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Iterated Greedy methods for the distributed permutation flowshop scheduling problem

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  • Ruiz, Rubén
  • Pan, Quan-Ke
  • Naderi, Bahman

Abstract

Large manufacturing firms operate more than one production center. As a result, in relation to scheduling problems, which factory manufactures which product is an important consideration. In this paper we study an extension of the well known permutation flowshop scheduling problem in which there is a set of identical factories, each one with a flowshop structure. The objective is to minimize the maximum completion time or makespan among all factories. The resulting problem is known as the distributed permutation flowshop and has attracted considerable interest over the last few years. Contrary to the recent trend in the scheduling literature, where complex nature-inspired or metaphor-based methods are often proposed, we present simple Iterated Greedy algorithms that have performed well in related problems. Improved initialization, construction and destruction procedures, along with a local search with a strong intensification are proposed. The result is a very effective algorithm with little problem-specific knowledge that is shown to provide demonstrably better solutions in a comprehensive and thorough computational and statistical campaign.

Suggested Citation

  • Ruiz, Rubén & Pan, Quan-Ke & Naderi, Bahman, 2019. "Iterated Greedy methods for the distributed permutation flowshop scheduling problem," Omega, Elsevier, vol. 83(C), pages 213-222.
    • Handle: RePEc:eee:jomega:v:83:y:2019:i:c:p:213-222
    DOI: 10.1016/j.omega.2018.03.004
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    Cited by:

    1. Pourya Pourhejazy & Chen-Yang Cheng & Kuo-Ching Ying & Nguyen Hoai Nam, 2023. "Meta-Lamarckian-based iterated greedy for optimizing distributed two-stage assembly flowshops with mixed setups," Annals of Operations Research, Springer, vol. 322(1), pages 125-146, March.
    2. Yong Wang & Yuting Wang & Yuyan Han, 2023. "A Variant Iterated Greedy Algorithm Integrating Multiple Decoding Rules for Hybrid Blocking Flow Shop Scheduling Problem," Mathematics, MDPI, vol. 11(11), pages 1-25, May.
    3. Victor Abu-Marrul & Rafael Martinelli & Silvio Hamacher & Irina Gribkovskaia, 2023. "Simheuristic algorithm for a stochastic parallel machine scheduling problem with periodic re-planning assessment," Annals of Operations Research, Springer, vol. 320(2), pages 547-572, January.
    4. Arshad Ali & Yuvraj Gajpal & Tarek Y. Elmekkawy, 2021. "Distributed permutation flowshop scheduling problem with total completion time objective," OPSEARCH, Springer;Operational Research Society of India, vol. 58(2), pages 425-447, June.
    5. Victor Fernandez-Viagas & Luis Sanchez-Mediano & Alvaro Angulo-Cortes & David Gomez-Medina & Jose Manuel Molina-Pariente, 2022. "The Permutation Flow Shop Scheduling Problem with Human Resources: MILP Models, Decoding Procedures, NEH-Based Heuristics, and an Iterated Greedy Algorithm," Mathematics, MDPI, vol. 10(19), pages 1-32, September.
    6. Ferdinand Kóča & Hana Pačaiová & Renata Turisová & Andrea Sütőová & Peter Darvaši, 2023. "The Methodology for Assessing the Applicability of CSR into Supplier Management Systems," Sustainability, MDPI, vol. 15(17), pages 1-25, September.
    7. Xiaohui Zhang & Xinhua Liu & Shufeng Tang & Grzegorz Królczyk & Zhixiong Li, 2019. "Solving Scheduling Problem in a Distributed Manufacturing System Using a Discrete Fruit Fly Optimization Algorithm," Energies, MDPI, vol. 12(17), pages 1-24, August.
    8. Wendi Xu & Xianpeng Wang & Qingxin Guo & Xiangman Song & Ren Zhao & Guodong Zhao & Yang Yang & Te Xu & Dakuo He, 2022. "Gathering Strength, Gathering Storms: Knowledge Transfer via Selection for VRPTW," Mathematics, MDPI, vol. 10(16), pages 1-17, August.
    9. 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.
    10. Chenyao Zhang & Yuyan Han & Yuting Wang & Junqing Li & Kaizhou Gao, 2023. "A Distributed Blocking Flowshop Scheduling with Setup Times Using Multi-Factory Collaboration Iterated Greedy Algorithm," Mathematics, MDPI, vol. 11(3), pages 1-25, January.
    11. Mecler, Davi & Abu-Marrul, Victor & Martinelli, Rafael & Hoff, Arild, 2022. "Iterated greedy algorithms for a complex parallel machine scheduling problem," European Journal of Operational Research, Elsevier, vol. 300(2), pages 545-560.
    12. Wang, Yuhang & Han, Yuyan & Wang, Yuting & Tasgetiren, M. Fatih & Li, Junqing & Gao, Kaizhou, 2023. "Intelligent optimization under the makespan constraint: Rapid evaluation mechanisms based on the critical machine for the distributed flowshop group scheduling problem," European Journal of Operational Research, Elsevier, vol. 311(3), pages 816-832.
    13. Said Aqil & Karam Allali, 2021. "On a bi-criteria flow shop scheduling problem under constraints of blocking and sequence dependent setup time," Annals of Operations Research, Springer, vol. 296(1), pages 615-637, January.
    14. Perez-Gonzalez, Paz & Framinan, Jose M., 2024. "A review and classification on distributed permutation flowshop scheduling problems," European Journal of Operational Research, Elsevier, vol. 312(1), pages 1-21.

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