计算机工程与应用 ›› 2008, Vol. 44 ›› Issue (11): 229-231.

• 工程与应用 • 上一篇    下一篇

基于改进粒子群算法的立体仓库货位分配优化

陈月婷,何 芳   

  1. 济南大学 控制科学与工程学院,济南 250022
  • 收稿日期:2007-07-24 修回日期:2007-09-28 出版日期:2008-04-11 发布日期:2008-04-11
  • 通讯作者: 陈月婷

Location assignment optimization of AS/RS based on improved Particle Swarm Optimization

CHEN Yue-ting,HE Fang   

  1. School of Control Science and Engineering,University of Ji’nan,Ji’nan 250022,China
  • Received:2007-07-24 Revised:2007-09-28 Online:2008-04-11 Published:2008-04-11
  • Contact: CHEN Yue-ting

摘要: 研究自动化立体仓库固定货架的货位分配问题,货位分配综合考虑了货架的稳定性和出入库效率,建立了货位优化的数学模型,提出了基于Pareto最优解的改进粒子群算法(PSO)来解决此问题的方法。在优化过程中引用了置换的概念来计算粒子的速度,并且在算法中采用小生境技术提高非劣解集的分散性,用存档群体保存了非劣解。仿真实验证明,此优化策略可以有效地解决自动化立体仓库的货位分配问题。

关键词: 自动化立体仓库, 货位分配, 粒子群算法(PSO), 置换

Abstract: The goods location assignment of an automated warehouse is discussed in the paper.The stability of the shelf and the efficiency of the storage/retrieval operation are taken into account.The mathematic model is built to describe the problem of the location assignment optimization.Improved Particle Swarm Optimization(PSO)based on Pareto optimal solution is used to deal with the location assignment.In the process of optimization,the conception of permutation is adopted to calculate the velocity of the particles.Niche technique has been used to improve the diversity of non-inferior solutions.Archive is used to keep down all the non-inferior ones to the results.The simulation results indicate that it could be used to resolve the problem of the location assignment.

Key words: automated warehouse, location assignment, Particle Swarm Optimization(PSO), permutation