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Scatter search for minimizing weighted tardiness in a single machine scheduling with setups

Author

Listed:
  • Miguel A. González

    (University of Oviedo)

  • Juan José Palacios

    (University of Oviedo)

  • Camino R. Vela

    (University of Oviedo)

  • Alejandro Hernández-Arauzo

    (University of Oviedo)

Abstract

Single machine scheduling problems have many real-life applications and may be hard to solve due to the particular characteristics of some production environments. In this paper, we tackle the single machine scheduling problem with sequence-dependent setup times with the objective of minimizing the weighted tardiness. To solve this problem, we propose a scatter search algorithm which uses path relinking in its core. This algorithm is enhanced with some procedures to speed-up the neighbors’ evaluation and with some diversification and intensification techniques, the latter taking some elements from iterated local search. We conducted an experimental study across a well-known set of instances to analyze the contribution of each component to the overall performance of the algorithm, as well as to compare our proposal with the state-of-the-art metaheuristics, obtaining competitive results. We also propose a new benchmark with larger and more challenging instances and provide the first results for them.

Suggested Citation

  • Miguel A. González & Juan José Palacios & Camino R. Vela & Alejandro Hernández-Arauzo, 2017. "Scatter search for minimizing weighted tardiness in a single machine scheduling with setups," Journal of Heuristics, Springer, vol. 23(2), pages 81-110, June.
  • Handle: RePEc:spr:joheur:v:23:y:2017:i:2:d:10.1007_s10732-017-9325-1
    DOI: 10.1007/s10732-017-9325-1
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    References listed on IDEAS

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    Cited by:

    1. Wenzhu Liao & Tong Wang, 2018. "Promoting Green and Sustainability: A Multi-Objective Optimization Method for the Job-Shop Scheduling Problem," Sustainability, MDPI, vol. 10(11), pages 1-19, November.
    2. Ronghua Meng & Yunqing Rao & Qiang Luo, 2020. "Modeling and solving for bi-objective cutting parallel machine scheduling problem," Annals of Operations Research, Springer, vol. 285(1), pages 223-245, February.

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