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Optimizing Perishable Product Supply Chain Network Using Hybrid Metaheuristic Algorithms

Author

Listed:
  • Lihong Pan

    (Business School, Hunan University, Changsha 410082, China)

  • Miyuan Shan

    (Business School, Hunan University, Changsha 410082, China)

  • Linfeng Li

    (Business School, Hunan Agricultural University, Changsha 410128, China)

Abstract

This paper focuses on optimizing the long- and short-term planning of the perishable product supply chain network (PPSCN). It addresses the integration of strategic location, tactical inventory, and operational routing decisions. Additionally, it takes into consideration the specific characteristics of perishable products, including their shelf life, inventory management, and transportation damages. The main objective is to minimize the overall supply chain cost. To achieve this, a nonlinear mixed integer programming model is developed for the multi-echelon, multi-product, and multi-period location-inventory-routing problem (LIRP) in the PPSCN. Two hybrid metaheuristic algorithms, namely genetic algorithm (GA) and multiple population genetic algorithm (MPGA), are hybridized with variable neighborhood search (VNS) and proposed to solve this NP-hard problem. Moreover, a novel coding method is devised to represent the complex structure of the LIRP problem. The input parameters are tuned using the Taguchi experimental design method, considering the sensitivity of meta-heuristic algorithms to these parameters. Through experiments of various scales, the hybrid MPGA with VNS indicates superior performance, as evidenced by the experimental results. Sensitivity analysis is conducted to examine the influence of key model parameters on the optimal objective, providing valuable management implications. The results clearly validate the efficacy of the proposed model and solution method as a reliable tool for optimizing the design problem of the PPSCN.

Suggested Citation

  • Lihong Pan & Miyuan Shan & Linfeng Li, 2023. "Optimizing Perishable Product Supply Chain Network Using Hybrid Metaheuristic Algorithms," Sustainability, MDPI, vol. 15(13), pages 1-21, July.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:13:p:10711-:d:1188910
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    References listed on IDEAS

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    1. Shiva Zandkarimkhani & Hassan Mina & Mehdi Biuki & Kannan Govindan, 2020. "A chance constrained fuzzy goal programming approach for perishable pharmaceutical supply chain network design," Annals of Operations Research, Springer, vol. 295(1), pages 425-452, December.
    2. Wu, Ting & Shen, Houcai & Zhu, Cheng, 2015. "A multi-period location model with transportation economies-of-scale and perishable inventory," International Journal of Production Economics, Elsevier, vol. 169(C), pages 343-349.
    3. Chunxiao Zhao & Junhua Chen & Xingchen Zhang & Zanyang Cui, 2022. "Solution of Multi-Crew Depots Railway Crew Scheduling Problems: The Chinese High-Speed Railway Case," Sustainability, MDPI, vol. 14(1), pages 1-18, January.
    4. Mark Ferguson & Michael E. Ketzenberg, 2006. "Information Sharing to Improve Retail Product Freshness of Perishables," Production and Operations Management, Production and Operations Management Society, vol. 15(1), pages 57-73, March.
    5. Ming Liu & Hao Tang & Yunfeng Wang & Ruixi Li & Yi Liu & Xin Liu & Yaqian Wang & Yiyang Wu & Yu Wu & Zhijun Sun, 2023. "Enhancing Food Supply Chain in Green Logistics with Multi-Level Processing Strategy under Disruptions," Sustainability, MDPI, vol. 15(2), pages 1-21, January.
    6. Ali Diabat & Tarek Abdallah & Tung Le, 2016. "A hybrid tabu search based heuristic for the periodic distribution inventory problem with perishable goods," Annals of Operations Research, Springer, vol. 242(2), pages 373-398, July.
    7. Lihua Liu & Lai Soon Lee & Hsin-Vonn Seow & Chuei Yee Chen, 2022. "Logistics Center Location-Inventory-Routing Problem Optimization: A Systematic Review Using PRISMA Method," Sustainability, MDPI, vol. 14(23), pages 1-39, November.
    8. Zhu, Stuart X. & Ursavas, Evrim, 2018. "Design and analysis of a satellite network with direct delivery in the pharmaceutical industry," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 116(C), pages 190-207.
    9. Zegordi, S.H. & Beheshti Nia, M.A., 2009. "A multi-population genetic algorithm for transportation scheduling," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 45(6), pages 946-959, November.
    10. Shoyab Ali & Annapurna Bhargava & Akash Saxena & Pavan Kumar, 2023. "A Hybrid Marine Predator Sine Cosine Algorithm for Parameter Selection of Hybrid Active Power Filter," Mathematics, MDPI, vol. 11(3), pages 1-25, January.
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    1. Weng Hoe Lam & Weng Siew Lam & Pei Fun Lee, 2024. "A Bibliometric Analysis of a Genetic Algorithm for Supply Chain Agility," Mathematics, MDPI, vol. 12(8), pages 1-22, April.
    2. Sina Abbasi & Maryam Moosivand & Ilias Vlachos & Mohammad Talooni, 2023. "Designing the Location–Routing Problem for a Cold Supply Chain Considering the COVID-19 Disaster," Sustainability, MDPI, vol. 15(21), pages 1-24, October.

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