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A closed-loop supply chain network design problem with integrated forward and reverse channel decisions

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  • Gopalakrishnan Easwaran
  • Halit Üster

Abstract

This article considers a multi-product closed-loop logistics network design problem with hybrid manufacturing/remanufacturing facilities and finite-capacity hybrid distribution/collection centers to serve a set of retail locations. First, a mixed integer linear program is presented that determines the optimal solution that characterizes facility locations, along with the integrated forward and reverse flows such that the total cost of facility location, processing, and transportation associated with forward and reverse flows in the network is minimized. Second, a solution method based on Benders' decomposition with strengthened Benders' cuts for improved computational efficiencies is devised. In addition to this method, an alternative formulation is presented and a new dual solution method for the associated Benders' decomposition to obtain a different set of strengthened Benders' cuts is developed. In the Benders' decomposition framework, the strengthened cuts obtained from original and alternative formulations simultaneously are used to obtain an improved efficiency. Computational results illustrating the performance of the solution algorithms in terms of both solution quality and time are presented. It is inferred that the simultaneous use of the strengthened cuts obtained using different formulations facilitates tighter bounds and improves computational efficiency of Benders' algorithm.

Suggested Citation

  • Gopalakrishnan Easwaran & Halit Üster, 2010. "A closed-loop supply chain network design problem with integrated forward and reverse channel decisions," IISE Transactions, Taylor & Francis Journals, vol. 42(11), pages 779-792.
    • Handle: RePEc:taf:uiiexx:v:42:y:2010:i:11:p:779-792
    DOI: 10.1080/0740817X.2010.504689
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    Citations

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    Cited by:

    1. He, Yuanjie, 2015. "Acquisition pricing and remanufacturing decisions in a closed-loop supply chain," International Journal of Production Economics, Elsevier, vol. 163(C), pages 48-60.
    2. Fu, Lingxian & Meng, Fanyong, 2020. "A human disease transmission inspired dynamic model for closed-loop supply chain management," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 134(C).
    3. Accorsi, Riccardo & Manzini, Riccardo & Pini, Chiara & Penazzi, Stefano, 2015. "On the design of closed-loop networks for product life cycle management: Economic, environmental and geography considerations," Journal of Transport Geography, Elsevier, vol. 48(C), pages 121-134.
    4. De, Manoranjan & Giri, B.C., 2020. "Modelling a closed-loop supply chain with a heterogeneous fleet under carbon emission reduction policy," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 133(C).
    5. Min Huang & Pengxing Yi & Tielin Shi & Lijun Guo, 2018. "A modal interval based method for dynamic decision model considering uncertain quality of used products in remanufacturing," Journal of Intelligent Manufacturing, Springer, vol. 29(4), pages 925-935, April.
    6. Ali Pedram & Shahryar Sorooshian & Freselam Mulubrhan & Afshin Abbaspour, 2023. "Incorporating Vehicle-Routing Problems into a Closed-Loop Supply Chain Network Using a Mixed-Integer Linear-Programming Model," Sustainability, MDPI, vol. 15(4), pages 1-24, February.
    7. Reddy, K. Nageswara & Kumar, Akhilesh & Choudhary, Alok & Cheng, T. C. Edwin, 2022. "Multi-period green reverse logistics network design: An improved Benders-decomposition-based heuristic approach," European Journal of Operational Research, Elsevier, vol. 303(2), pages 735-752.
    8. Zhi-Hai Zhang & Gemma Berenguer & Zuo-Jun (Max) Shen, 2015. "A Capacitated Facility Location Model with Bidirectional Flows," Transportation Science, INFORMS, vol. 49(1), pages 114-129, February.
    9. R.S. Rogulin, 2020. "Modeling of Promising Interaction Between a Timber Industry Enterprise and a Commodity Exchange in Russia," Journal of Applied Economic Research, Graduate School of Economics and Management, Ural Federal University, vol. 19(4), pages 489-511.
    10. S.A. Torabi & J. Namdar & S.M. Hatefi & F. Jolai, 2016. "An enhanced possibilistic programming approach for reliable closed-loop supply chain network design," International Journal of Production Research, Taylor & Francis Journals, vol. 54(5), pages 1358-1387, March.

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