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Proceedings Year : 2021

A Random-key based genetic algorithm for the flexible job-shop scheduling minimizing total completion time

Abstract

This paper studies the flexible job-shop scheduling problem (FJSP) with the objective of minimizing the total completion time. This problem is known to be strongly NP-hard [1]. Therefore, it is quite difficult to achieve an optimal solution to this problem with exact methods and heuristic approaches are generally used to find near optimal solutions within a reasonable computation time. The present work proposes a Random-Key based genetic algorithm for the joint resolution of the inherent assignment and sequencing subproblems. A new chromosome encoding method with some effective crossover and mutation operators are introduced. Also, a mixed integer linear program is developed and tested. Computational experiments are carried out on a large set of instances. The proposed algorithm is proved to be both effective and efficient in solving the studied problem.
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Dates and versions

hal-03999937 , version 1 (22-02-2023)

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Asma Fekih, Hatem Hadda, Imed Kacem, Atidel Hadj-Alouane. A Random-key based genetic algorithm for the flexible job-shop scheduling minimizing total completion time. IEEE, pp.443-447, 2021, ⟨10.1109/DESE54285.2021.9719336⟩. ⟨hal-03999937⟩
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