Self-Adaptive Heuristics for Evolutionary Computation 2024 pdf epub mobi 電子書 下載


Self-Adaptive Heuristics for Evolutionary Computation

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Evolutionary algorithms are successful biologically inspired meta-heuristics. Their success depends on adequate parameter settings. The question arises: how can evolutionary algorithms learn parameters automatically during the optimization? Evolution strategies gave an answer decades ago: self-adaptation. Their self-adaptive mutation control turned out to be exceptionally successful. But nevertheless self-adaptation has not achieved the attention it deserves. This book introduces various types of self-adaptive parameters for evolutionary computation. Biased mutation for evolution strategies is useful for constrained search spaces. Self-adaptive inversion mutation accelerates the search on combinatorial TSP-like problems. After the analysis of self-adaptive crossover operators the book concentrates on premature convergence of self-adaptive mutation control at the constraint boundary. Besides extensive experiments, statistical tests and some theoretical investigations enrich the analysis of the proposed concepts.

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發表於2024-11-09

Self-Adaptive Heuristics for Evolutionary Computation 2024 pdf epub mobi 電子書 下載

Self-Adaptive Heuristics for Evolutionary Computation 2024 pdf epub mobi 電子書 下載

Self-Adaptive Heuristics for Evolutionary Computation 2024 pdf epub mobi 電子書 下載



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出版者:
作者:Kramer, Oliver
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頁數:194
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價格:$ 179.67
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isbn號碼:9783540692805
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