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DOI:
计算机系统应用英文版:2013,22(2):138-141
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改进的自适应混沌差分进化算法
(辽宁工程技术大学, 电气与控制工程学院, 葫芦岛 125105)
Improved Adaptive Chaotic Differential Evolution Algorithm
(College of Electrical and Control Engineering, Liaoning Technical University, Huludao 125105, China)
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Received:August 04, 2012    Revised:September 23, 2012
中文摘要: 为了提高差分进化算法的寻优速度、克服启发式算法常见的早熟收敛问题, 提出一种基于帐篷映射(Tent)的自适应混沌嵌入式差分进化算法(CLSDE). 算法采用 Tent 映射生成的混沌序列来取代基本DE算法选择操作中的随机数, 充分利用了混沌运动的随机性、遍历性和规律性. 通过与混沌PSO算法与普通的DE算法比较, 测试函数仿真结果表明, 该算法具有良好的全局搜索能力, 寻优精度较高, 收敛速度快, 鲁棒性好.
Abstract:In order to improve the differential evolution algorithm for optimum speed and overcome the heuristic algorithm common premature convergence problem is proposed based on a Tent mapping (Tent) of adaptive chaotic embedded differential evolution algorithm (CLSDE). Tent mapping algorithm using of the generation of chaotic sequence to replace basic DE algorithm to select the operation of the random, and make full use of the chaotic motions of the randomness, ergodicity and regularity, so it can smooth out the problem of local precocious and rapid speed up its global convergence speed. Through the and chaos PSO algorithm and the ordinary DE comparison algorithm, the simulation results show that the new algorithm in the solution precision, stability and convergence borrows and good performance.
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基金项目:辽宁省高校优秀人才项(2008RC25); 辽宁省创新团队项目(LT2010047)
引用文本:
王涛,王焕.改进的自适应混沌差分进化算法.计算机系统应用,2013,22(2):138-141
WANG Tao,WANG Huan.Improved Adaptive Chaotic Differential Evolution Algorithm.COMPUTER SYSTEMS APPLICATIONS,2013,22(2):138-141