Metaheuristic Computation: A Performance Perspective: 195 (Intelligent Systems Reference Library, 195) - Tapa dura

Libro 162 de 188: Intelligent Systems Reference Library

Cuevas, Erik; Camarena, Octavio; Diaz, Primitivo

 
9783030580995: Metaheuristic Computation: A Performance Perspective: 195 (Intelligent Systems Reference Library, 195)
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ISBN 10: 3030580997 ISBN 13: 9783030580995
Editorial: Springer, 2020

Sinopsis

This book is primarily intended for undergraduate and postgraduate students of Science, Electrical Engineering, or Computational Mathematics. Metaheuristic search methods are so numerous and varied in terms of design and potential applications; however, for such an abundant family of optimization techniques, there seems to be a question which needs to be answered: Which part of the design in a metaheuristic algorithm contributes more to its better performance? Several works that compare the performance among metaheuristic approaches have been reported in the literature. Nevertheless, they suffer from one of the following limitations: (A)Their conclusions are based on the performance of popular evolutionary approaches over a set of synthetic functions with exact solutions and well-known behaviors, without considering the application context or including recent developments.  (B) Their conclusions consider only the comparison of their final results which cannot evaluate the nature of a good or bad balance between exploration and exploitation. The objective of this book is to compare the performance of various metaheuristic techniques when they are faced with complex optimization problems extracted from different engineering domains. The material has been compiled from a teaching perspective.

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De la contraportada

This book is primarily intended for undergraduate and postgraduate students of Science, Electrical Engineering, or Computational Mathematics. Metaheuristic search methods are so numerous and varied in terms of design and potential applications; however, for such an abundant family of optimization techniques, there seems to be a question which needs to be answered: Which part of the design in a metaheuristic algorithm contributes more to its better performance? Several works that compare the performance among metaheuristic approaches have been reported in the literature. Nevertheless, they suffer from one of the following limitations: (A)Their conclusions are based on the performance of popular evolutionary approaches over a set of synthetic functions with exact solutions and well-known behaviors, without considering the application context or including recent developments.  (B) Their conclusions consider only the comparison of their final results which cannot evaluate the nature of a good or bad balance between exploration and exploitation. The objective of this book is to compare the performance of various metaheuristic techniques when they are faced with complex optimization problems extracted from different engineering domains. The material has been compiled from a teaching perspective.

"Sobre este título" puede pertenecer a otra edición de este libro.

Editorial
Springer
Año de publicación
2020
Idioma
Inglés
ISBN 10 
3030580997
ISBN 13 
9783030580995
Encuadernación
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Número de edición
1
Número de páginas
284
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Otras ediciones populares con el mismo título

9783030581022: Metaheuristic Computation: A Performance Perspective: 195 (Intelligent Systems Reference Library)

Edición Destacada

ISBN 10:  3030581020 ISBN 13:  9783030581022
Editorial: Springer, 2021
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