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Robust Optimization for a Bi-Objective Green Closed-Loop Supply Chain with Heterogeneous Transportation System and Presorting Consideration

Author

Listed:
  • Essam Kaoud

    (Department of Mechanical Engineering, Toyohashi University of Technology, Toyohashi 441-8580, Japan)

  • Mohammad A. M. Abdel-Aal

    (Industrial and Systems Engineering Department, King Fahd University of Petroleum and Minerals, Dhahran 31261, Saudi Arabia
    Interdisciplinary Research Center of Smart Mobility and Logistics, King Fahd University of Petroleum and Minerals, Dhahran 31261, Saudi Arabia)

  • Tatsuhiko Sakaguchi

    (Department of Informatics, Faculty of Engineering, Kindai University, Higashi-Hiroshima 739-2116, Japan)

  • Naoki Uchiyama

    (Department of Mechanical Engineering, Toyohashi University of Technology, Toyohashi 441-8580, Japan)

Abstract

In this study, we propose a robust bi-objective optimization model of the green closed-loop supply chain network considering presorting, a heterogeneous transportation system, and carbon emissions. The proposed model is an uncertain bi-objective mixed-integer linear optimization model that maximizes profit and minimizes carbon emissions by considering uncertain costs, selling price, and carbon emissions. The robust optimization approach is implemented using the combined interval and polyhedral, “Interval+ Polyhedral,” uncertainty set to develop the robust counterpart of the proposed model. Robust Pareto optimal solutions are obtained using a lexicographic weighted Tchebycheff optimization approach of the bi-objective model. Intensive computational experiments are conducted and a robust Pareto optimal front is obtained with a probability guarantee that the constraints containing uncertain parameters are not violated (constraint satisfaction).

Suggested Citation

  • Essam Kaoud & Mohammad A. M. Abdel-Aal & Tatsuhiko Sakaguchi & Naoki Uchiyama, 2022. "Robust Optimization for a Bi-Objective Green Closed-Loop Supply Chain with Heterogeneous Transportation System and Presorting Consideration," Sustainability, MDPI, vol. 14(16), pages 1-23, August.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:16:p:10281-:d:891697
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    References listed on IDEAS

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    Cited by:

    1. Fang Xu & Mengfan Yan & Lun Wang & Shaojian Qu, 2022. "The Robust Emergency Medical Facilities Location-Allocation Models under Uncertain Environment: A Hybrid Approach," Sustainability, MDPI, vol. 15(1), pages 1-23, December.
    2. Prasit Kailomsom & Charoenchai Khompatraporn, 2023. "A Multi-Objective Optimization Model for Multi-Facility Decisions of Infectious Waste Transshipment and Disposal," Sustainability, MDPI, vol. 15(6), pages 1-16, March.

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