Multimodal Optimization by Means of Evolutionary Algorithms (häftad)
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Format
Häftad (Paperback / softback)
Språk
Engelska
Antal sidor
189
Utgivningsdatum
2019-03-14
Upplaga
Softcover reprint of the original 1st ed. 2015
Förlag
Springer International Publishing AG
Illustrationer
5 Illustrations, color; 37 Illustrations, black and white; XX, 189 p. 42 illus., 5 illus. in color.
Dimensioner
234 x 156 x 11 mm
Vikt
304 g
Antal komponenter
1
Komponenter
1 Paperback / softback
ISBN
9783319791562

Multimodal Optimization by Means of Evolutionary Algorithms

av Mike Preuss
Häftad,  Engelska, 2019-03-14
1113
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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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It provides an excellent explanation of the theoretical background of many topics in evolutionary computation . I strongly recommend this book for graduate students or any researcher who wants to work in the EC field . It also may help in improving some algorithms and may motivate the researcher to introduce new ones. the chapters are self-contained so that you can read individual chapters that you are interested in without the need to read the whole book. (Nailah Al-Madi, Genetic Programming and Evolvable Machines, Vol. 17 (3), September, 2016)

Övrig information

Dr. Mike Preuss got his Ph.D. in the Technische Universitt Dortmund and he is now a researcher at the Westflische Wilhelms-Universitt Mnster. He has published in the leading journals and conferences on various aspects of computational intelligence, in particular evolutionary computing, heuristics, search and multicriteria optimization and served on many of the key academic conference committees, journal boards and review committees in this field. He is a leading figure in the application of computational and artificial intelligence to games.

Innehållsförteckning

Introduction: Towards Multimodal Optimization.- Experimentation in Evolutionary Computation.- Groundwork for Niching.- Nearest-Better Clustering.- Niching Methods and Multimodal Optimization Performance.- Nearest-Better Based Niching.

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