| Modified evolutionary algorithm for global optimization |
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| 引用本文： | 郭崇慧,陆玉昌,唐焕文. Modified evolutionary algorithm for global optimization[J]. 系统工程与电子技术(英文版), 2004, 15(1) |
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| 作者姓名： | 郭崇慧 陆玉昌 唐焕文 |
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| 基金项目： | ThisprojectwassupportedbytheNational“973”Project (G19980 3 0 414 )andtheNationalNaturalScienceFoundationofChina(79990 5 80 ) . |
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| 摘 要： | 1 .INTRODUCTIONOptimization problemsoftenariseinscience ,engi neering ,andbusinessapplications .Tosolvevariousoptimizationproblems ,manysolutionsbasedonthegradientorhigher orderstatisticsoftheobjectivefunction ,suchassteepestdescentmethod ,conjugategradie…
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Modified evolutionary algorithm for global optimization |
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| Abstract: | A modification of evolutionary programming or evolution strategies for ndimensional global optimization is proposed. Based on the ergodicity and inherentrandomness of chaos, the main characteristic of the new algorithm which includes two phases is that chaotic behavior is exploited to conduct a rough search of the problem space in order to find the promising individuals in Phase I. Adjustment strategy of steplength and intensive searches in Phase II are employed. The population sequences generated by the algorithm asymptotically converge to global optimal solutions with probability one. The proposed algorithm is applied to several typical test problems. Numerical results illustrate that this algorithm can more efficiently solve complex global optimization problems than evolutionary programming and evolution strategies in most cases. |
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| Keywords: | global optimization evolutionary algorithms chaos search |
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