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Titlebook: Adaptive and Multilevel Metaheuristics; Carlos Cotta,Marc Sevaux,Kenneth S?rensen Book 2008 Springer-Verlag Berlin Heidelberg 2008 Layer.P

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發(fā)表于 2025-3-21 17:01:27 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
期刊全稱Adaptive and Multilevel Metaheuristics
影響因子2023Carlos Cotta,Marc Sevaux,Kenneth S?rensen
視頻videohttp://file.papertrans.cn/145/144774/144774.mp4
發(fā)行地址Presents recent results in Adaptive and Multilevel Metaheuristics
學(xué)科分類Studies in Computational Intelligence
圖書封面Titlebook: Adaptive and Multilevel Metaheuristics;  Carlos Cotta,Marc Sevaux,Kenneth S?rensen Book 2008 Springer-Verlag Berlin Heidelberg 2008 Layer.P
影響因子.One of the keystones in practical metaheuristic problem-solving is the fact that tuning the optimization technique to the problem under consideration is crucial for achieving top performance. This tuning/customization is usually in the hands of the algorithm designer, and despite some methodological attempts, it largely remains a scientific art. Transferring a part of this customization effort to the algorithm itself -endowing it with smart mechanisms to self-adapt to the problem- has been a long pursued goal in the field of metaheuristics...These mechanisms can involve different aspects of the algorithm, such as for example, self-adjusting the parameters, self-adapting the functioning of internal components, evolving search strategies, etc...Recently, the idea of hyperheuristics, i.e., using a metaheuristic layer for adapting the search by selectively using different low-level heuristics, has also been gaining popularity. This volume presents recent advances in the area of adaptativeness in metaheuristic optimization, including up-to-date reviews of hyperheuristics and self-adaptation in evolutionary algorithms, as well as cutting edge works on adaptive, self-adaptive and multile
Pindex Book 2008
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Teresa M. Buck,Jeffrey L. Brodsky any assumptions about the function to be optimized, apart from the availability of evaluations at selected test points. The main design criterion of the Reactive Affine Shaker (RASH) scheme consists of the adaptation of a search region by an affine transformation. The modification takes into accoun
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