结合粒子群和单纯形的改进飞蛾优化算法  

Improved moth-flame optimization method based on combination of particle swarm optimization and simplex method

作　　者：赵东[1] 孙明玉 朱金龙 于繁华[1] 刘光洁[1] 陈慧灵 ZHAO Dong;SUN Ming-yu;ZHU Jin-long;YU Fan-hua;LIU Guang-jie;CHEN Hui-ling(College of Computer Science and Technology,Changchun Normal University,Changchun 130032,China;College of Mathematics and Electronic Information Engineering,Wenzhou University,Wenzhou 325035,China)

机构地区：[1]长春师范大学计算机科学与技术学院,长春130032 [2]温州大学数理与电子信息工程学院,浙江温州325035

出　　处：《吉林大学学报（工学版）》2018年第6期1867-1872,共6页Journal of Jilin University:Engineering and Technology Edition

基　　金：吉林省教育厅"十三五"科学技术研究项目(2016392);吉林省产业技术研究与开发专项项目(2017C301-2);吉林省科技厅重点科技研发项目(20180201086SF)

摘　　要：为提高飞蛾优化算法求解实际问题的能力,提出了一种基于单存形的混合飞蛾优化算法。该算法通过粒子群优化获取飞蛾的初始最优位置,使其具有更佳丰富的种群;同时,引入单存形方法获取最优解。通过与其他4种算法在10个函数上测试比较,结果表明:本文算法收敛速度及解的质量优于其他算法,具有更好的求解能力和优化性能,可作为问题优化的有效工具。In order to improve the ability of moth optimization algorithm in solving practical problems,a novel hybrid moth optimization algorithm based on single storage is proposed.The algorithm uses particle swarm optimization to obtain the initial optimal location of the moths,so that it has a better and richer population. The optimal solution is also obtained by the simplex method.The proposed algorithm is compared with other four kinds of algorithms by tests on ten functions.Experimental results show that the convergence speed and solution quality of the proposed algorithm are better than other algorithms,it has better solving and optimizing performance,and can be used as an effective optimization tool.

关 键 词：计算机应用 单纯形法 飞蛾优化算法 粒子群优化 函数优化 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]