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An Improved Particle Swarm Optimization for the Automobile Spare Part Warehouse Location Problem

Author

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  • Zhen Yaobao
  • Hu Ping
  • Yang Shu

Abstract

This paper deals with a real-life warehouse location problem, which is an automobile spare part warehouse location problem. Since the automobile spare part warehouse location problem is a very complex problem, particle swarm optimization is used and some improved strategies are proposed to improve the performance of this algorithm. At last, the computational results of the benchmark problems about warehouse location problems are used to examine the effectiveness of particle swarm optimization. Then the results of the real-life automobile spare part warehouse location problem also indicate that the improved particle swarm optimization is a feasible method to solve the warehouse location problem.

Suggested Citation

  • Zhen Yaobao & Hu Ping & Yang Shu, 2013. "An Improved Particle Swarm Optimization for the Automobile Spare Part Warehouse Location Problem," Mathematical Problems in Engineering, Hindawi, vol. 2013, pages 1-6, November.
    • Handle: RePEc:hin:jnlmpe:726194
    DOI: 10.1155/2013/726194
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    Cited by:

    1. Ao Lv & Baofeng Sun, 2022. "Multi-Objective Robust Optimization for the Sustainable Location-Inventory-Routing Problem of Auto Parts Supply Logistics," Mathematics, MDPI, vol. 10(16), pages 1-22, August.

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