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1998, European Journal of Operational Research
In this paper we apply the tabu search (TS) technique to a complex machine scheduling problem. The problem can be considered as a generalization of the job-shop problem with both simple and parallel machines, job batches. setup times and release and due dates. The goal is to obtain feasible schedules by minimizing the makespan C,,,,, if the problem is feasible, or to obtain a "best compromise" schedule if a full solution is not possible. The TS algorithm developed here is distinguished mainly by two aspects. Firstly, the core of the procedure is a tabu thresholding algorithm which uses a sophisticated set of moves aimed at resolving violated constraints. Secondly. the TS algorithm supplements the central tabu thresholding algorithm with two diversification strategies which are dependent on the state of the search. These strategies involve fairly major disruption of the schedules, and force significant diversification of the search. Computational experiments show that our algorithm can find high quality schedules in short running times.
International Journal of Operations …, 2006
OR Spektrum, 1994
In this paper we study the following generalization of the job-shop scheduling problem. Each operation can be performed by one machine out of a set of machines given for this operation. The processing time does not depend on the machine which has been chosen ...
Discrete Applied Mathematics, 1996
Flexible manufacturing systems (FMSs) are nowadays installed in the mechanical industry. In such systems. many different part types are produced simultaneously and it is necessary to take tooling constraints into account for finding an optimal schedule.
Annals of Operations Research, 1993
In this paper, we apply the tabu-search technique to the job-shop scheduling problem, a notoriously difficult problem in combinatorial optimization. We show that our implementation of this method dominates both a previous approach with tabu search and the other heuristics based on iterative improvements.
2005
Tabu search algorithms are developed for solving a large class of cyclic machine scheduling problems with the objective to minimize the cycle time. Neighborhoods are derived which generalize the block-approach based neighborhoods which have been successfully applied to noncyclic job-shop problems. For a variant of this neighborhood opt-connectivity is proved.
This paper addresses minimizing Total Weighted Earliness/Tardiness (TWET) of jobs in a Flexible Job Shop (FJS) problem. The FJS problem is an extension of the classical Job Shop (JS) problem that implies each operation may be assigned to alternative available machines. So, a job may have alternative routing. The FJS problem with a TWET criterion is modeled as a mixed integer programming. The model is proven to be Np-complete. To solve the model, an algorithm, based on a Tabu Search approach (TS), is developed. The proposed algorithm employs TS to nd the best routing of each job and a backward procedure to operations scheduling. Two neighboring functions a r e designed and their e ect is investigated on the performance. The numerical experiments show the suggested algorithm e ciently solves the model in a reasonable CPU time.
Control and Cybernetics, 2000
A bstract: Most of multiple criteria scheduling problems are NP-hard, so that exact procedures can only solve small problems and with two criteria. The complexity and the diversity of multiple criteria scheduling problems resulted in many alternative approaches to solve them. Exact and approximate procedures proposed in the literature are mainly dedicated to the problem to be solved and their performance depends on the problem data, on the criteria optimized, and are generally difficult to implement. We propose in this paper a Tabu Search approach to multiple criteria scheduling problems. The proposed procedure is a general flexible method, able to solve hard multiple criteria scheduling problems, easy to implement, and providing a set of potential efficient schedules. The criteria are any combination chosen from (Cmax, Tmax ,I, Nr and F).
Computers & Operations Research, 2012
In this paper, we propose a model for Flexible Job Shop Scheduling Problem (FJSSP) with transportation constraints and bounded processing times. This is a NP hard problem. Objectives are to minimize the makespan and the storage of solutions. A genetic algorithm with tabu search procedure is proposed to solve both assignment of resources and sequencing problems on each resource. In order to evaluate the proposed algorithm's efficiency, five types of instances are tested. Three of them consider sequencing problems with or without assignment of processing or/and transport resources. The fourth and fifth ones introduce bounded processing times which mainly characterize Surface Treatment Facilities (STFs). Computational results show that our model and method are efficient for solving both assignment and scheduling problems in various kinds of systems.
2002
In this paper, a multiple dispatching rule based meta-heuristic solution approach for Job Shop Scheduling Problems (JSSP) is presented. The proposed algorithm makes use of Giffler & Thompson's heuristic in deducting feasible schedules and Multiple Objective Tabu Search (MOTS) in generating optimal schedules. Several example problems are solved from the literature to present the effectiveness of the proposed algorithm. The results obtained from the computational study have shown that the proposed algorithm can be used as a new alternative solution technique for finding good solutions to this complex problem.
2017
Scheduling in production systems consists in assigning operations on a set of available resources in order to achieve defined objectives. The Flexible Job shop Scheduling Problem (FJSP) is one of the scheduling problems where each operation can be processed on different machine and its processing time depends on the used machine. But in the recent years, many companies decide to move towards the decentralization of their factories which allow it to gain advantages towards its customers. In the case of the classic Flexible Job shop Scheduling Problem, we assume that there is a single factory with a set of m machines and n jobs, but in Distributed and Flexible Job shop Scheduling Problem (DFJSP), there is a set of geographically distributed factories in different locations. Each factory contains m machines on which n jobs must be processed. The Distributed scheduling problems and more specifically the DFJSP are much more complicated than standard problems because they involve not only the problem of assigning jobs to machines but also the problem of distribution of jobs in different factories. So, the DFJSP is harder than the FJSP. The DFJSP is classified, as most of scheduling problems, NP-Hard in complexity theory. In this paper, we propose a decentralized model based on tabu search to solve the Distributed and Flexible Job shop Scheduling Problem in order to minimize the maximum completion time (makespan). To evaluate the performance of our model, a set of experiments are performed on benchmark instances well known in the literature.
IFAC Proceedings Volumes, 2012
This article deals with the parallel machines scheduling problem to minimize the total tardiness, when jobs have different release dates. Preemption and splitting are not allowed. Since machines are considered identical, assigning a job to any of the available machines does not affect its processing time. This problem is considered NP-hard. This article presents a Tabu Search method to solve the problem, as well as a mathematical model. The proposed method is compared to a Local Search algorithm and other methods from literature, performing over 1000 different instances. The obtained results are discussed and analyzed to identify dominant structures of solutions.
Journal of Intelligent Manufacturing, 2004
This paper presents a tabu search approach for the job-shop scheduling problem. Although the problem is NP-hard, satisfactory solutions have been obtained recently by tabu search. However, tabu search has a problem-specific and parametric structure. Therefore, in the paper, we focussed on the tabu search strategies and parameters such as initial solution, neighborhood structure, tabu list, aspiration criterion, elite solutions list, intensification, diversification and the number of iteration. In order to compare some neighborhood strategies and tabu list length methods, a computational study is done on the benchmark problems.
Journal of Intelligent Manufacturing, 2013
We tackle the job shop scheduling problem with sequence dependent setup times and maximum lateness minimization by means of a tabu search algorithm. We start by defining a disjunctive model for this problem, which allows us to study some properties of the problem. Using these properties we define a new local search neighborhood structure, which is then incorporated into the proposed tabu search algorithm. To assess the performance of this algorithm, we present the results of an extensive experimental study, including an analysis of the tabu search algorithm under different running conditions and a comparison with the state-of-the-art algorithms. The experiments are performed across two sets of conventional benchmarks with 960 and 17 instances respectively. The results demonstrate that the proposed tabu search algorithm is superior to the state-of-the-art methods both in quality and stability. In particular, our algorithm establishes new best solutions for 817 of the 960 instances of the first set and reaches the best known solutions in 16 of the 17 instances of the second set. Keywords scheduling • tabu search • setup times • lateness minimization • computational experiments.
Computers & Operations Research, 2004
In this study, a Tabu Search (TS) approach to the parallel machine scheduling problem is presented. The problem considered consists of a set of independent jobs to be scheduled on a number of parallel processors to minimize total tardiness. Several surveys on parallel machine scheduling with due date related objectives [ 1, 2, 3] reveal that the NP-hard nature of the problem renders it a challenging area for many researchers who studied various versions.
2018
Job shop scheduling problem (JSP) is an attractive field for researchers and production managers since it is a famous problem in many industries and a complex problem for researchers. Due to NP-hardness property of this problem, many meta-heuristics are developed to solve it. Solution representation (solution seed) is an important element for any meta-heuristic algorithm. Therefore, many researchers try to present different encodings to solve this problem. Fattahi et al., and Gen & Cheng suggested two solutions for this problem that both have advantages and weaknesses in searching solution space to reach an acceptable solution. In the current paper, a cyclic algorithm based on tabu search algorithm was proposed to improve the exploration and exploitation powers of these encodings. Also, several problems of different sizes are solved by it and the obtained results were compared. Results showed the applicability and effectiveness of the proposed solution representation in comparison w...
This paper presents two Tabu Search type algorithms for solving the multiprocessor scheduling problem. This problem consists in finding a schedule for a general task graph to be executed on a multiprocessor system so that the schedule length can be minimized. The multiprocessor scheduling problem is known to be NP-hard, and to obtain optimal and suboptimal solutions, several heuristic based algorithms have been developed in . Our approaches are validated on 13 randomly generated instances. The numerical results show that our algorithms produce solutions closer to optimality and/or of better quality than the methods presented in .
Journal of Scheduling
We consider in this work a bicriteria scheduling problem on two different parallel machines with a periodic preventive maintenance policy. The two objectives considered involve minimization of job rejection costs and weighted sum of completion times. They are handled through a lexicographic approach, due to a natural hierarchy among the two objectives in the applications considered. The main contributions of this paper are first to present a new problem relevant to practice, second, to develop a mixed-integer-linear-program model for the problem, and third, to introduce two generalizable tabu-search metaheuristics relying on different neighborhood structures and solution spaces. Computational results for 120 instances (generated from a real case) are reported to empirically demonstrate the effectiveness of the proposed metaheuristics.
2010
This paper presents two Tabu Search type algorithms for solving the multiprocessor scheduling problem. This problem consists in finding a schedule for a general task graph to be executed on a multiprocessor system so that the schedule length can be minimized. The multiprocessor scheduling problem is known to be NP-hard, and to obtain optimal and suboptimal solutions, several heuristic based algorithms have been developed in . Our approaches are validated on 13 randomly generated instances. The numerical results show that our algorithms produce solutions closer to optimality and/or of better quality than the methods presented in .
African Journal of Business Management, 2011
In modern manufacturing and production systems, flexibility has increased as a response mechanism toward changes. In such systems, a piece may have several flexible process programs. In this study, scheduling problem in flexible job-shop manufacturing production systems is studied with minimization objective function of make span () "and" average time in completion of pieces () that is consistent with, just in time philosophy and management objectives of supply chain. Concerning problem being NP-hard, heuristic method is proposed to solve it based on tabu search algorithm which is compared with a hierarchical method. Performance criteria for comparison are "response quality" and "calculation time" in which results of numerical test approve the priority of tabu search algorithm in comparison to hierarchical method.
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