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Multimodal Optimization by Means of Evolutionary Algorithms

Autor: Mike Preuss

Jazyk:

Väzba: Brožovaná

Vydavateľ: Springer International Publishing AG

Dostupnosť: Skladom u dodávateľa

Odosielame za 5-8 dní

99.73 €

This book offers the first comprehensive taxonomy for multimodal optimization algorithms, work with...

Informácie o knihe

Autor

Mike Preuss

Jazyk

Angličtina

Väzba

Kniha - Brožovaná

Vydalo

2019

Stránok

189

EAN

9783319791562

Enbook ID

21072375

Vydavateľ

Springer International Publishing AG

Hmotnosť

332

Rozmery

155 x 235 x 12

Kompletný popis

This book offers the first comprehensive taxonomy for multimodal optimization algorithms, work with its root in topics such as niching, parallel evolutionary algorithms, and global optimization. The author explains niching in evolutionary algorithms and its benefits; he examines their suitability for use as diagnostic tools for experimental analysis, especially for detecting problem (type) properties; and he measures and compares the performances of niching and canonical EAs using different benchmark test problem sets. His work consolidates the recent successes in this domain, presenting and explaining use cases, algorithms, and performance measures, with a focus throughout on the goals of the optimization processes and a deep understanding of the algorithms used. The book will be useful for researchers and practitioners in the area of computational intelligence, particularly those engaged with heuristic search, multimodal optimization, evolutionary computing, and experimental analysis.

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Multimodal Optimization by Means of Evolutionary Algorithms

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