摘要
为提高差分进化算法的局部搜索能力和避开罚函数方法中罚参数选择问题,提出一种混沌局部搜索策略的差分进化算法(CLSDE)用于解决非线性混合整数规划问题.CLSDE中,只对目标函数中的变量进行编码,约束条件函数中的变量随机产生,每代进化完毕后,对最优个体进行混沌局部搜索.6个基本的测试函数实验结果证明CLSDE比MIHDE具有较好的寻优能力.
In order to improve local search ability of differential evolution and avoid selecting penalty parameters of penalty function method, differential evolution algodthra with chaotic local search strategy （CLSDE） was proposed to solve mixed-integer nonlinear programming problems. In CLSDE, only variables in objective function are encoded, variables in constraint function are randomly generated, the best individual is executed by chaotic local search after each individual evolves one time per generation. Experiment re- suits on six basic test functions show that CLSDE had the better ability of finding optimal solution than that of MIHDE.
出处
《小型微型计算机系统》
CSCD
北大核心
2012年第6期1306-1309,共4页
Journal of Chinese Computer Systems
基金
国家自然科学基金项目(50275150)资助
湖南省科技计划项目(YK0812)资助
益阳市科技计划项目(2010JZ25)资助
关键词
差分进化
混沌局部搜索策略
混合整数非线性规划
罚函数
differential evolution （DE}
chaotic-local-search strategy
mixed-integer nonlinear programming
penalty function
