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A multi-objective integrated optimisation model for facility location and order allocation problem in a two-level supply chain network

Author

Listed:
  • Hamzeh Amin-Tahmasbi

    (East of Guilan, University of Guilan)

  • Sina Sadafi

    (University of Koshar)

  • Banu Y. Ekren

    (Yasar University, Department of Industrial Engineering
    Cranfield University, School of Management)

  • Vikas Kumar

    (Bristol Business School, University of the West of England)

Abstract

This study proposes a mixed-integer multi-objective integrated mathematical model solving facility location and order allocation optimisation problems simultaneously in a two-echelon supply chain network. The proposed problem is motivated by a factoryless concept and by providing a dynamic decision-making solution under a multi-period time horizon. Within the model, we also determine the optimal replenishment number of production facilities by the multi-objective functions. The multi-objective functions include minimisation of the total cost, rejected and late delivery units and, maximisation of the assessment score of the selected suppliers. The studied dynamic decision model is significant for the cost-efficient management of companies’ supply chain networks. The mixed-integer mathematical model is developed by the LP-metric method and it is solved by the GAMS optimisation software. Due to the NP-hard structure of the problem, for large-scale instances, we utilise the Multi-Objective Particle Swarm Optimisation (MOPSO) and Multi-Objective Vibration Damping Optimisation (MOVDO) heuristic solution approaches. Numerical results show that, for large-scale problems, the MOPSO method performs better in Pareto solutions and decreases run times. However, the MOVDO method performs better regarding the Mean Ideal Distance and the Number of Solutions Cover surface criterion. The developed solution approach by this paper is a generic model which can be applied for any two-level network for simultaneous optimisation of supplier selection, location determination of facilities and their replenishment amounts.

Suggested Citation

  • Hamzeh Amin-Tahmasbi & Sina Sadafi & Banu Y. Ekren & Vikas Kumar, 2023. "A multi-objective integrated optimisation model for facility location and order allocation problem in a two-level supply chain network," Annals of Operations Research, Springer, vol. 324(1), pages 993-1022, May.
    • Handle: RePEc:spr:annopr:v:324:y:2023:i:1:d:10.1007_s10479-022-04635-1
    DOI: 10.1007/s10479-022-04635-1
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    References listed on IDEAS

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    1. Mohammed, Ahmed & Harris, Irina & Govindan, Kannan, 2019. "A hybrid MCDM-FMOO approach for sustainable supplier selection and order allocation," International Journal of Production Economics, Elsevier, vol. 217(C), pages 171-184.
    2. Mohammad Saeid Atabaki & Mohammad Mohammadi & Bahman Naderi, 2017. "Hybrid Genetic Algorithm and Invasive Weed Optimization via Priority Based Encoding for Location-Allocation Decisions in a Three-Stage Supply Chain," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 34(02), pages 1-44, April.
    3. Feng, Bo & Fan, Zhi-Ping & Li, Yanzhi, 2011. "A decision method for supplier selection in multi-service outsourcing," International Journal of Production Economics, Elsevier, vol. 132(2), pages 240-250, August.
    4. Melo, M.T. & Nickel, S. & Saldanha-da-Gama, F., 2009. "Facility location and supply chain management - A review," European Journal of Operational Research, Elsevier, vol. 196(2), pages 401-412, July.
    5. Vincent F. Yu & Nur Mayke Eka Normasari & Huynh Trung Luong, 2015. "Integrated Location-Production-Distribution Planning in a Multiproducts Supply Chain Network Design Model," Mathematical Problems in Engineering, Hindawi, vol. 2015, pages 1-13, March.
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