Metaheuristic optimization : nature-inspired algorithms swarm and computational intelligence, theory and applications / Modestus O. Okwu, Lagouge K. Tartibu.
Okwu, Modestus O., author.; Tartibu, Lagouge K., author.
2021
QA76.9.A43
Available Online

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Title Metaheuristic optimization : nature-inspired algorithms swarm and computational intelligence, theory and applications / Modestus O. Okwu, Lagouge K. Tartibu.
Author Okwu, Modestus O., author.
ISBN 9783030611118 (electronic bk.)
3030611116 (electronic bk.)
9783030611101
DOI https://doi.org/10.1007/978-3-030-61111-8
Published Cham : Springer, [2021]
Language English
Description 1 online resource (196 pages)
Item Number 10.1007/978-3-030-61111-8 doi
Call Number QA76.9.A43
Dewey Decimal Classification 006.3
Summary This book exemplifies how algorithms are developed by mimicking nature. Classical techniques for solving day-to-day problems is time-consuming and cannot address complex problems. Metaheuristic algorithms are nature-inspired optimization techniques for solving real-life complex problems. This book emphasizes the social behaviour of insects, animals and other natural entities, in terms of converging power and benefits. Major nature-inspired algorithms discussed in this book include the bee colony algorithm, ant colony algorithm, grey wolf optimization algorithm, whale optimization algorithm, firefly algorithm, bat algorithm, ant lion optimization algorithm, grasshopper optimization algorithm, butterfly optimization algorithm and others. The algorithms have been arranged in chapters to help readers gain better insight into nature-inspired systems and swarm intelligence. All the MATLAB codes have been provided in the appendices of the book to enable readers practice how to solve examples included in all sections. This book is for experts in Engineering and Applied Sciences, Natural and Formal Sciences, Economics, Humanities and Social Sciences.
Bibliography, etc. Note Includes bibliographical references.
Access Note Access limited to authorized users.
Digital File Characteristics text file
PDF
Source of Description Description based on print version record.
Added Author Tartibu, Lagouge K., author.
Series Studies in computational intelligence ; v. 927.
Available in Other Form Metaheuristic Optimization: Nature-Inspired Algorithms Swarm and Computational Intelligence, Theory and Applications.
Linked Resources Online Access
Record Appears in Online Resources > Ebooks
All Resources
Introduction To Optimization
Particle Swarm Optimisation
Artificial Bee Colony Algorithm
Ant Colony Algorithm
Grey Wolf Optimizer
Whale Optimization Algorithm
Bat Algorithm
Ant Lion Optimization Algorithm
Grasshopper Optimisation Algorithm (Goa)
Moths-Flame Optimization Algorithm
Genetic Algorithm
Artificial Neural Network
Future of Nature Inspired Algorithm, Swarm and Computational Intelligence.

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