Improved Particle Swarm Optimization Algorithm for Stochastic EOQ Models with Multi-Item and Multi-Storehouse

摘要：

A new economic order quantity (EOQ) model is developed for multi-item and multi-storehouse with limited funds, limited storage capacity and stochastic demand. The model is proved to be a nonlinear convex programming. For finding the optimal replenishment schedule, we design a new particle swarm optimization (PSO) algorithm that combines gradient acceleration and penalty functions. Comparing with the basic PSO and some other optimization algorithms, this improved algorithm adequately utilizes the gradient information and fitness values of objective function. Numerical results show that the improved PSO is feasible and can get better convergence efficiency and higher solution precision than the basic PSO and genetic algorithms.

关键词： particle swarm optimization stochastic EOQ multi-item multi-storehouse.

作者: Peixin Zhao Hong Wang Hongfeng Gao

作者单位: School of Management Shandong University Jinan,Shandong Province,China College of Finance Shandong Institute of Light Industry Jinan,Shandong Province,China The Automation Institute Shandong Academy of Sciences Jinan,Shandong Province,China

会议类型: 国际会议

会议名称: 2006 IEEE International Conference on Information Acquisition

会议地点: 山东威海

会议语种:英文

页码: 1047-1051

在线出版日期: 2006-08-20（万方平台首次上网日期，不代表论文的发表时间）