Description: Metaheuristic Optimization : Nature-inspired Algorithms and Swarm Intelligence, Theory and Applications, Hardcover by Okwu, Modestus O.; Tartibu, Lagouge K., ISBN 3030611108, ISBN-13 9783030611101, Like New Used, Free P&P in the UK 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 th 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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Book Title: Metaheuristic Optimization : Nature-inspired Algorithms and Swarm
Number of Pages: 192 Pages
Language: English
Publication Name: Metaheuristic Optimization: Nature-Inspired Algorithms Swarm and Computational Intelligence, Theory and Applications
Publisher: Springer Nature Switzerland A&G
Publication Year: 2020
Subject: Computer Science
Item Height: 235 mm
Item Weight: 477 g
Type: Textbook
Author: Lagouge K. Tartibu, Modestus O. Okwu
Series: Studies in Computational Intelligence
Item Width: 155 mm
Format: Hardcover
