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A Stochastic Programming Approach with Improved Multi-Criteria Scenario-Based Solution Method for Sustainable Reverse Logistics Design of Waste Electrical and Electronic Equipment (WEEE)

Author

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  • Hao Yu

    (Department of Industrial Engineering, Faculty of Engineering Science and Technology, UiT—The Arctic University of Norway, Narvik 8505, Norway)

  • Wei Deng Solvang

    (Department of Industrial Engineering, Faculty of Engineering Science and Technology, UiT—The Arctic University of Norway, Narvik 8505, Norway)

Abstract

Today, the increased public concern about sustainable development and more stringent environmental regulations have become important driving forces for value recovery from end-of-life and end-of use products through reverse logistics. Waste electrical and electronic equipment (WEEE) contains both valuable components that need to be recycled and hazardous substances that have to be properly treated or disposed of, so the design of a reverse logistics system for sustainable treatment of WEEE is of paramount importance. This paper presents a stochastic mixed integer programming model for designing and planning a generic multi-source, multi-echelon, capacitated, and sustainable reverse logistics network for WEEE management under uncertainty. The model takes into account both economic efficiency and environmental impacts in decision-making, and the environmental impacts are evaluated in terms of carbon emissions. A multi-criteria two-stage scenario-based solution method is employed and further developed in this study for generating the optimal solution for the stochastic optimization problem. The proposed model and solution method are validated through a numerical experiment and sensitivity analyses presented later in this paper, and an analysis of the results is also given to provide a deep managerial insight into the application of the proposed stochastic optimization model.

Suggested Citation

  • Hao Yu & Wei Deng Solvang, 2016. "A Stochastic Programming Approach with Improved Multi-Criteria Scenario-Based Solution Method for Sustainable Reverse Logistics Design of Waste Electrical and Electronic Equipment (WEEE)," Sustainability, MDPI, vol. 8(12), pages 1-28, December.
    • Handle: RePEc:gam:jsusta:v:8:y:2016:i:12:p:1331-:d:85485
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    Cited by:

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    2. Govindan, Kannan & Gholizadeh, Hadi, 2021. "Robust network design for sustainable-resilient reverse logistics network using big data: A case study of end-of-life vehicles," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 149(C).
    3. Xichen Lyu & Yingying Xu & Dian Sun, 2021. "An Evolutionary Game Research on Cooperation Mode of the NEV Power Battery Recycling and Gradient Utilization Alliance in the Context of China’s NEV Power Battery Retired Tide," Sustainability, MDPI, vol. 13(8), pages 1-27, April.
    4. Van Engeland, Jens & Beliën, Jeroen & De Boeck, Liesje & De Jaeger, Simon, 2020. "Literature review: Strategic network optimization models in waste reverse supply chains," Omega, Elsevier, vol. 91(C).
    5. Yan Sun & Xinya Li & Xia Liang & Cevin Zhang, 2019. "A Bi-Objective Fuzzy Credibilistic Chance-Constrained Programming Approach for the Hazardous Materials Road-Rail Multimodal Routing Problem under Uncertainty and Sustainability," Sustainability, MDPI, vol. 11(9), pages 1-27, May.
    6. Monica Leba & Andreea Ionica & Raluca Dovleac & Remus Dobra, 2018. "Waste Management System for Batteries," Sustainability, MDPI, vol. 10(2), pages 1-16, January.
    7. Thi Yen Pham & Gi-Tae Yeo, 2018. "A Comparative Analysis Selecting the Transport Routes of Electronics Components from China to Vietnam," Sustainability, MDPI, vol. 10(7), pages 1-18, July.
    8. Vahid Azizi & Guiping Hu, 2021. "A Multi-Stage Stochastic Programming Model for the Multi-Echelon Multi-Period Reverse Logistics Problem," Sustainability, MDPI, vol. 13(24), pages 1-15, December.
    9. Hao Yu & Xu Sun & Wei Deng Solvang & Xu Zhao, 2020. "Reverse Logistics Network Design for Effective Management of Medical Waste in Epidemic Outbreaks: Insights from the Coronavirus Disease 2019 (COVID-19) Outbreak in Wuhan (China)," IJERPH, MDPI, vol. 17(5), pages 1-25, March.

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