项目优化调度问题的求解新方法  

Improved PSO algorithm for project optimization scheduling

作　　者：王静莲[1] 刘弘[2] 杨文潮[1] 李少辉[2] 

机构地区：[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

出　　处：《计算机工程与应用》2008年第19期36-38,共3页Computer Engineering and Applications

基　　金：国家高技术研究发展计划(863)(the National High-Tech Research and Development Plan of China under Grant No.2003AA1Z2320);山东省科技公关计划(the Key Technologies R&D Program of Shandong Province,China under Grant No.2005GG4201009)

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。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 .

关 键 词：群体智能 微粒群算法 CSCW 进化算法 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]