%0 Journal Article
%T Novel constrained optimization genetic algorithm and its engineering applications<br>一种新的约束优化遗传算法及其工程应用
%A WU Hua-wei
%A CHEN Te-fang
%A HUANG Wei-ming
%A XU Bing
%A HU Chun-kai
%A <br>吴华伟
%A 陈特放
%A 黄伟明
%A 许　炳
%A 胡春凯
%J 计算机应用研究
%D 2013
%I 
%X This paper proposed a novel genetic algorithm to solve constrained optimization problems. It introduced the indivi-dual generation based on good-point-set method into the genetic algorithm initial step, which maintained the population diversity of the genetic algorithm. In the evolution process, it searched the decision space of a problem through the arithmetic crossover operator of feasible and infeasible solutions. In order to coordinate the exploitation and the exploration ability of the algorithm, it used Gaussian and Cauchy mutation operators to the feasible and infeasible subpopulation respectively. It tested several benchmark problems and two engineering design problems. The results show that the proposed method is an effective way for constrained optimization problems.
%K constrained optimization problem
%K genetic algorithm
%K arithmetic crossover
%K mutation<br>约束优化问题
%K 遗传算法
%K 算术交叉
%K 变异
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=51EFA6F8AD1002433B7533754DACF728&yid=FF7AA908D58E97FA&vid=340AC2BF8E7AB4FD&iid=0B39A22176CE99FB&sid=4C2B9916B58305BE&eid=0918129209B14F3E&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=10