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Metaheuristic computationa performan...

Camarena, Octavio.

Metaheuristic computationa performance perspective /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Metaheuristic computationby Erik Cuevas, Primitivo Diaz, Octavio Camarena.
Reminder of title:	a performance perspective /
Author:	Cuevas, Erik.
other author:	Diaz, Primitivo.
Published:	Cham :Springer International Publishing :2021.
Description:	xiv, 269 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Metaheuristics.
Online resource:	https://doi.org/10.1007/978-3-030-58100-8
ISBN:	9783030581008$q(electronic bk.)

Metaheuristic computationa performance perspective /
Cuevas, Erik.

Metaheuristic computationa performance perspective /[electronic resource] :by Erik Cuevas, Primitivo Diaz, Octavio Camarena. - Cham :Springer International Publishing :2021. - xiv, 269 p. :ill., digital ;24 cm. - Intelligent systems reference library,v.1951868-4394 ;. - Intelligent systems reference library ;v.24..

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$q(electronic bk.)

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

757062
Metaheuristics.

LC Class. No.: QA76.9.A43 / C84 2021

Dewey Class. No.: 005.1

Metaheuristic computationa performance perspective /
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505 0 $a Introductory concepts of metaheuristic computation -- Introductory concepts of metaheuristic computation -- A metaheuristic methodology based on fuzzy logic principles.
520 $a 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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