【作者】 马明轩； 毛文涛； 范黎林； 郎祎平； 刘春红；

【Author】 Mingxuan Ma;Wendao Mao;Lilin Fan;Yiping Lang;Chunhong Liu;School of Computer and Information Engineering,Henan Normal University;

【机构】 河南师范大学计算机与信息工程学院；

【摘要】 库存优化是制造企业多级供应链管理中的重要手段。其中,如何有效协同各级仓储库存成本和跨地区调度效率,成为实现安全库存的关键。本文构建了一个由中心库、区域库和网点库构成的多级安全库存优化模型,在配件跨地区调货决策和故障配件返修的影响下制定模型中库存的最大订货量,并使用多目标遗传算法实现成本与运输距离的同时优化。仿真实验结果表明,相比较只考虑成本和距离的库存优化模型,本文所提模型可同时兼顾成本和距离,更适合解决跨地区的复杂库存优化问题。更多还原

【Abstract】 Inventory optimization is generally viewed as a vital step in multi-level inventory collaboration of manufacturing enterprises. How to effectively collaborate storage costs of all levels and the efficiency of cross-regional scheduling has become the key to achieve safe inventory. In this paper, a multi-level safe inventory optimization model is constructed for an inventory network with central, regional and node storages. This model can determine the maximum order quantity of inventory by considering the impact of cross-regional relocation decision and defective parts repair simultaneously. Moreover, this model uses a multi-objective genetic algorithm to achieve optimization on cost and transportation distance. A simulational experiment is conducted. The results show that, compared with the inventory optimization model that only considers cost and distance respectively, the proposed model can take both cost and distance into consideration, and is more suitable for solving complex cross-regional inventory optimization problems.更多还原