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E-commerce warehouse layout optimization: systematic layout planning using a genetic algorithm

Author

Listed:
  • Xiulian Hu

    (Fuzhou University of International Studies and Trade
    Ming Chuan University
    Logistics Research Center of Fuzhou University)

  • Yi-Fei Chuang

    (Ming Chuan University)

Abstract

China has witnessed a rapid growth in e-commerce in recent years, particularly after the introduction of mobile Internet. The growth of logistics applications has led to the need for effective logistics operations. To facilitate this, the sorting efficiency of goods in a warehouse has to be high. As an important node connecting the central warehouse and the distribution website in the e-commerce supply chain, the warehouse belonging to an e-commerce business is crucial as the sorting efficiency of goods depends on the layout of the warehouse. The purpose of this article is to optimize the layout of e-commerce warehouses and improve sorting efficiency. First, the comprehensive interrelationship of functional areas is obtained employing a systematic layout planning method. Then, a nonlinear programming model is established. The objective function is constructed with the minimum total handling cost and the maximum comprehensive relationship. Finally, a genetic algorithm is used to solve the nonlinear programming model to obtain a scientific and reasonable e-commerce warehouse layout plan. The genetic algorithm is shown to have better convergence than particle swarm optimization and simulated annealing. After re-layout, the handling cost can be considerably reduced after optimization and the fitness function optimization rate is 39.25%. Our findings shed light on the facility layout decision of e-commerce warehouse, and reduce the material handling cost of the company and improve the picking efficiency.

Suggested Citation

  • Xiulian Hu & Yi-Fei Chuang, 2023. "E-commerce warehouse layout optimization: systematic layout planning using a genetic algorithm," Electronic Commerce Research, Springer, vol. 23(1), pages 97-114, March.
    • Handle: RePEc:spr:elcore:v:23:y:2023:i:1:d:10.1007_s10660-021-09521-9
    DOI: 10.1007/s10660-021-09521-9
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    References listed on IDEAS

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