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An Improved Differential Evolution Algorithm for a Multicommodity Location-Inventory Problem with False Failure Returns

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Listed:
  • Congdong Li
  • Hao Guo
  • Ying Zhang
  • Shuai Deng
  • Yu Wang

Abstract

Customer returns are a common phenomenon in many industries, and they have a significant impact on business organizations and their supply chains. False failure returns are returned products that have no functional or cosmetic defects, and they represent a large body of customer returns in practice. In this paper, we develop a mixed-integer nonlinear programming model to study a multicommodity location-inventory problem in a forward-reverse logistics network. This model minimizes the total cost in this network by considering false failure returns, and it also considers many real-world business scenarios in forward and reverse logistics flows. Moreover, we design a new heuristic approach to solve the model efficiently. Finally, numerical experiments are conducted to validate our solution approach and provide meaningful managerial insights.

Suggested Citation

  • Congdong Li & Hao Guo & Ying Zhang & Shuai Deng & Yu Wang, 2018. "An Improved Differential Evolution Algorithm for a Multicommodity Location-Inventory Problem with False Failure Returns," Complexity, Hindawi, vol. 2018, pages 1-13, October.
    • Handle: RePEc:hin:complx:1967398
    DOI: 10.1155/2018/1967398
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    References listed on IDEAS

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