Hybrid particle swarm optimization with chaotic search for solving integer and mixed integer programming problems  

作　　者：谭跃 谭冠政 邓曙光 

机构地区：[1]School of Information Science and Engineering,Central South University [2]School of Communication and Electronic Engineering,Hunan City University

出　　处：《Journal of Central South University》2014年第7期2731-2742,共12页中南大学学报（英文版）

基　　金：Projects(50275150,61173052) supported by the National Natural Science Foundation of China;Project(14FJ3112) supported by the Planned Science and Technology of Hunan Province,China;Project(14B033) supported by Scientific Research Fund Education Department of Hunan Province,China

摘　　要：A novel chaotic search method is proposed,and a hybrid algorithm combining particle swarm optimization(PSO) with this new method,called CLSPSO,is put forward to solve 14 integer and mixed integer programming problems.The performances of CLSPSO are compared with those of other five hybrid algorithms combining PSO with chaotic search methods.Experimental results indicate that in terms of robustness and final convergence speed,CLSPSO is better than other five algorithms in solving many of these problems.Furthermore,CLSPSO exhibits good performance in solving two high-dimensional problems,and it finds better solutions than the known ones.A performance index(PI) is introduced to fairly compare the above six algorithms,and the obtained values of(PI) in three cases demonstrate that CLSPSO is superior to all the other five algorithms under the same conditions.A novel chaotic search method is proposed,and a hybrid algorithm combining particle swarm optimization（PSO） with this new method,called CLSPSO,is put forward to solve 14 integer and mixed integer programming problems.The performances of CLSPSO are compared with those of other five hybrid algorithms combining PSO with chaotic search methods.Experimental results indicate that in terms of robustness and final convergence speed,CLSPSO is better than other five algorithms in solving many of these problems.Furthermore,CLSPSO exhibits good performance in solving two high-dimensional problems,and it finds better solutions than the known ones.A performance index（PI） is introduced to fairly compare the above six algorithms,and the obtained values of（PI） in three cases demonstrate that CLSPSO is superior to all the other five algorithms under the same conditions.

关 键 词：particle swarm optimization chaotic search integer programming problem mixed integer programming problem 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]