一种求解约束优化问题的改进差分进化算法  

An Improved Differential Evolution Algorithm for Solving Constraint Optimization Problem

作　　者：宁桂英[1] 曹敦虔[2] 周永权[3] NING Gui-ying CAO Dun-qian ZHOU Yong-quan(Lushan College of Guangxi University Science and Technology, Liuzhou 545616, China College of Science, Guangxi University for Nationalities, Nanning 530006, China College of Information Science and Engineering, Guangxi University for Nationalities, China)

机构地区：[1]广西科技大学鹿山学院,广西柳州545616 [2]广西民族大学理学院,广西南宁530006 [3]广西民族大学信息科学与工程学院,广西南宁530006

出　　处：《数学的实践与认识》2017年第2期155-165,共11页Mathematics in Practice and Theory

基　　金：国家自然科学基金(61165015);2015年度广西高校科学技术研究项目(KY2015YB521);2015年度广西教育厅科学研究项目(KY2015YB081)

摘　　要：针对在处理约束优化问题时约束条件难以处理的问题,提出了一种求解约束优化问题的改进差分进化算法.即在每代进化前将群体分为可行个体和不可行个体两类,对不可行个体,用差量法将其逐个转化为可行个体,并保持种群规模不变,经过一序列的进化后,计算所有可行个体的适应度并找到问题的最优解.对5个经典函数进行了优化测试,测试结果表明提出的算法对求解约束优化问题是有效的.Constraint conditions are difficult to handle in dealing with constrained optimization problems.According to this problem,an improved differential evolution algorithm for solving constraint optimization problem is proposed.That is,before each generation,the populations of each generation are divided into two categories：feasible individuals and infeasible individuals,for the infeasible individuals,each one will be transformed into feasible one with dispersion method and keep the population size.After a sequence of evolution,all the feasible individuals＇ fitness valves were calculated and found the optimum solution.And five classic functions were tested.Simulation results show that the proposed algorithm for solving constrained optimization problems is effective.

关 键 词：约束优化 差分进化 不可行个体 适应度 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]