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Symbiotic organisms search algorithm for the unrelated parallel machines scheduling with sequence-dependent setup times

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  • Absalom E Ezugwu
  • Olawale J Adeleke
  • Serestina Viriri

Abstract

This paper addresses the problem of makespan minimization on unrelated parallel machines with sequence dependent setup times. The symbiotic organisms search (SOS) algorithm is a new and popular global optimization technique that has received wide acceptance in recent years from researchers in continuous and discrete optimization domains. An improved SOS algorithm is developed to solve the parallel machine scheduling problem. Since the standard SOS algorithm was originally developed to solve continuous optimization problems, a new solution representation and decoding procedure is designed to make the SOS algorithm suitable for the unrelated parallel machine scheduling problem (UPMSP). Similarly, to enhance the solution quality of the SOS algorithm, an iterated local search strategy based on combining variable numbers of insertion and swap moves is incorporated into the SOS algorithm. More so, to further improve the SOS optimization speed and performance, the longest processing time first (LPT) rule is used to design a machine assignment heuristic that assigns processing machines to jobs based on the machine dynamic load-balancing mechanism. Subsequently, the machine assignment scheme is incorporated into SOS algorithms and used to solve the UPMSP. The performances of the proposed methods are evaluated by comparing their solutions with other existing techniques from the literature. A number of statistical tests were also conducted to determine the variations in performance for each of the techniques. The experimental results showed that the SOS with LPT (SOS-LPT) heuristic has the best performance compared to other tested method, which is closely followed by SOS algorithm, indicating that the two proposed algorithms’ solution approaches are reasonable and effective for solving large-scale UPMSPs.

Suggested Citation

  • Absalom E Ezugwu & Olawale J Adeleke & Serestina Viriri, 2018. "Symbiotic organisms search algorithm for the unrelated parallel machines scheduling with sequence-dependent setup times," PLOS ONE, Public Library of Science, vol. 13(7), pages 1-23, July.
    • Handle: RePEc:plo:pone00:0200030
    DOI: 10.1371/journal.pone.0200030
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    References listed on IDEAS

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    1. Chen, Yin-Yann & Cheng, Chen-Yang & Wang, Li-Chih & Chen, Tzu-Li, 2013. "A hybrid approach based on the variable neighborhood search and particle swarm optimization for parallel machine scheduling problems—A case study for solar cell industry," International Journal of Production Economics, Elsevier, vol. 141(1), pages 66-78.
    2. Armentano, Vinicius Amaral & de Franca Filho, Moacir Felizardo, 2007. "Minimizing total tardiness in parallel machine scheduling with setup times: An adaptive memory-based GRASP approach," European Journal of Operational Research, Elsevier, vol. 183(1), pages 100-114, November.
    3. Secui, Dinu Calin, 2016. "A modified Symbiotic Organisms Search algorithm for large scale economic dispatch problem with valve-point effects," Energy, Elsevier, vol. 113(C), pages 366-384.
    4. Mokotoff, E. & Chretienne, P., 2002. "A cutting plane algorithm for the unrelated parallel machine scheduling problem," European Journal of Operational Research, Elsevier, vol. 141(3), pages 515-525, September.
    5. Mokotoff, Ethel, 2004. "An exact algorithm for the identical parallel machine scheduling problem," European Journal of Operational Research, Elsevier, vol. 152(3), pages 758-769, February.
    6. Vallada, Eva & Ruiz, Rubén, 2011. "A genetic algorithm for the unrelated parallel machine scheduling problem with sequence dependent setup times," European Journal of Operational Research, Elsevier, vol. 211(3), pages 612-622, June.
    7. Mauro Dell’Amico & Silvano Martello, 1995. "Optimal Scheduling of Tasks on Identical Parallel Processors," INFORMS Journal on Computing, INFORMS, vol. 7(2), pages 191-200, May.
    8. Dell'Amico, Mauro & Martello, Silvano, 2005. "A note on exact algorithms for the identical parallel machine scheduling problem," European Journal of Operational Research, Elsevier, vol. 160(2), pages 576-578, January.
    9. Tanaka, Shunji & Araki, Mituhiko, 2008. "A branch-and-bound algorithm with Lagrangian relaxation to minimize total tardiness on identical parallel machines," International Journal of Production Economics, Elsevier, vol. 113(1), pages 446-458, May.
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    Cited by:

    1. Jesús Isaac Vázquez-Serrano & Leopoldo Eduardo Cárdenas-Barrón & Rodrigo E. Peimbert-García, 2021. "Agent Scheduling in Unrelated Parallel Machines with Sequence- and Agent–Machine–Dependent Setup Time Problem," Mathematics, MDPI, vol. 9(22), pages 1-34, November.
    2. J. Adan, 2022. "A hybrid genetic algorithm for parallel machine scheduling with setup times," Journal of Intelligent Manufacturing, Springer, vol. 33(7), pages 2059-2073, October.
    3. Jean-Paul Arnaout, 2020. "A worm optimization algorithm to minimize the makespan on unrelated parallel machines with sequence-dependent setup times," Annals of Operations Research, Springer, vol. 285(1), pages 273-293, February.

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