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Metaheuristic and evolutionary compu...

Malik, Hasmat.

Metaheuristic and evolutionary computationalgorithms and applications /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Metaheuristic and evolutionary computationedited by Hasmat Malik ... [et al.].
Reminder of title:	algorithms and applications /
other author:	Malik, Hasmat.
Published:	Singapore :Springer Singapore :2021.
Description:	xxix, 820 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Metaheuristics.
Online resource:	https://doi.org/10.1007/978-981-15-7571-6
ISBN:	9789811575716$q(electronic bk.)

Metaheuristic and evolutionary computationalgorithms and applications /
Metaheuristic and evolutionary computationalgorithms and applications /[electronic resource] :edited by Hasmat Malik ... [et al.]. - Singapore :Springer Singapore :2021. - xxix, 820 p. :ill., digital ;24 cm. - Studies in computational intelligence,v.9161860-949X ;. - Studies in computational intelligence ;v. 216..

Chapter 1. Introduction: Optimization and Metaheuristics Algorithms -- Chapter 2. Metaheuristics Paradigms for Renewable Energy Systems: Advances in Optimization Algorithms -- Chapter 3. Tackling Power Quality Issues using Metaheuristics -- Chapter 4. Meta-Heuristic application in Suppression of Noise -- Chapter 5. A review on Genetic Algorithm and its application in Power system Engineering -- Chapter 6. Different Variants of Particle Swarm Optimization Algorithms and its Application: A Review -- Chapter 7. Application of Metaheuristics in Power Electronics -- Chapter 8. Cuckoo Search Algorithm: A Review of Recent Variants and Engineering Applications -- Chapter 9. Energy Management System for Hybrid Energy System: Renewable Integration, modeling & optimization, control aspects and conceptual framework -- Chapter 10. Recent Advances and Application of Metaheuristic Algorithms: A survey (2014-2020)

This book addresses the principles and applications of metaheuristic approaches in engineering and related fields. The first part covers metaheuristics tools and techniques such as ant colony optimization and Tabu search, and their applications to several classes of optimization problems. In turn, the book's second part focuses on a wide variety of metaheuristics applications in engineering and/or the applied sciences, e.g. in smart grids and renewable energy. In addition, the simulation codes for the problems discussed are included in an appendix for ready reference. Intended for researchers aspiring to learn and apply metaheuristic techniques, and gathering contributions by prominent experts in the field, the book offers readers an essential introduction to metaheuristics, its theoretical aspects and applications.

ISBN: 9789811575716$q(electronic bk.)

Standard No.: 10.1007/978-981-15-7571-6doiSubjects--Topical Terms:

757062
Metaheuristics.

LC Class. No.: QA76.9.A43 / M47 2021

Dewey Class. No.: 005.13

Metaheuristic and evolutionary computationalgorithms and applications /
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505 0 $a Chapter 1. Introduction: Optimization and Metaheuristics Algorithms -- Chapter 2. Metaheuristics Paradigms for Renewable Energy Systems: Advances in Optimization Algorithms -- Chapter 3. Tackling Power Quality Issues using Metaheuristics -- Chapter 4. Meta-Heuristic application in Suppression of Noise -- Chapter 5. A review on Genetic Algorithm and its application in Power system Engineering -- Chapter 6. Different Variants of Particle Swarm Optimization Algorithms and its Application: A Review -- Chapter 7. Application of Metaheuristics in Power Electronics -- Chapter 8. Cuckoo Search Algorithm: A Review of Recent Variants and Engineering Applications -- Chapter 9. Energy Management System for Hybrid Energy System: Renewable Integration, modeling & optimization, control aspects and conceptual framework -- Chapter 10. Recent Advances and Application of Metaheuristic Algorithms: A survey (2014-2020)
520 $a This book addresses the principles and applications of metaheuristic approaches in engineering and related fields. The first part covers metaheuristics tools and techniques such as ant colony optimization and Tabu search, and their applications to several classes of optimization problems. In turn, the book's second part focuses on a wide variety of metaheuristics applications in engineering and/or the applied sciences, e.g. in smart grids and renewable energy. In addition, the simulation codes for the problems discussed are included in an appendix for ready reference. Intended for researchers aspiring to learn and apply metaheuristic techniques, and gathering contributions by prominent experts in the field, the book offers readers an essential introduction to metaheuristics, its theoretical aspects and applications.
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