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Metaheuristic Computation: A Performance Perspective

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Metaheuristic Computation: A Performance Perspective/ by Erik Cuevas, Primitivo Diaz, Octavio Camarena.
作者:	Cuevas, Erik.
其他作者:	Camarena, Octavio.
面頁冊數:	XIV, 269 p. 93 illus., 31 illus. in color.online resource. :
Contained By:	Springer Nature eBook
標題:	Artificial Intelligence. -
電子資源:	https://doi.org/10.1007/978-3-030-58100-8
ISBN:	9783030581008

Metaheuristic Computation: A Performance Perspective
Cuevas, Erik.

Metaheuristic Computation: A Performance Perspective[electronic resource] /by Erik Cuevas, Primitivo Diaz, Octavio Camarena. - 1st ed. 2021. - XIV, 269 p. 93 illus., 31 illus. in color.online resource. - Intelligent Systems Reference Library, 195 1868-4408 ;. - Intelligent Systems Reference Library,67.

Introductory concepts of metaheuristic computation -- Introductory concepts of metaheuristic computation -- A metaheuristic methodology based on fuzzy logic principles.

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.

ISBN: 9783030581008

Standard No.: 10.1007/978-3-030-58100-8doiSubjects--Topical Terms:

646849
Artificial Intelligence.

LC Class. No.: Q342

Dewey Class. No.: 006.3

Metaheuristic Computation: A Performance Perspective
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