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Multi-objective sequence dependent setup times permutation flowshop: A new algorithm and a comprehensive study

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  • Ciavotta, Michele
  • Minella, Gerardo
  • Ruiz, Rubén

Abstract

The permutation flowshop scheduling problem has been thoroughly studied in recent decades, both from single objective as well as from multi-objective perspectives. To the best of our knowledge, little has been done regarding the multi-objective flowshop with Pareto approach when sequence dependent setup times are considered. As setup times and multi-criteria problems are important in industry, we must focus on this area. We propose a simple, yet powerful algorithm for the sequence dependent setup times flowshop problem with several criteria. The presented method is referred to as Restarted Iterated Pareto Greedy or RIPG and is compared against the best performing approaches from the relevant literature. Comprehensive computational and statistical analyses are carried out in order to demonstrate that the proposed RIPG method clearly outperforms all other algorithms and, as a consequence, it is a state-of-art method for this important and practical scheduling problem.

Suggested Citation

  • Ciavotta, Michele & Minella, Gerardo & Ruiz, Rubén, 2013. "Multi-objective sequence dependent setup times permutation flowshop: A new algorithm and a comprehensive study," European Journal of Operational Research, Elsevier, vol. 227(2), pages 301-313.
  • Handle: RePEc:eee:ejores:v:227:y:2013:i:2:p:301-313
    DOI: 10.1016/j.ejor.2012.12.031
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    Cited by:

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    4. Pablo Valledor & Alberto Gomez & Javier Puente & Isabel Fernandez, 2022. "Solving Rescheduling Problems in Dynamic Permutation Flow Shop Environments with Multiple Objectives Using the Hybrid Dynamic Non-Dominated Sorting Genetic II Algorithm," Mathematics, MDPI, vol. 10(14), pages 1-20, July.
    5. Yepes-Borrero, Juan C. & Perea, Federico & Ruiz, Rubén & Villa, Fulgencia, 2021. "Bi-objective parallel machine scheduling with additional resources during setups," European Journal of Operational Research, Elsevier, vol. 292(2), pages 443-455.
    6. Xiong, Hegen & Fan, Huali & Jiang, Guozhang & Li, Gongfa, 2017. "A simulation-based study of dispatching rules in a dynamic job shop scheduling problem with batch release and extended technical precedence constraints," European Journal of Operational Research, Elsevier, vol. 257(1), pages 13-24.
    7. V. Anjana & R. Sridharan & P. N. Ram Kumar, 2020. "Metaheuristics for solving a multi-objective flow shop scheduling problem with sequence-dependent setup times," Journal of Scheduling, Springer, vol. 23(1), pages 49-69, February.
    8. Sioud, A. & Gagné, C., 2018. "Enhanced migrating birds optimization algorithm for the permutation flow shop problem with sequence dependent setup times," European Journal of Operational Research, Elsevier, vol. 264(1), pages 66-73.
    9. Zixiang Li & Mukund Nilakantan Janardhanan & S. G. Ponnambalam, 2021. "Cost-oriented robotic assembly line balancing problem with setup times: multi-objective algorithms," Journal of Intelligent Manufacturing, Springer, vol. 32(4), pages 989-1007, April.

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