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Logistics network design for product recovery in fuzzy environment

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  • Qin, Zhongfeng
  • Ji, Xiaoyu

Abstract

The design of product recovery network is one of the important and challenging problems in the field of reverse logistics. Some models have been formatted by researchers under deterministic environment. However, uncertainty is inherent during the process of the practical product recovery. In order to deal with uncertainty, this paper employs a fuzzy programming tool to design the product recovery network. Based on different criteria, three types of optimization models are proposed and some properties of them are investigated. To solve the proposed models, we design a hybrid intelligent algorithm which integrates fuzzy simulation and genetic algorithm. Finally, several numerical examples are presented to illustrate the effectiveness of the proposed models and algorithm.

Suggested Citation

  • Qin, Zhongfeng & Ji, Xiaoyu, 2010. "Logistics network design for product recovery in fuzzy environment," European Journal of Operational Research, Elsevier, vol. 202(2), pages 479-490, April.
    • Handle: RePEc:eee:ejores:v:202:y:2010:i:2:p:479-490
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    References listed on IDEAS

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    3. 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.
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    8. Ayvaz, Berk & Bolat, Bersam & Aydın, Nezir, 2015. "Stochastic reverse logistics network design for waste of electrical and electronic equipment," Resources, Conservation & Recycling, Elsevier, vol. 104(PB), pages 391-404.
    9. Mohammed, Ahmed & Wang, Qian, 2017. "The fuzzy multi-objective distribution planner for a green meat supply chain," International Journal of Production Economics, Elsevier, vol. 184(C), pages 47-58.
    10. Sheikholeslami, Mahnaz & Zarrinpoor, Naeme, 2023. "Designing an integrated humanitarian logistics network for the preparedness and response phases under uncertainty," Socio-Economic Planning Sciences, Elsevier, vol. 86(C).
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