通货膨胀下的联合库存选址模型研究

An Integrated Inventory-Location Model Under Inflation

研究了通货膨胀对涉及一个供应商、多个候选配送中心和零售商的三级分销网络设计的影响。不同于传统的联合库存选址模型,所研究的模型考虑了整个系统的相关成本的时间价值,其目标是使在一定的通货膨胀率下总的选址、运输和库存成本之和的现值最小。为此,建立了一个非线性的整数规划模型,该模型为无容量约束问题的扩展模型,属于NP-hard问题。提出了3种基于不同编码形式的遗传算法用于求解该模型,并通过不同规模的算例对3种算法进行了有效性的分析和对比。最后,通过对各算例的计算结果的分析,发现随着通货膨胀率的增长,为了使这个分析网络的总成本现值最小,需要增加建立的DC的数量。

Today, the growing inflation rate at home and abroad is tremendously influencing the world economy and the human＇s daily lives. A distribution network design problem under inflation was studied, involving a single supplier, a number of potential distribution centers and retailers. Different from the traditional inventory-location models, the time value of the related costs of the whole distribution network was considered. The goal of the model is to minimize the present value of total cost that includes location, transportation and inventory cost. This model as a nonlinear integer programming problem was formulated, which is an extension of uncapacitated facility location problem, so it is a NP-hard problem. Three genetic algorithms based on different coding forms are proposed. The effectiveness of these algorithms through different sizes of instances was analyzed. The results show that, for minimizing the present value of the total cost under the growing inflation rate, the optimal policy would need to increase the number of the built distribution centers.