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Designing a reverse logistics network for optimal collection, recovery and quality-based product-mix planning

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  • Das, Kanchan
  • Chowdhury, Abdul H.

Abstract

This study proposes an integrated, reverse logistics supply chain planning process with modular product design that produces and markets products at different quality levels. A mixed integer programming (MIP) model formulates the overall planning process required to maximize profit by considering the collection of returned products, the recovery of modules and the proportion of the product mix at different quality levels. This paper proposes the collection of returnables (end-of life, defective, product under warranty) through retail outlets combined with the recovery of modules from the collected products using a network of recovery service providers. The proposed modular product design approach would create a design criterion that provides an improved recovery process at a lower cost. This study uses a total supply chain view that considers the production, transportation and distribution of products to customers, while a numerical problem illustrates the applicability of the models.

Suggested Citation

  • Das, Kanchan & Chowdhury, Abdul H., 2012. "Designing a reverse logistics network for optimal collection, recovery and quality-based product-mix planning," International Journal of Production Economics, Elsevier, vol. 135(1), pages 209-221.
    • Handle: RePEc:eee:proeco:v:135:y:2012:i:1:p:209-221
    DOI: 10.1016/j.ijpe.2011.07.010
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    4. Niknejad, A. & Petrovic, D., 2014. "Optimisation of integrated reverse logistics networks with different product recovery routes," European Journal of Operational Research, Elsevier, vol. 238(1), pages 143-154.
    5. Wang, Wenyuan & Wang, Yue & Mo, Daniel & Tseng, Mitchell M., 2017. "Managing component reuse in remanufacturing under product diffusion dynamics," International Journal of Production Economics, Elsevier, vol. 183(PB), pages 551-560.
    6. Diabat, Ali & Kannan, Devika & Kaliyan, Mathiyazhagan & Svetinovic, Davor, 2013. "An optimization model for product returns using genetic algorithms and artificial immune system," Resources, Conservation & Recycling, Elsevier, vol. 74(C), pages 156-169.
    7. Govindan, Kannan & Soleimani, Hamed & Kannan, Devika, 2015. "Reverse logistics and closed-loop supply chain: A comprehensive review to explore the future," European Journal of Operational Research, Elsevier, vol. 240(3), pages 603-626.
    8. Zhang, Qinhong & Segerstedt, Anders & Tsao, Yu-Chung & Liu, Biyu, 2015. "Returnable packaging management in automotive parts logistics: Dedicated mode and shared mode," International Journal of Production Economics, Elsevier, vol. 168(C), pages 234-244.
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    11. Heydari, Jafar & Govindan, Kannan & Sadeghi, Razieh, 2018. "Reverse supply chain coordination under stochastic remanufacturing capacity," International Journal of Production Economics, Elsevier, vol. 202(C), pages 1-11.
    12. Pokharel, Shaligram & Liang, Yijiong, 2012. "A model to evaluate acquisition price and quantity of used products for remanufacturing," International Journal of Production Economics, Elsevier, vol. 138(1), pages 170-176.
    13. Sgarbossa, Fabio & Russo, Ivan, 2017. "A proactive model in sustainable food supply chain: Insight from a case study," International Journal of Production Economics, Elsevier, vol. 183(PB), pages 596-606.
    14. Muneeb, Syed Mohd & Asim, Zainab & Hajiaghaei-Keshteli, Mostafa & Abbas, Haidar, 2023. "A multi-objective integrated supplier selection-production-distribution model for re-furbished products: Towards a circular economy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 175(C).
    15. Lai, Kee-hung & Wu, Sarah J. & Wong, Christina W.Y., 2013. "Did reverse logistics practices hit the triple bottom line of Chinese manufacturers?," International Journal of Production Economics, Elsevier, vol. 146(1), pages 106-117.
    16. Accorsi, Riccardo & Cascini, Alessandro & Cholette, Susan & Manzini, Riccardo & Mora, Cristina, 2014. "Economic and environmental assessment of reusable plastic containers: A food catering supply chain case study," International Journal of Production Economics, Elsevier, vol. 152(C), pages 88-101.
    17. Taleizadeh, Ata Allah & Sadeghi, Razieh, 2019. "Pricing strategies in the competitive reverse supply chains with traditional and e-channels: A game theoretic approach," International Journal of Production Economics, Elsevier, vol. 215(C), pages 48-60.
    18. Ye, Fei & Zhao, Xiande & Prahinski, Carol & Li, Yina, 2013. "The impact of institutional pressures, top managers' posture and reverse logistics on performance—Evidence from China," International Journal of Production Economics, Elsevier, vol. 143(1), pages 132-143.
    19. Mirzabeiki, Vahid & Saghiri, Soroosh Sam, 2020. "From ambition to action: How to achieve integration in omni-channel?," Journal of Business Research, Elsevier, vol. 110(C), pages 1-11.
    20. Agrawal, Saurabh & Singh, Rajesh K. & Murtaza, Qasim, 2015. "A literature review and perspectives in reverse logistics," Resources, Conservation & Recycling, Elsevier, vol. 97(C), pages 76-92.
    21. Chou, Yon-Chun & Lin, Yue-Lan & Chun, King-Fai, 2014. "A construction of knowledge rules for reactive planning of job-mix assignment to homogeneous serial batch machines," International Journal of Production Economics, Elsevier, vol. 151(C), pages 56-66.
    22. Wiegand, Nico & Imschloss, Monika, 2021. "Do You Like What You (Can't) See? The Differential Effects of Hardware and Software Upgrades on High-Tech Product Evaluations," Journal of Interactive Marketing, Elsevier, vol. 56(C), pages 18-40.

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