A computer based strategy design for automobile spare part logistics network optimization

Gao Yi, Lin Xinda, Wang Dong
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引用次数: 2

Abstract

This paper discusses the problem of the automobile spare part logistics warehouse network strategy, a quite important problem in logistics. On the basis of the integration of quantitative technology and qualitative technology, a mathematic model and algorithm of automobile spare part logistics network optimization are presented. In the quantitative analysis part we propose a novel hybrid approach through crossing over the PSO and GA, called hybrid PSO-GA based algorithm. Among the mixed algorithm, GA is embedded to solve the difficulties of updating the particles in the binary code system; the roulette algorithm is embedded to eliminate worse particles; SA is embed to control convergence of particles. Then in the qualitative part, we propose a selection model along with the AHP methodology that project selection would be easier and more accurate than before. In the end we apply the above approach in an automobile spare part logistics company. Computational simulation is carried out to evaluate the performance of the algorithm and the results show that this approach can indeed find effective solutions for the automobile spare part logistics optimization problem.
基于计算机的汽车备件物流网络优化策略设计
本文讨论了汽车零部件物流仓库网络化战略问题,这是物流领域一个非常重要的问题。在定量技术和定性技术相结合的基础上,提出了汽车零部件物流网络优化的数学模型和算法。在定量分析部分,我们提出了一种将粒子群算法与遗传算法相结合的混合算法,即基于混合粒子群算法的遗传算法。在混合算法中,嵌入遗传算法解决了二进制码系统中粒子更新困难的问题;嵌入轮盘赌算法,消除不良粒子;嵌入SA来控制粒子的收敛。然后,在定性部分,我们提出了一个选择模型,结合AHP方法,项目选择将比以前更容易和更准确。最后,将上述方法应用于某汽车零部件物流公司。通过计算仿真对算法的性能进行了评价,结果表明该方法确实可以为汽车零部件物流优化问题找到有效的解决方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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