energies, the model reduces to the SM, augmented by seesaw generated neutrino masses and mixing, plus the axion. The latter solves the strong CP problem and accounts for the cold dark matter in the Universe. The inflaton is comprised by a mixture of σ and the SM Higgs and reheating of the Universe after inflation proceeds via the Higgs portal. Baryogenesis occurs via thermal leptogenesis. Thus, five fundamental problems of particle physics and cosmology are solved at one stroke in this unified Standard Model-Axion-Seesaw-Higgs portal inflation (SMASH) model. It can be probed decisively by upcoming cosmic microwave background and axion dark matter experiments.
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Wang Wei
2016-01-01
Full Text Available When searching for the optimum condenser cooling water flow in a thermal power plant with natural draft cooling towers, it is essential to evaluate the outlet water temperature of cooling towers when the cooling water flow and inlet water temperature change. However, the air outlet temperature and tower draft or inlet air velocity are strongly coupled for natural draft cooling towers. Traditional methods, such as trial and error method, graphic method and iterative methods are not simple and efficient enough to be used for plant practice. In this paper, we combine Merkel equation with draft equation, and develop the coupled description for performance evaluation of natural draft cooling towers. This model contains two inputs: the cooling water flow, the inlet cooling water temperature and two outputs: the outlet water temperature, the inlet air velocity, equivalent to tower draft. In this model, we furthermore put forward a soft-sensing algorithm to calculate the total drag coefficient instead of empirical correlations. Finally, we design an iterative approach to solve this coupling model, and illustrate three cases to prove that the coupling model and solving approach proposed in our paper are effective for cooling tower performance evaluation.
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Salvador Lucas
2015-12-01
Full Text Available Recent developments in termination analysis for declarative programs emphasize the use of appropriate models for the logical theory representing the program at stake as a generic approach to prove termination of declarative programs. In this setting, Order-Sorted First-Order Logic provides a powerful framework to represent declarative programs. It also provides a target logic to obtain models for other logics via transformations. We investigate the automatic generation of numerical models for order-sorted first-order logics and its use in program analysis, in particular in termination analysis of declarative programs. We use convex domains to give domains to the different sorts of an order-sorted signature; we interpret the ranked symbols of sorted signatures by means of appropriately adapted convex matrix interpretations. Such numerical interpretations permit the use of existing algorithms and tools from linear algebra and arithmetic constraint solving to synthesize the models.
Glass, Christopher E.
1990-08-01
The computer program EASI, an acronym for Equilibrium Air Shock Interference, was developed to calculate the inviscid flowfield, the maximum surface pressure, and the maximum heat flux produced by six shock wave interference patterns on a 2-D, cylindrical configuration. Thermodynamic properties of the inviscid flowfield are determined using either an 11-specie, 7-reaction equilibrium chemically reacting air model or a calorically perfect air model. The inviscid flowfield is solved using the integral form of the conservation equations. Surface heating calculations at the impingement point for the equilibrium chemically reacting air model use variable transport properties and specific heat. However, for the calorically perfect air model, heating rate calculations use a constant Prandtl number. Sample calculations of the six shock wave interference patterns, a listing of the computer program, and flowcharts of the programming logic are included.
Machine learning in updating predictive models of planning and scheduling transportation projects
1997-01-01
A method combining machine learning and regression analysis to automatically and intelligently update predictive models used in the Kansas Department of Transportations (KDOTs) internal management system is presented. The predictive models used...
Scheduling the scheduling task : a time management perspective on scheduling
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
solveME: fast and reliable solution of nonlinear ME models
DEFF Research Database (Denmark)
Yang, Laurence; Ma, Ding; Ebrahim, Ali
2016-01-01
Background: Genome-scale models of metabolism and macromolecular expression (ME) significantly expand the scope and predictive capabilities of constraint-based modeling. ME models present considerable computational challenges: they are much (>30 times) larger than corresponding metabolic reconstr......Background: Genome-scale models of metabolism and macromolecular expression (ME) significantly expand the scope and predictive capabilities of constraint-based modeling. ME models present considerable computational challenges: they are much (>30 times) larger than corresponding metabolic...... reconstructions (M models), are multiscale, and growth maximization is a nonlinear programming (NLP) problem, mainly due to macromolecule dilution constraints. Results: Here, we address these computational challenges. We develop a fast and numerically reliable solution method for growth maximization in ME models...
Multi-objective group scheduling optimization integrated with preventive maintenance
Liao, Wenzhu; Zhang, Xiufang; Jiang, Min
2017-11-01
This article proposes a single-machine-based integration model to meet the requirements of production scheduling and preventive maintenance in group production. To describe the production for identical/similar and different jobs, this integrated model considers the learning and forgetting effects. Based on machine degradation, the deterioration effect is also considered. Moreover, perfect maintenance and minimal repair are adopted in this integrated model. The multi-objective of minimizing total completion time and maintenance cost is taken to meet the dual requirements of delivery date and cost. Finally, a genetic algorithm is developed to solve this optimization model, and the computation results demonstrate that this integrated model is effective and reliable.
Estimating exponential scheduling preferences
DEFF Research Database (Denmark)
Hjorth, Katrine; Börjesson, Maria; Engelson, Leonid
2015-01-01
of car drivers' route and mode choice under uncertain travel times. Our analysis exposes some important methodological issues related to complex non-linear scheduling models: One issue is identifying the point in time where the marginal utility of being at the destination becomes larger than the marginal......Different assumptions about travelers' scheduling preferences yield different measures of the cost of travel time variability. Only few forms of scheduling preferences provide non-trivial measures which are additive over links in transport networks where link travel times are arbitrarily...... utility of being at the origin. Another issue is that models with the exponential marginal utility formulation suffer from empirical identification problems. Though our results are not decisive, they partly support the constant-affine specification, in which the value of travel time variability...
Directory of Open Access Journals (Sweden)
W. Sinkala
2012-01-01
Full Text Available We use Lie symmetry analysis to solve a boundary value problem that arises in chemical engineering, namely, mass transfer during the contact of a solid slab with an overhead flowing fluid. This problem was earlier tackled using Adomian decomposition method (Fatoorehchi and Abolghasemi 2011, leading to the Adomian series form of solution. It turns out that the application of Lie group analysis yields an elegant form of the solution. After introducing the governing mathematical model and some preliminaries of Lie symmetry analysis, we compute the Lie point symmetries admitted by the governing equation and use these to construct the desired solution as an invariant solution.
The Markov chain method for solving dead time problems in the space dependent model of reactor noise
International Nuclear Information System (INIS)
Degweker, S.B.
1997-01-01
The discrete time Markov chain approach for deriving the statistics of time-correlated pulses, in the presence of a non-extending dead time, is extended to include the effect of space energy distribution of the neutron field. Equations for the singlet and doublet densities of follower neutrons are derived by neglecting correlations beyond the second order. These equations are solved by the modal method. It is shown that in the unimodal approximation, the equations reduce to the point model equations with suitably defined parameters. (author)
Showing a model's eye movements in examples does not improve learning of problem-solving tasks
van Marlen, Tim; van Wermeskerken, Margot; Jarodzka, Halszka; van Gog, Tamara
2016-01-01
Eye movement modeling examples (EMME) are demonstrations of a computer-based task by a human model (e.g., a teacher), with the model's eye movements superimposed on the task to guide learners' attention. EMME have been shown to enhance learning of perceptual classification tasks; however, it is an
Model-based problem solving through symbolic regression via pareto genetic programming
Vladislavleva, E.
2008-01-01
Pareto genetic programming methodology is extended by additional generic model selection and generation strategies that (1) drive the modeling engine to creation of models of reduced non-linearity and increased generalization capabilities, and (2) improve the effectiveness of the search for robust
Testing the slope model of scheduling preferences on stated preference data
DEFF Research Database (Denmark)
Abegaz, Dereje Fentie; Hjorth, Katrine; Rich, Jeppe
2017-01-01
are expected to yield similar results. We use stated preference data to compare the valuation of travel time variability under a structural model where trip-timing preferences are defined in terms of time-dependent utility rates, the “slope model”, against its reduced-form model. Two choice experiments...... are used that are identical except one has a fixed departure time while the other allows respondents to choose departure time freely. The empirical results in this paper do not support the theoretical equivalence of the two models as the implied value of travel time variability under the reduced-form model......The valuation of travel time variability is derived either from a structural model, given information on departure time, or directly from a reduced-form model where departure time is assumed to be optimally chosen. The two models are theoretically equivalent under certain assumptions, hence...
Guastello, Stephen J; Craven, Joanna; Zygowicz, Karen M; Bock, Benjamin R
2005-07-01
The process by which an initially leaderless group differentiates into one containing leadership and secondary role structures was examined using the swallowtail catastrophe model and principles of selforganization. The objectives were to identify the control variables in the process of leadership emergence in creative problem solving groups and production groups. In the first of two experiments, groups of university students (total N = 114) played a creative problem solving game. Participants later rated each other on leadership behavior, styles, and variables related to the process of conversation. A performance quality measure was included also. Control parameters in the swallowtail catastrophe model were identified through a combination of factor analysis and nonlinear regression. Leaders displayed a broad spectrum of behaviors in the general categories of Controlling the Conversation and Creativity in their role-play. In the second experiment, groups of university students (total N = 197) engaged in a laboratory work experiment that had a substantial production goal component. The same system of ratings and modeling strategy was used along with a work production measure. Leaders in the production task emerged to the extent that they exhibited control over both the creative and production aspects of the task, they could keep tension low, and the externally imposed production goals were realistic.
Planning and Scheduling for Environmental Sensor Networks
Frank, J. D.
2005-12-01
Environmental Sensor Networks are a new way of monitoring the environment. They comprise autonomous sensor nodes in the environment that record real-time data, which is retrieved, analyzed, integrated with other data sets (e.g. satellite images, GIS, process models) and ultimately lead to scientific discoveries. Sensor networks must operate within time and resource constraints. Sensors have limited onboard memory, energy, computational power, communications windows and communications bandwidth. The value of data will depend on when, where and how it was collected, how detailed the data is, how long it takes to integrate the data, and how important the data was to the original scientific question. Planning and scheduling of sensor networks is necessary for effective, safe operations in the face of these constraints. For example, power bus limitations may preclude sensors from simultaneously collecting data and communicating without damaging the sensor; planners and schedulers can ensure these operations are ordered so that they do not happen simultaneously. Planning and scheduling can also ensure best use of the sensor network to maximize the value of collected science data. For example, if data is best recorded using a particular camera angle but it is costly in time and energy to achieve this, planners and schedulers can search for times when time and energy are available to achieve the optimal camera angle. Planning and scheduling can handle uncertainty in the problem specification; planners can be re-run when new information is made available, or can generate plans that include contingencies. For example, if bad weather may prevent the collection of data, a contingent plan can check lighting conditions and turn off data collection to save resources if lighting is not ideal. Both mobile and immobile sensors can benefit from planning and scheduling. For example, data collection on otherwise passive sensors can be halted to preserve limited power and memory
Method of solving conformal models in D-dimensional space I
International Nuclear Information System (INIS)
Fradkin, E.S.; Palchik, M.Y.
1996-01-01
We study the Hilbert space of conformal field theory in D-dimensional space. The latter is shown to have model-independent structure. The states of matter fields and gauge fields form orthogonal subspaces. The dynamical principle fixing the choice of model may be formulated either in each of these subspaces or in their direct sum. In the latter case, gauge interactions are necessarily present in the model. We formulate the conditions specifying the class of models where gauge interactions are being neglected. The anomalous Ward identities are derived. Different values of anomalous parameters (D-dimensional analogs of a central charge, including operator ones) correspond to different models. The structure of these models is analogous to that of 2-dimensional conformal theories. Each model is specified by D-dimensional analog of null vector. The exact solutions of the simplest models of this type are examined. It is shown that these models are equivalent to Lagrangian models of scalar fields with a triple interaction. The values of dimensions of such fields are calculated, and the closed sets of differential equations for higher Green functions are derived. Copyright copyright 1996 Academic Press, Inc
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E.C. Biscaia Junior
2001-06-01
Full Text Available A dynamic kinetic-diffusive model for the extraction of metallic ions from aqueous liquors using liquid surfactant membranes is proposed. The model incorporates undesirable intrinsic phenomena such as swelling and breakage of the emulsion globules that have to be controlled during process operation. These phenomena change the spatial location of the chemical reaction during the course of extraction, resulting in a transient moving boundary problem. The orthogonal collocation method was used to transform the partial differential equations into an ordinary differential equation set that was solved by an implicit numerical routine. The model was found to be numerically stable and reliable in predicting the behaviour of zinc extraction with acidic extractant for long residence times.
Neilson, Peter D; Neilson, Megan D
2005-09-01
Adaptive model theory (AMT) is a computational theory that addresses the difficult control problem posed by the musculoskeletal system in interaction with the environment. It proposes that the nervous system creates motor maps and task-dependent synergies to solve the problems of redundancy and limited central resources. These lead to the adaptive formation of task-dependent feedback/feedforward controllers able to generate stable, noninteractive control and render nonlinear interactions unobservable in sensory-motor relationships. AMT offers a unified account of how the nervous system might achieve these solutions by forming internal models. This is presented as the design of a simulator consisting of neural adaptive filters based on cerebellar circuitry. It incorporates a new network module that adaptively models (in real time) nonlinear relationships between inputs with changing and uncertain spectral and amplitude probability density functions as is the case for sensory and motor signals.
1D and 2D Numerical Modeling for Solving Dam-Break Flow Problems Using Finite Volume Method
Directory of Open Access Journals (Sweden)
Szu-Hsien Peng
2012-01-01
Full Text Available The purpose of this study is to model the flow movement in an idealized dam-break configuration. One-dimensional and two-dimensional motion of a shallow flow over a rigid inclined bed is considered. The resulting shallow water equations are solved by finite volumes using the Roe and HLL schemes. At first, the one-dimensional model is considered in the development process. With conservative finite volume method, splitting is applied to manage the combination of hyperbolic term and source term of the shallow water equation and then to promote 1D to 2D. The simulations are validated by the comparison with flume experiments. Unsteady dam-break flow movement is found to be reasonably well captured by the model. The proposed concept could be further developed to the numerical calculation of non-Newtonian fluid or multilayers fluid flow.
Chen, Yu-Ren; Dye, Chung-Yuan
2013-06-01
In most of the inventory models in the literature, the deterioration rate of goods is viewed as an exogenous variable, which is not subject to control. In the real market, the retailer can reduce the deterioration rate of product by making effective capital investment in storehouse equipments. In this study, we formulate a deteriorating inventory model with time-varying demand by allowing preservation technology cost as a decision variable in conjunction with replacement policy. The objective is to find the optimal replenishment and preservation technology investment strategies while minimising the total cost over the planning horizon. For any given feasible replenishment scheme, we first prove that the optimal preservation technology investment strategy not only exists but is also unique. Then, a particle swarm optimisation is coded and used to solve the nonlinear programming problem by employing the properties derived from this article. Some numerical examples are used to illustrate the features of the proposed model.
Using a vision cognitive algorithm to schedule virtual machines
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Zhao Jiaqi
2014-09-01
Full Text Available Scheduling virtual machines is a major research topic for cloud computing, because it directly influences the performance, the operation cost and the quality of services. A large cloud center is normally equipped with several hundred thousand physical machines. The mission of the scheduler is to select the best one to host a virtual machine. This is an NPhard global optimization problem with grand challenges for researchers. This work studies the Virtual Machine (VM scheduling problem on the cloud. Our primary concern with VM scheduling is the energy consumption, because the largest part of a cloud center operation cost goes to the kilowatts used. We designed a scheduling algorithm that allocates an incoming virtual machine instance on the host machine, which results in the lowest energy consumption of the entire system. More specifically, we developed a new algorithm, called vision cognition, to solve the global optimization problem. This algorithm is inspired by the observation of how human eyes see directly the smallest/largest item without comparing them pairwisely. We theoretically proved that the algorithm works correctly and converges fast. Practically, we validated the novel algorithm, together with the scheduling concept, using a simulation approach. The adopted cloud simulator models different cloud infrastructures with various properties and detailed runtime information that can usually not be acquired from real clouds. The experimental results demonstrate the benefit of our approach in terms of reducing the cloud center energy consumption
A Note on Some Numerical Approaches to Solve a θ˙ Neuron Networks Model
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Samir Kumar Bhowmik
2014-01-01
Full Text Available Space time integration plays an important role in analyzing scientific and engineering models. In this paper, we consider an integrodifferential equation that comes from modeling θ˙ neuron networks. Here, we investigate various schemes for time discretization of a theta-neuron model. We use collocation and midpoint quadrature formula for space integration and then apply various time integration schemes to get a full discrete system. We present some computational results to demonstrate the schemes.
Solving Problems in Various Domains by Hybrid Models of High Performance Computations
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Yurii Rogozhin
2014-03-01
Full Text Available This work presents a hybrid model of high performance computations. The model is based on membrane system (P~system where some membranes may contain quantum device that is triggered by the data entering the membrane. This model is supposed to take advantages of both biomolecular and quantum paradigms and to overcome some of their inherent limitations. The proposed approach is demonstrated through two selected problems: SAT, and image retrieving.
A System for Automatically Generating Scheduling Heuristics
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.
Staff Scheduling within the Retail Business in Denmark
DEFF Research Database (Denmark)
Leedgaard, Jesper; Mortensen, Kim H.; Larsen, Allan
2002-01-01
Staff Scheduling within the retail business deals with the assignment of employees such as shop assistants to work tasks so that the right number of employees are available at any given times and the total staff costs are minimized. In this paper the retail staff scheduling problem is formulated...... as a Mixed Integer Problem. The retail staff scheduling problem is solved using the metaheuristic {\\$\\backslash\\$it Simulated Annealing}. The heuristic is implemented by modifying the original MIP model. Some of the constraints defined in the MIP are relaxed, entered into the objective function and weighted...... according to their relative importance. The problem is then formulated as minimizing the overall constraint violation. A thorough parameter test has been applied to the developed heuristics. The developed system has successfully been implemented in a number of shops and stores in Denmark....
Gerretsen, E.
2000-01-01
Prediction models for the airborne and impact sound transmission in buildings have recently been established (EN 12354- 1&2:1999). However, these models do not cover technical installations and machinery as a source of sound in buildings. Yet these can cause unacceptable sound levels and it is
Parallel Algorithm for Solving TOV Equations for Sequence of Cold and Dense Nuclear Matter Models
Ayriyan, Alexander; Buša, Ján; Grigorian, Hovik; Poghosyan, Gevorg
2018-04-01
We have introduced parallel algorithm simulation of neutron star configurations for set of equation of state models. The performance of the parallel algorithm has been investigated for testing set of EoS models on two computational systems. It scales when using with MPI on modern CPUs and this investigation allowed us also to compare two different types of computational nodes.
A problem-solving environment for data assimilation in air quality modelling
Velzen, N. van; Segers, A.J.
2010-01-01
A generic toolbox for data assimilation called COSTA (COmmon Set of Tools for the Assimilation of data) makes it possible to simplify the application of data assimilation to models and to try out various methods for a particular model. Concepts of object oriented programming are used to define
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