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Cooperative metaheuristics for the permutation flowshop scheduling problem

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  • Vallada, Eva
  • Ruiz, Rubén

Abstract

In this work, we propose cooperative metaheuristic methods for the permutation flowshop scheduling problem considering two objectives separately: total tardiness and makespan. We use the island model where each island runs an instance of the algorithm and communications start when the islands have reached certain level of evolution, that is, communication is not allowed from the beginning of the execution. Subsequent ones occur when new better solutions are found. We carry out an exhaustive comparison of the cooperative methods against the sequential counterparts running in completely comparable scenarios. Results have been carefully analysed by means of statistical procedures and we can conclude that the cooperative methods yield much better results than the sequential algorithms and state-of-the-art methods running in the same number of processors but without communications. The proposed cooperative schemes are easy to apply to other algorithms and problems.

Suggested Citation

  • Vallada, Eva & Ruiz, Rubén, 2009. "Cooperative metaheuristics for the permutation flowshop scheduling problem," European Journal of Operational Research, Elsevier, vol. 193(2), pages 365-376, March.
  • Handle: RePEc:eee:ejores:v:193:y:2009:i:2:p:365-376
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    8. Ruiz, Ruben & Stutzle, Thomas, 2007. "A simple and effective iterated greedy algorithm for the permutation flowshop scheduling problem," European Journal of Operational Research, Elsevier, vol. 177(3), pages 2033-2049, March.
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    Cited by:

    1. Choi, Byung-Cheon & Lee, Kangbok & Leung, Joseph Y.-T. & Pinedo, Michael L., 2010. "Flow shops with machine maintenance: Ordered and proportionate cases," European Journal of Operational Research, Elsevier, vol. 207(1), pages 97-104, November.
    2. Yenisey, Mehmet Mutlu & Yagmahan, Betul, 2014. "Multi-objective permutation flow shop scheduling problem: Literature review, classification and current trends," Omega, Elsevier, vol. 45(C), pages 119-135.
    3. Pan, Quan-Ke & Ruiz, Rubén, 2014. "An effective iterated greedy algorithm for the mixed no-idle permutation flowshop scheduling problem," Omega, Elsevier, vol. 44(C), pages 41-50.
    4. Ruiz-Torres, Alex J. & Ho, Johnny C. & Ablanedo-Rosas, José H., 2011. "Makespan and workstation utilization minimization in a flowshop with operations flexibility," Omega, Elsevier, vol. 39(3), pages 273-282, June.
    5. Naderi, Bahman & Ruiz, Rubén, 2014. "A scatter search algorithm for the distributed permutation flowshop scheduling problem," European Journal of Operational Research, Elsevier, vol. 239(2), pages 323-334.
    6. Li, Xiaoping & Chen, Long & Xu, Haiyan & Gupta, Jatinder N.D., 2015. "Trajectory Scheduling Methods for minimizing total tardiness in a flowshop," Operations Research Perspectives, Elsevier, vol. 2(C), pages 13-23.
    7. Martín Ravetti & Carlos Riveros & Alexandre Mendes & Mauricio Resende & Panos Pardalos, 2012. "Parallel hybrid heuristics for the permutation flow shop problem," Annals of Operations Research, Springer, vol. 199(1), pages 269-284, October.
    8. Vallada, Eva & Ruiz, Rubén & Framinan, Jose M., 2015. "New hard benchmark for flowshop scheduling problems minimising makespan," European Journal of Operational Research, Elsevier, vol. 240(3), pages 666-677.
    9. Schryen, Guido, 2020. "Parallel computational optimization in operations research: A new integrative framework, literature review and research directions," European Journal of Operational Research, Elsevier, vol. 287(1), pages 1-18.

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