AN IMPROVED DYNAMICAL EVOLUTIONARY ALGORITHM BASED ON CHAOTIC
An improved dynamical evolutionary algorithm based on the chaotic is proposed for optimizing. The new algorithm makes full use of initial value sensitivity and track ergodicity of chaos, overcoming the disadvantage of big searching dead zone existed in conventional chaotic mutation model. To achieve high performance in optimizing, the chaotic search mechanism is embedded in the standard dynamical evolutionary algorithm adaptiveh/ to avoid the stagnancy of population and increase the speed of convergence. The method keeps balance between the global search and the local search. It has been compared with other methods. In comparison, the proposed method shows its superiority in convergence property and robustness. It is validated by the simulation results.
Dynamical evolutionary algorithm chaotic search optimization
YI JIANG LING WANG LI CHEN
The School of Computer, Wuhan University, Wuhan, China, 430072 The School of Computer Sci.and Tech., Wuhan University of Science and Technology City college, Wuhan, China,430083 The School of Computer Sci.and Tech., Wuhan University of Science and Technology, Wuhan, China, 4300
国际会议
2008 International Conference on Machine Learning and Cybernetics(2008机器学习与控制论国际会议)
昆明
英文
4085-4089
2008-07-12(万方平台首次上网日期,不代表论文的发表时间)