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Fuzzy Bi-Objective Production-Distribution Planning Problem under the Carbon Emission Constraint

Author

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  • Ilkyeong Moon

    (Department of Industrial Engineering, Seoul National University, Seoul 08826, Korea)

  • Yoon Jea Jeong

    (Department of Industrial Engineering, Seoul National University, Seoul 08826, Korea)

  • Subrata Saha

    (Department of Industrial Engineering, Seoul National University, Seoul 08826, Korea)

Abstract

This study addresses the design of a four-stage production distribution system under a carbon emission constraint. The first stage contains a set of established retail outlets. The second stage consists of a set of possible distribution centers. The third stage is comprised of a set of manufacturing units. The final and fourth stage involves a set of suppliers. We propose a bi-objective optimization problem with a mixed-integer linear programming scheme for maximizing the total profits while minimizing the cumulative shortages in a multi-period planning horizon with inaccurate information on raw material resources. We also propose a two-phase approach to solve the proposed model and obtain a Pareto-optimal solution. The effectiveness of the solution method for obtaining the fuzzy efficient solution is demonstrated with computational experiments. Sensitivity analysis is used for examining the effect of the carbon emission constraint on the optimal decisions.

Suggested Citation

  • Ilkyeong Moon & Yoon Jea Jeong & Subrata Saha, 2016. "Fuzzy Bi-Objective Production-Distribution Planning Problem under the Carbon Emission Constraint," Sustainability, MDPI, vol. 8(8), pages 1-17, August.
    • Handle: RePEc:gam:jsusta:v:8:y:2016:i:8:p:798-:d:75904
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    References listed on IDEAS

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    2. Tapan Kumar Datta & Sayantan Datta & Adrijit Goswami, 2024. "A sustainable bi-objective inventory model with source-based emissions and plan-based green investments under inflation and the present value of money," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 34(1), pages 91-117.
    3. Sadok Turki & Stanislav Didukh & Christophe Sauvey & Nidhal Rezg, 2017. "Optimization and Analysis of a Manufacturing–Remanufacturing–Transport–Warehousing System within a Closed-Loop Supply Chain," Sustainability, MDPI, vol. 9(4), pages 1-20, April.
    4. Nielsen, Izabela Ewa & Saha, Subrata, 2018. "Procurement planning in a multi-period supply chain: An epiphany," Operations Research Perspectives, Elsevier, vol. 5(C), pages 383-398.
    5. Lotfi Hidri & Ali Alqahtani & Achraf Gazdar & Belgacem Ben Youssef, 2021. "Green Scheduling of Identical Parallel Machines with Release Date, Delivery Time and No-Idle Machine Constraints," Sustainability, MDPI, vol. 13(16), pages 1-30, August.
    6. Yunting Feng & Yong Geng & Ge Zhao & Mengya Li, 2022. "Carbon Emission Constraint Policy in an OEM and Outsourcing Remanufacturer Supply Chain with Consumer Preferences," IJERPH, MDPI, vol. 19(8), pages 1-16, April.
    7. Hong, Zhaofu & Chu, Chengbin & Zhang, Linda L. & Yu, Yugang, 2017. "Optimizing an emission trading scheme for local governments: A Stackelberg game model and hybrid algorithm," International Journal of Production Economics, Elsevier, vol. 193(C), pages 172-182.
    8. Yanjie Zhou & Gyu M. Lee, 2017. "A Lagrangian Relaxation-Based Solution Method for a Green Vehicle Routing Problem to Minimize Greenhouse Gas Emissions," Sustainability, MDPI, vol. 9(5), pages 1-17, May.
    9. Daiki Min & Kwanghun Chung, 2017. "A Joint Optimal Decision on Shipment Size and Carbon Reduction under Direct Shipment and Peddling Distribution Strategies," Sustainability, MDPI, vol. 9(11), pages 1-21, November.
    10. Soon-Kyo Lee & Seung Ho Yoo & Taesu Cheong, 2017. "Sustainable EOQ under Lead-Time Uncertainty and Multi-Modal Transport," Sustainability, MDPI, vol. 9(3), pages 1-22, March.

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