國立高雄大學圖資館 |

Language: English

Back

New metaheuristic schemesmechanisms and applications /

Record Type:	Electronic resources : Monograph/item
Title/Author:	New metaheuristic schemesby Erik Cuevas, Daniel Zaldívar, Marco Pérez-Cisneros.
Reminder of title:	mechanisms and applications /
Author:	Cuevas, Erik.
other author:	Zaldívar, Daniel.
Published:	Cham :Springer Nature Switzerland :2024.
Description:	xiv, 268 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Metaheuristics.
Online resource:	https://doi.org/10.1007/978-3-031-45561-2
ISBN:	9783031455612$q(electronic bk.)

New metaheuristic schemesmechanisms and applications /
Cuevas, Erik.

New metaheuristic schemesmechanisms and applications /[electronic resource] :by Erik Cuevas, Daniel Zaldívar, Marco Pérez-Cisneros. - Cham :Springer Nature Switzerland :2024. - xiv, 268 p. :ill. (some col.), digital ;24 cm. - Intelligent systems reference library,v. 2461868-4408 ;. - Intelligent systems reference library ;v.24..

Introduction to Metaheuristic Schemes: Characteristics, Properties, and Importance in Solving Optimization Problems -- Exploring the potential of agent systems for metaheuristics -- Dynamic Multimodal Function Optimization: An Evolutionary-Mean Shift Approach -- Trajectory-Driven Metaheuristic Approach using a Second-Order model -- Collaborative Hybrid Grey Wolf Optimizer: Uniting Synchrony and Asynchrony -- Efficient Image Contrast Enhancement by using the Moth Swarm Algorithm.

Recently, novel metaheuristic techniques have emerged in response to the limitations of conventional approaches, leading to enhanced outcomes. These new methods introduce interesting mechanisms and innovative collaborative strategies that facilitate the efficient exploration and exploitation of extensive search spaces characterized by numerous dimensions. The objective of this book is to present advancements that discuss novel alternative metaheuristic developments that have demonstrated their effectiveness in tackling various complex problems. This book encompasses a variety of emerging metaheuristic methods and their practical applications. The content is presented from a teaching perspective, making it particularly suitable for undergraduate and postgraduate students in fields such as science, electrical engineering, and computational mathematics. The book aligns well with courses in artificial intelligence, electrical engineering, and evolutionary computation. Furthermore, the material offers valuable insights to researchers within the metaheuristic and engineering communities. Similarly, engineering practitioners unfamiliar with metaheuristic computation concepts will recognize the pragmatic value of the discussed techniques. These methods transcend mere theoretical tools that have been adapted to effectively address the significant real-world problems commonly encountered in engineering domains.

ISBN: 9783031455612$q(electronic bk.)

Standard No.: 10.1007/978-3-031-45561-2doiSubjects--Topical Terms:

757062
Metaheuristics.

LC Class. No.: QA76.9.A43

Dewey Class. No.: 005.1

New metaheuristic schemesmechanisms and applications /
LDR:03056nmm a2200361 a 4500 001 660861
003 DE-He213
005 20231106140838.0
006 m d
007 cr nn 008maaau
008 241106s2024 sz s 0 eng d
020 $a 9783031455612$q(electronic bk.)
020 $a 9783031455605$q(paper)
024 7 $a 10.1007/978-3-031-45561-2 $2 doi
035 $a 978-3-031-45561-2
040 $a GP $c GP
041 0 $a eng
050 4 $a QA76.9.A43
072 7 $a TJF $2 bicssc
072 7 $a GPFC $2 bicssc
072 7 $a TEC007000 $2 bisacsh
072 7 $a TJF $2 thema
072 7 $a GPFC $2 thema
082 0 4 $a 005.1 $2 23
090 $a QA76.9.A43 $b C965 2024
100 1 $a Cuevas, Erik. $3 737835
245 1 0 $a New metaheuristic schemes $h [electronic resource] : $b mechanisms and applications / $c by Erik Cuevas, Daniel Zaldívar, Marco Pérez-Cisneros.
260 $a Cham : $b Springer Nature Switzerland : $b Imprint: Springer, $c 2024.
300 $a xiv, 268 p. : $b ill. (some col.), digital ; $c 24 cm.
490 1 $a Intelligent systems reference library, $x 1868-4408 ; $v v. 246
505 0 $a Introduction to Metaheuristic Schemes: Characteristics, Properties, and Importance in Solving Optimization Problems -- Exploring the potential of agent systems for metaheuristics -- Dynamic Multimodal Function Optimization: An Evolutionary-Mean Shift Approach -- Trajectory-Driven Metaheuristic Approach using a Second-Order model -- Collaborative Hybrid Grey Wolf Optimizer: Uniting Synchrony and Asynchrony -- Efficient Image Contrast Enhancement by using the Moth Swarm Algorithm.
520 $a Recently, novel metaheuristic techniques have emerged in response to the limitations of conventional approaches, leading to enhanced outcomes. These new methods introduce interesting mechanisms and innovative collaborative strategies that facilitate the efficient exploration and exploitation of extensive search spaces characterized by numerous dimensions. The objective of this book is to present advancements that discuss novel alternative metaheuristic developments that have demonstrated their effectiveness in tackling various complex problems. This book encompasses a variety of emerging metaheuristic methods and their practical applications. The content is presented from a teaching perspective, making it particularly suitable for undergraduate and postgraduate students in fields such as science, electrical engineering, and computational mathematics. The book aligns well with courses in artificial intelligence, electrical engineering, and evolutionary computation. Furthermore, the material offers valuable insights to researchers within the metaheuristic and engineering communities. Similarly, engineering practitioners unfamiliar with metaheuristic computation concepts will recognize the pragmatic value of the discussed techniques. These methods transcend mere theoretical tools that have been adapted to effectively address the significant real-world problems commonly encountered in engineering domains.
650 0 $a Metaheuristics. $3 757062
650 1 4 $a Cyber-Physical Systems. $3 919034
650 2 4 $a Machine Learning. $3 833608
650 2 4 $a Artificial Intelligence. $3 212515
650 2 4 $a Computer Science. $3 212513
700 1 $a Zaldívar, Daniel. $3 972170
700 1 $a Pérez-Cisneros, Marco. $3 972171
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer Nature eBook
830 0 $a Intelligent systems reference library ; $v v.24. $3 558591
856 4 0 $u https://doi.org/10.1007/978-3-031-45561-2
950 $a Engineering (SpringerNature-11647)