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Multimodal Optimization by Means of Evolutionary Algorithms

Language EnglishEnglish
Book Paperback
Book Multimodal Optimization by Means of Evolutionary Algorithms Mike Preuss
Libristo code: 21072375
Publishers Springer International Publishing AG, March 2019
This book offers the first comprehensive taxonomy for multimodal optimization algorithms, work with... Full description
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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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About the book

Full name Multimodal Optimization by Means of Evolutionary Algorithms
Author Mike Preuss
Language English
Binding Book - Paperback
Date of issue 2019
Number of pages 189
EAN 9783319791562
Libristo code 21072375
Weight 332
Dimensions 155 x 235 x 12
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