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Hybrid bat algorithm for flow shop scheduling problems

Author

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  • Ömür Tosun
  • M.K. Marichelvam

Abstract

In this paper, a hybrid bat algorithm is proposed to solve the permutation flow shop scheduling problems with makespan criterion. Developed for numerical optimisation, local search techniques are integrated into the bat algorithm to solve the flow shop problems. Reeves test problems from the literature are used to compare the performance of the proposed algorithm against the best known solutions, NEH and with different metaheuristics. Computational results and statistical analysis indicate that the proposed algorithm can be more efficient than many other metaheuristic algorithms addressed in the literature.

Suggested Citation

  • Ömür Tosun & M.K. Marichelvam, 2016. "Hybrid bat algorithm for flow shop scheduling problems," International Journal of Mathematics in Operational Research, Inderscience Enterprises Ltd, vol. 9(1), pages 125-138.
    • Handle: RePEc:ids:ijmore:v:9:y:2016:i:1:p:125-138
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    Cited by:

    1. Karimi-Mamaghan, Maryam & Mohammadi, Mehrdad & Pasdeloup, Bastien & Meyer, Patrick, 2023. "Learning to select operators in meta-heuristics: An integration of Q-learning into the iterated greedy algorithm for the permutation flowshop scheduling problem," European Journal of Operational Research, Elsevier, vol. 304(3), pages 1296-1330.

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