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A hybrid VNS-HS algorithm for a supply chain scheduling problem with deteriorating jobs

Author

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  • Xinbao Liu
  • Shaojun Lu
  • Jun Pei
  • Panos M. Pardalos

Abstract

This paper investigates a coordinated scheduling problem in a two stage supply chain where parallel-batching machine, deteriorating jobs and transportation coordination are considered simultaneously. During the production stage, jobs are processed by suppliers and there exists one parallel-batching machine in each supplier. The actual processing time of a job depends on its starting time and normal processing time. The normal processing time of a batch is equal to the largest normal processing time among all jobs in its batch. During the transportation stage, the jobs are then delivered to the manufacturer. Since suppliers are distributed in different locations, the transportation time between each supplier and the manufacturer is different. Based on some structural properties of the studied problem, an optimal algorithm for minimising makespan on a single supplier is presented. This supply chain scheduling problem is proved to be NP-hard, and a hybrid VNS-HS algorithm combining variable neighbourhood search (VNS) with harmony search (HS) is proposed to find a good solution in reasonable time. Finally, some computational experiments are conducted and the results demonstrate the effectiveness and efficiency of the proposed VNS-HS.

Suggested Citation

  • Xinbao Liu & Shaojun Lu & Jun Pei & Panos M. Pardalos, 2018. "A hybrid VNS-HS algorithm for a supply chain scheduling problem with deteriorating jobs," International Journal of Production Research, Taylor & Francis Journals, vol. 56(17), pages 5758-5775, September.
    • Handle: RePEc:taf:tprsxx:v:56:y:2018:i:17:p:5758-5775
    DOI: 10.1080/00207543.2017.1418986
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    Citations

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    Cited by:

    1. Bartłomiej Przybylski, 2022. "Parallel-machine scheduling of jobs with mixed job-, machine- and position-dependent processing times," Journal of Combinatorial Optimization, Springer, vol. 44(1), pages 207-222, August.
    2. Wenjuan Fan & Yi Wang & Tongzhu Liu & Guixian Tong, 2020. "A patient flow scheduling problem in ophthalmology clinic solved by the hybrid EDA–VNS algorithm," Journal of Combinatorial Optimization, Springer, vol. 39(2), pages 547-580, February.
    3. Xue Huang & Na Yin & Wei-Wei Liu & Ji-Bo Wang, 2020. "Common Due Window Assignment Scheduling with Proportional Linear Deterioration Effects," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 37(01), pages 1-15, January.
    4. Kaining Shao & Wenjuan Fan & Zishu Yang & Shanlin Yang & Panos M. Pardalos, 2022. "A column generation approach for patient scheduling with setup time and deteriorating treatment duration," Operational Research, Springer, vol. 22(3), pages 2555-2586, July.
    5. Xinyu Sun & Xin-Na Geng & Tao Liu, 2020. "Due-window assignment scheduling in the proportionate flow shop setting," Annals of Operations Research, Springer, vol. 292(1), pages 113-131, September.
    6. Jun Pei & Qingru Song & Baoyu Liao & Xinbao Liu & Panos M. Pardalos, 2021. "Parallel-machine serial-batching scheduling with release times under the effects of position-dependent learning and time-dependent deterioration," Annals of Operations Research, Springer, vol. 298(1), pages 407-444, March.
    7. Yong-Jae Kim & Byung-Soo Kim, 2022. "Population-Based Meta-Heuristic Algorithms for Integrated Batch Manufacturing and Delivery Scheduling Problem," Mathematics, MDPI, vol. 10(21), pages 1-22, November.

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