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An integrated robust optimisation approach to closed-loop supply chain network design under uncertainty: the case of the auto glass industry

Author

Listed:
  • Maryam Kolyaei
  • Adel Azar
  • Ali Rajabzadeh Ghatari
Abstract
In this paper, we propose an integrated model that has two stages. In the first stage, suppliers and subcontractors are evaluated with a fuzzy method based on proposed qualitative set of criteria. The outputs of this stage are utilised as the input of the next stage. In stage two, a multi-objective mixed-integer linear programming model is proposed considering four conflicting objectives. The model is developed using robust programming to investigate the effects of uncertainty in customer demand. The model is able to: 1) select the best suppliers and subcontractors based on established qualitative and quantitative criteria; 2) allocate orders to them; 3) determine the optimal number of parts and products in the network. To motivate the practical aspect of the model in real-world applications, we applied the model to an auto glass company. The results revealed that the model is cost-efficient for CLSC network designs and can control the supply chain uncertainties.

Suggested Citation

  • Maryam Kolyaei & Adel Azar & Ali Rajabzadeh Ghatari, 2023. "An integrated robust optimisation approach to closed-loop supply chain network design under uncertainty: the case of the auto glass industry," International Journal of Process Management and Benchmarking, Inderscience Enterprises Ltd, vol. 14(3), pages 285-310.
    • Handle: RePEc:ids:ijpmbe:v:14:y:2023:i:3:p:285-310
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    Cited by:

    1. Huanyong Zhang & Ningshu Li & Jinghan Lin, 2024. "Modeling the Decision and Coordination Mechanism of Power Battery Closed-Loop Supply Chain Using Markov Decision Processes," Sustainability, MDPI, vol. 16(11), pages 1-19, May.

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