Constraint handling in metaheuristics and applications / Anand J. Kulkarni, Efrén Mezura-Montes, Yong Wang, Amir H. Gandomi, Ganesh Krishnasamy, editors.
2021
QA76.9.A43
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Title
Constraint handling in metaheuristics and applications / Anand J. Kulkarni, Efrén Mezura-Montes, Yong Wang, Amir H. Gandomi, Ganesh Krishnasamy, editors.
ISBN
9789813367104 (electronic bk.)
9813367105 (electronic bk.)
9789813367098
9813367091
9813367105 (electronic bk.)
9789813367098
9813367091
Published
Singapore : Springer, [2021]
Language
English
Description
1 online resource (336 pages)
Item Number
10.1007/978-981-33-6710-4 doi
Call Number
QA76.9.A43
Dewey Decimal Classification
519.6
Summary
This book aims to discuss the core and underlying principles and analysis of the different constraint handling approaches. The main emphasis of the book is on providing an enriched literature on mathematical modelling of the test as well as real-world problems with constraints, and further development of generalized constraint handling techniques. These techniques may be incorporated in suitable metaheuristics providing a solid optimized solution to the problems and applications being addressed. The book comprises original contributions with an aim to develop and discuss generalized constraint handling approaches/techniques for the metaheuristics and/or the applications being addressed. A variety of novel as well as modified and hybridized techniques have been discussed in the book. The conceptual as well as the mathematical level in all the chapters is well within the grasp of the scientists as well as the undergraduate and graduate students from the engineering and computer science streams. The reader is encouraged to have basic knowledge of probability and mathematical analysis and optimization. The book also provides critical review of the contemporary constraint handling approaches. The contributions of the book may further help to explore new avenues leading towards multidisciplinary research discussions. This book is a complete reference for engineers, scientists, and students studying/working in the optimization, artificial intelligence (AI), or computational intelligence arena.
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Includes bibliographical references.
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Table of Contents
1. The Find-Fix-Finish-Exploit-Analyze (F3EA) meta-heuristic algorithm with an extended constraint handling technique for constrained optimization and engineering design
An improved Cohort Intelligence with Panoptic Learning Behavior for solving constrained problems
Nature-Inspired Metaheuristic Algorithms for Constraint Handling: Challenges, Issues and Research Perspective.
An improved Cohort Intelligence with Panoptic Learning Behavior for solving constrained problems
Nature-Inspired Metaheuristic Algorithms for Constraint Handling: Challenges, Issues and Research Perspective.