摘要
混沌变异进化算法忽略了混沌规律性,未充分利用知识来提高算法的局部收敛能力.为此,借鉴文化算法的双层进化结构,在文化算法的进化引导函数中引入自适应混沌变异策略,提出一种自适应混沌文化算法.利用进化过程隐含知识控制变异尺度,使知识引导个体能跳出局部较优解,在保证种群多样性的同时,实现进化后期的精细搜索.仿真结果表明,该算法可以有效提高进化收敛速度,具有较好的计算稳定性.
In evolutionary algorithms with chaotic mutation, implicit knowledge and orderliness of chaos are not fully utilized to improve local convergence. An adaptive chaotic cultural algorithm is proposed by adopting dual strueture in cultural algorithm and adaptive chaotic mutaion in evolution induction funtions. Implicit knowledge extracted from evolution process is used to control mutation scale, which inducts individuals escaping from local best solutions. This strategy can ensure the diversity of population and exploitation in the latter evolution. Simulation results indicate that the algorithm can effectively improve the speed of convergence and has better computation stability.
出处
《控制与决策》
EI
CSCD
北大核心
2009年第4期514-519,共6页
Control and Decision
基金
国家自然科学基金项目(60805025)
国家863计划项目(2007AA12Z162)
中国博士后科学基金项目(2005037225)
