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Enterprise logistics Network Optimization Based on Genetic Algorithm

机译:基于遗传算法的企业物流网络优化

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After the enterprise has developed to a certain scale, its logistics and supply chains will become more complex. For example, tobacco logistics network optimization of construction can effectively connect all websites of tobacco production, processing, and management. It can also promote lowest logistic cost and the highest efficiency. For building the best tobacco logistics networks, we need to set a scientific logistics nodes. This article established a mathematical model of a logistics network optimization according to existing logistics network system of a tobacco company and geographical characteristics. With the goal of total cost least in logistics system, the models builder up mathematical models which are based on the distance between each distribution center and each point of sales, unit freight, and shipment of each distribution center, in addition to the delivery requirements quantity of each point of sales. It discusses the design and implementation about the logistics network optimization based on genetic algorithm. Finally, it depthly analysised and verified the model and the solutions through cases.
机译:企业发展到一定规模后,其物流和供应链将变得更加复杂。例如,烟草物流网络优化建筑能够有效地连接烟草生产,加工和管理的所有网站。它还可以促进最低的逻辑成本和最高效率。为建立最佳烟草物流网络,我们需要设置科学物流节点。本文根据烟草公司的现有物流网络系统和地理特征建立了物流网络优化的数学模型。在物流系统中的总成本中的目标,模型构建数学模型,基于每个分销中心和每个销售点的距离,单位货运和每个配送中心的运输,以及交货需求量每个销售点。基于遗传算法的物流网络优化探讨了设计与实现。最后,它通过案例进行深度分析和验证了模型和解决方案。

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