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Two hybrid flow shop scheduling lines with assembly stage and compatibility constraints

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  • Rafael Muñoz-Sánchez
  • Iris Martínez-Salazar
  • José Luis González-Velarde
  • Yasmín Á Ríos Solís

Abstract

Two hybrid flow shop scheduling lines must be coordinated to assemble batches of terminated products at their last stage. Each product is thus composed of two jobs, each produced in one of the lines. The set of jobs is to be processed in a series of stages to minimize the makespan of the scheduling, but jobs forming a product must arrive at the assembly line simultaneously. We propose a mixed integer linear programming model. Then, based on the model, we propose a pull-matheuristic algorithm. Finally, we present two metaheuristics, a greedy randomized adaptive search procedure and a biased random key genetic algorithm, and compare all the methodologies with real-based instances of a production scheduling problem in the automobile manufacturing industry. The greedy algorithm yields high-quality solutions, while the genetic one offers the best computational times.

Suggested Citation

  • Rafael Muñoz-Sánchez & Iris Martínez-Salazar & José Luis González-Velarde & Yasmín Á Ríos Solís, 2024. "Two hybrid flow shop scheduling lines with assembly stage and compatibility constraints," PLOS ONE, Public Library of Science, vol. 19(6), pages 1-16, June.
    • Handle: RePEc:plo:pone00:0304119
    DOI: 10.1371/journal.pone.0304119
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    References listed on IDEAS

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    4. Xiang Tian & Xiyu Liu & Hongyan Zhang & Minghe Sun & Yuzhen Zhao, 2020. "A DNA algorithm for the job shop scheduling problem based on the Adleman-Lipton model," PLOS ONE, Public Library of Science, vol. 15(12), pages 1-21, December.
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