Improved particle swarm optimization algorithm and its global convergence analysis
会议名称：《2010 Chinese Control and Decision Conference》
会议日期：2010年
学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 081104[工学-模式识别与智能系统] 08[工学] 0835[工学-软件工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）]
基 金：supported by the Natural Science Foundation of Jiangsu University of China under Grant 08KJD510011 Natural Science Foundation for Qualified Personnel of Jiangsu University of China under Grant 08JDG017 the Open Project of the National Key Laboratory of Industrial Control Technology in Zhejiang University under Grant ICT0910
关 键 词：Particle Swarm Optimization Global Optimization Global Convergence Analysis
摘 要：This paper proposed an novel improved particle swarm optimizer(PSO) algorithm with global convergence *** global optimum position is unpredictable,so a random solution is introduced to the improved PSO as the best solution(P) in the end of every *** novel search strategy enables the improved PSO to make use of the uncertain information,in addition to experience,to achieve better quahty *** proof shows the novel random search strategy enables the improved PSO to own the performance of global *** of well-known benchmarks used in evolutionary optimization methods are used to evaluate the performance of the improved *** experiments,we observe that the improved PSO significantly improves the PSO’s performance and performs better than the basic PSO and other recent variants of PSO.