Hybrid metaheuristics for unrelated parallel machine scheduling with sequence-dependent setup times

Chen, Chun-Lung; Chen, Chuen-Lung

doi:10.1007/s00170-008-1692-1

Cited by 45 publications

(15 citation statements)

References 31 publications

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“…Lopes and De-Carvalho [24] presented a branch-and-price algorithm to minimize total weighted tardiness. Chen and Chen [25] proposed several hybrid metaheuristics based on variable neighborhood descent approach and TS method to minimize the number of tardy jobs. Their computational results indicated that the proposed hybrid metaheuristics outperform several basic TS heuristics.…”

Section: Literature Reviewmentioning

confidence: 99%

Scheduling unrelated parallel machines with sequence-dependent setup times

Zeidi

Mohammad-Hosseini

2015

Int J Adv Manuf Technol

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In this study, the problem of scheduling jobs on unrelated parallel machines with sequence-dependent setup times under due-date constraints is considered to minimize the total cost of tardiness and earliness. A new mathematical model is presented for considered problem and due to the complexity of the problem; an integrated meta-heuristic algorithm is designed to solve the problem. The proposed algorithm consists of genetic algorithm as the basic algorithm and simulated annealing method as local search procedure that follows the genetic algorithm to improve the quality of solutions. The performance of the proposed algorithm is evaluated by solving a set of test problems. The results show that the proposed integrated algorithm is effective.

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Section: Literature Reviewmentioning

confidence: 99%

Scheduling unrelated parallel machines with sequence-dependent setup times

Zeidi

Mohammad-Hosseini

2015

Int J Adv Manuf Technol

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“…R. Tavakkoli-Moghaddam et al presented a two-level MIP model and then used a genetic algorithm to solve the bi-objective parallel machine scheduling problem (Tavakkoli-Moghaddam et al 2009). A hybrid meta-heuristic was designed in Chen and Chen (2009) to minimize the weighted number of tardy jobs.…”

Section: Literature Reviewmentioning

confidence: 99%

Parallel Machine Scheduling with Resources Constraint and Sequence Dependent Setup Times

Hou

Guo

2012

Proceedings of 2012 3rd International Asia Conference on Industrial Engineering and Management Innovation (IEMI2012)

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This paper considered the scheduling problem of minimizing makespan on parallel machines with multiple resources constraint and job sequence dependent setup times. We proposed a mixed integer programming model to formulate the problem and used commercial software to get the optimal solution and Gantt chart of a small-size case. Then a Genetic Algorithm (GA) was developed to solve the problem in an acceptable time for large-size cases. Computational experiences shown that the proposed GA can achieve high quality solutions comparable to those obtained by commercial software and outperform the schedule rules existing in real manufacturing operation.

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“…The proposed algorithm produces solutions close to the optimum found by CPLEX in a short time. Chen and Chen [21] considered a problem with sequence-dependent setup times. They developed a solution procedure which integrates the virtues of the variable neighborhood descent approach and tabu search to minimize the weighted number of tardy jobs.…”

Section: Literature Reviewmentioning

confidence: 99%

“…In the second one, neighboring solutions are generated from scheduling vector by applying some traditional swap, insert, and reverse moves. Chen and Chen [21] proposed a hybrid meta-heuristic which integrates the principles of the variable neighborhood descent approach and tabu search. Four reduced-size neighborhood structures using swap and insert methods are proposed in the metaheuristic.…”

Section: Literature Reviewmentioning

confidence: 99%

An artificial bee colony algorithm approach for unrelated parallel machine scheduling with processing set restrictions, job sequence-dependent setup times, and due date

Caniyilmaz

Benli

Ilkay

2014

Int J Adv Manuf Technol

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The problem dealt with in this study has job sequence-dependent setup times under suitable machine constraints and due date constraints. The performance criterion for this problem is to minimize the sum of makespan and total tardiness. In the literature, an application of ABC algorithm for the problems which includes all the properties that we have dealt has not been discussed. Because there is no appropriate test data, a real-life data was collected from a factory. In this study, a new approach has been proposed for the solution with meta-heuristics of unrelated parallel machine scheduling problems which is a combinatorial problem. This new neighborhood approach provides different machine assignments for every candidate job sequences. This approach is used by integrating into ABC and GA. To evaluate the performances of the algorithms, the real-life problem was solved by using ABC and GA algorithms under similar conditions. It was found that all jobs can be completed in two shifts without the need for a third shift. Computational results show that ABC algorithm has better performance than GA.

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Hybrid metaheuristics for unrelated parallel machine scheduling with sequence-dependent setup times

Cited by 45 publications

References 31 publications

Scheduling unrelated parallel machines with sequence-dependent setup times

Scheduling unrelated parallel machines with sequence-dependent setup times

Parallel Machine Scheduling with Resources Constraint and Sequence Dependent Setup Times

An artificial bee colony algorithm approach for unrelated parallel machine scheduling with processing set restrictions, job sequence-dependent setup times, and due date

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