基于粒子群迭代自组织数据分析算法的逆向物流库存管理

Inventory Management in Reverse Logistics Based on Integrated Particle Swarm Iterative Self-organizing Data Analysis Technique

将粒子群算法与迭代自组织数据分析算法(ISODATA)结合,提出了一种基于粒子群的ISODATA算法。新的算法继承了粒子群算法全局搜索能力强的特点和迭代自组织数据分析算法(ISODATA)易于收敛、稳定性强、对聚类有一定自主性的特点。仿真实验表明,利用该算法可以对逆向物流情况下的库存管理模式进行识别,可以对库存管理进行准确、实时的指导。

In this paper, by combining the particle swarm algorithm and the iterative self-organizing data analysis technique algorithm （ISODATA）, we proposed the ISODATA based on particle swarm, which inherited the strength of both algorithms and then, through a simulation, proved that this algorithm could be used to identify the inventory management modes in reverse logistics and instruct the inventory management in an accurate and real-time manner.