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Models and matheuristics for the unrelated parallel machine scheduling problem with additional resources

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  • Fanjul-Peyro, Luis
  • Perea, Federico
  • Ruiz, Rubén

Abstract

In this paper we analyze a parallel machine scheduling problem in which the processing of jobs on the machines requires a number of units of a scarce resource. This number depends both on the job and on the machine. The availability of resources is limited and fixed throughout the production horizon. The objective considered is the minimization of the makespan. We model this problem by means of two integer linear programming problems. One of them is based on a model previously proposed in the literature. The other one, which is based on the resemblance to strip packing problems, is an original contribution of this paper. As the models presented are incapable of solving medium-sized instances to optimality, we propose three matheuristic strategies for each of these two models. The algorithms proposed are tested over an extensive computational experience. Results show that the matheuristic strategies significantly outperform the mathematical models.

Suggested Citation

  • Fanjul-Peyro, Luis & Perea, Federico & Ruiz, Rubén, 2017. "Models and matheuristics for the unrelated parallel machine scheduling problem with additional resources," European Journal of Operational Research, Elsevier, vol. 260(2), pages 482-493.
    • Handle: RePEc:eee:ejores:v:260:y:2017:i:2:p:482-493
    DOI: 10.1016/j.ejor.2017.01.002
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    References listed on IDEAS

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    6. Ana Rita Antunes & Marina A. Matos & Ana Maria A. C. Rocha & Lino A. Costa & Leonilde R. Varela, 2022. "A Statistical Comparison of Metaheuristics for Unrelated Parallel Machine Scheduling Problems with Setup Times," Mathematics, MDPI, vol. 10(14), pages 1-19, July.
    7. Perea, Federico & Yepes-Borrero, Juan C. & Menezes, Mozart B.C., 2023. "Acceptance Ordering Scheduling Problem: The impact of an order-portfolio on a make-to-order firm’s profitability," International Journal of Production Economics, Elsevier, vol. 264(C).
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    14. Norelhouda Sekkal & Fayçal Belkaid, 0. "A multi-objective simulated annealing to solve an identical parallel machine scheduling problem with deterioration effect and resources consumption constraints," Journal of Combinatorial Optimization, Springer, vol. 0, pages 1-37.
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    19. 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.
    20. Bentao Su & Naiming Xie & Yingjie Yang, 2021. "Hybrid genetic algorithm based on bin packing strategy for the unrelated parallel workgroup scheduling problem," Journal of Intelligent Manufacturing, Springer, vol. 32(4), pages 957-969, April.
    21. Yantong Li & Jean-François Côté & Leandro Callegari-Coelho & Peng Wu, 2022. "Novel Formulations and Logic-Based Benders Decomposition for the Integrated Parallel Machine Scheduling and Location Problem," INFORMS Journal on Computing, INFORMS, vol. 34(2), pages 1048-1069, March.
    22. Hesham K. Alfares, 2022. "Plant shutdown maintenance workforce team assignment and job scheduling," Journal of Scheduling, Springer, vol. 25(3), pages 321-338, June.
    23. Emine Akyol Ozer & Tugba Sarac, 2019. "MIP models and a matheuristic algorithm for an identical parallel machine scheduling problem under multiple copies of shared resources constraints," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 27(1), pages 94-124, April.
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    25. Prahalad Venkateshan & Joseph Szmerekovsky & George Vairaktarakis, 2020. "A cutting plane approach for the multi-machine precedence-constrained scheduling problem," Annals of Operations Research, Springer, vol. 285(1), pages 247-271, February.

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