Nature-Inspired Methods for Metaheuristics Optimization Algorithms and Applications in Science and Engineering
This book gathers together a set of chapters covering recent development in optimization methods that are inspired by nature. The first group of chapters describes in detail different meta-heuristic algorithms, and shows their applicability using some test or real-world problems. The second part of...
Other Authors: | , |
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Format: | eBook |
Language: | English |
Published: |
Cham
Springer International Publishing
2020, 2020
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Edition: | 1st ed. 2020 |
Series: | Modeling and Optimization in Science and Technologies
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Subjects: | |
Online Access: | |
Collection: | Springer eBooks 2005- - Collection details see MPG.ReNa |
Summary: | This book gathers together a set of chapters covering recent development in optimization methods that are inspired by nature. The first group of chapters describes in detail different meta-heuristic algorithms, and shows their applicability using some test or real-world problems. The second part of the book is especially focused on advanced applications and case studies. They span different engineering fields, including mechanical, electrical and civil engineering, and earth/environmental science, and covers topics such as robotics, water management, process optimization, among others. The book covers both basic concepts and advanced issues, offering a timely introduction to nature-inspired optimization method for newcomers and students, and a source of inspiration as well as important practical insights to engineers and researchers |
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Physical Description: | XIII, 502 p. 252 illus., 110 illus. in color online resource |
ISBN: | 9783030264581 |