求解互补问题的改进粒子群算法研究  

An improved particle swarm optimization algorithm for solving complementary problems

作　　者：刘铭 董立娇 王秀玉 LIU Ming;DONG Li-jiao;WANG Xiu-yu(School of Mathematics and Statistics,Changchun University of Technology,Changchun 130012,China)

机构地区：[1]长春工业大学数学与统计学院,吉林长春130012

出　　处：《东北师大学报（自然科学版）》2018年第4期43-47,共5页Journal of Northeast Normal University(Natural Science Edition)

基　　金：国家自然科学基金资助项目(61272207;11226335)

摘　　要：对互补问题进行了研究.将改进粒子群算法与凝聚函数相结合,并选取适当函数作为适应度函数,从而改进了粒子群算法.数值计算结果表明,改进的粒子群算法在求解互补问题时收敛速度更快、准确率更高,是求解互补问题的一种有效的优化算法.The complementarity problem is studied by combining the improved particle swarm optimization algorithm with the cohesive function and choosing the appropriate function as the fitness function and then applying the improved particle swarm optimization algorithm to calculate.The numerical results show that the improved particle swarm algorithm has high convergence rate and high accuracy when solving complementary problems,which is an effective optimization algorithm to solve the complementary problem.

关 键 词：互补问题 凝聚函数 改进粒子群算法 

分 类 号：O221[理学—运筹学与控制论]