Electronic Resource

Metaheuristic Optimization: Nature-Inspired Algorithms Swarm and Computational Intelligence, Theory and Applications

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Penilaian

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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.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
1908001252	EB0001858	006.3 Okw m	Central Library (OPAC)	Available

Detail Information

Series Title

Studies in Computational Intelligence

Call Number

006.3 Okw m

Publisher

Switzerland : Springer Cham., 2020

Collation

xii, 192p.:Ill

Language

English

ISBN/ISSN

978-3-030-61111-8

Classification

006.3

Content Type

Ebook

Media Type

-

Carrier Type

online resource

Edition

1

Subject(s)

Computational Intelligence

Specific Detail Info

-

Statement of Responsibility

BRF

Other version/related

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