基于文化基因算法的多供应商多零售商VMI问题研究

发布时间：2018-05-11 14:47

本文选题：多供应商 + 多零售商　；参考：《现代制造工程》2017年02期

【摘要】：针对多供应商-多零售商-单个中心仓库供应链背景下的供应商管理库存问题,考虑供应商、零售商以及中心仓库的订货量和订货频次的约束,构建了供应商管理库存问题总库存成本的数学模型;针对上述模型,采用文化基因算法进行求解,以总的库存成本最低为目标来求解供应商、零售商及中心仓库每年的订货频次和订货量。该算法将个体表示为VMI问题的解,建立问题和算法的映射关系;在全局搜索过程中,采用基于位置的交叉方式吸收最优个体的优秀基因;在局部搜索过程中,采用基于位置的变异方式产生一定规模的邻域基因个体。采用正交试验对算法的重要参数进行了优化配置,通过实例验证了算法的有效性。
[Abstract]:In view of the Vendor Management inventory problem in the context of multi-supplier, multi-retailer and single central warehouse supply chain, the constraints of order quantity and ordering frequency of supplier, retailer and central warehouse are considered. The mathematical model of total inventory cost of Vendor Management inventory problem is constructed, and the cultural genetic algorithm is used to solve the above model, and the minimum total inventory cost is taken as the goal to solve the problem. Annual order frequency and order volume for retailers and central warehouses. The algorithm represents the individual as the solution of the VMI problem and establishes the mapping relationship between the problem and the algorithm. In the global search process, the best genes of the optimal individual are absorbed by a location-based crossover approach. Location-based mutation was used to produce neighborhood gene individuals of a certain scale. The important parameters of the algorithm are optimized by orthogonal test, and the effectiveness of the algorithm is verified by an example.
【作者单位】：上海海事大学科学研究院物流研究中心;上海海事大学文理学院;北京科技大学机械工程学院;
【基金】：国家自然科学基金资助项目(71171129) 上海市科委科研计划项目(12510501600;14DZ2280200;14511107402)
【分类号】：F724.2;F274;TP301.6

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