计算机工程与应用 ›› 2008, Vol. 44 ›› Issue (19): 36-38.

• 理论研究 • 上一篇    下一篇

项目优化调度问题的求解新方法

王静莲1,刘 弘2,杨文潮1,李少辉2   

  1. 1.鲁东大学 现代教育技术教学部,山东 烟台 264025
    2.山东师范大学 信息科学与工程学院,济南 250014
  • 收稿日期:2007-08-22 修回日期:2008-01-14 出版日期:2008-07-01 发布日期:2008-07-01
  • 通讯作者: 王静莲

Improved PSO algorithm for project optimization scheduling

WANG Jing-lian1,LIU Hong2,YANG Wen-chao1,LI Shao-hui2   

  1. 1.Teaching Department of Modern Education Technology of Ludong University,Yantai,Shandong 264025,China
    2.School of Information Management,Shandong Normal University,Ji’nan 250014,China
  • Received:2007-08-22 Revised:2008-01-14 Online:2008-07-01 Published:2008-07-01
  • Contact: WANG Jing-lian

摘要: 基于N维向量空间的数学表示,对标准PSO算法中速度和位置更新公式的符号及操作符进行了广义定义,进而提出了一种改进PSO算法;并将改进PSO算法应用于更具现实意义项目调度问题的求解。大量实验结果表明,该算法能有效求解的同时,其运行效率和解的性能也都优于相关算法。

关键词: 群体智能, 微粒群算法, CSCW, 进化算法

Abstract: Based on the N-dimensional vector’s description to problem solution,the paper has proposed the improved PSO algorithm by the way which is that the sign and the operation sign of the speed and the position renewal formula in the standard PSO algorithm have been redefined.Then the improved PSO is applied to solve the project optimization scheduling problem.The simulated experiments indicate the improved algorithm has better solution and the higher-performance characteristic than the genetic algorithms.

Key words: swarm intelligence, Particle Swarm Optimization algorithm(PSO), CSCW, evolutionary algorithm