A hybrid algorithm for flexible job-shop scheduling problem with setup times

Ameni Azzouz, Meriem Ennigrou, Lamjed Ben Said

Abstract

Job-shop scheduling problem is one of the most important fields in manufacturing optimization where a set of n jobs must be processed on a set of m specified machines. Each job consists of a specific set of operations, which have to be processed according to a given order. The Flexible Job Shop problem (FJSP) is a generalization of the above-mentioned problem, where each operation can be processed by a set of resources and has a processing time depending on the resource used. The FJSP problems cover two difficulties, namely, machine assignment problem and operation sequencing problem. This paper addresses the flexible job-shop scheduling problem with sequence-dependent setup times to minimize two kinds of objectives function: makespan and bi-criteria objective function. For that, we propose a hybrid algorithm based on genetic algorithm (GA) and variable neighbourhood search (VNS) to solve this problem. To evaluate the performance of our algorithm, we compare our results with other methods existing in literature. All the results show the superiority of our algorithm against the available ones in terms of solution quality.

Keywords

Job-shop scheduling problem; Flexible manufacturing systems; sequence-dependent setup times; Genetic algorithms; local search

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References

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The International Journal of Advanced Manufacturing Technology  vol: 110  issue: 9-10  first page: 2445  year: 2020  
doi: 10.1007/s00170-020-05850-5



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