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

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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 examplesincluded in all sections. This book is for experts in Engineering and Applied Sciences, Natural and Formal Sciences, Economics, Humanities and Social Sciences.

Introduction to metaheuristic techniques and algorithms, biomimicry and nature-inspired algorithms with swarm intelligence and presents the basics of the algorithms Provides a guide of how to develop algorithms from nature-inspired systems and to solve real-life complex stochastic problems Includes a list of real-life problems, model development with solution procedure from classical techniques, metaheuristic, and swarm intelligence

Inhalt
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).- MothsFlame Optimization Algorithm.- Genetic Algorithm.- Artificial Neural Network.- Future of Nature Inspired Algorithm, Swarm and Computational Intelligence.<p

Weitere Informationen

  • Allgemeine Informationen
    • GTIN 09783030611101
    • Auflage 1st edition 2021
    • Sprache Englisch
    • Genre Allgemeines & Lexika
    • Lesemotiv Verstehen
    • Größe H241mm x B160mm x T17mm
    • Jahr 2020
    • EAN 9783030611101
    • Format Fester Einband
    • ISBN 3030611108
    • Veröffentlichung 14.11.2020
    • Titel Metaheuristic Optimization: Nature-Inspired Algorithms Swarm and Computational Intelligence, Theory and Applications
    • Autor Lagouge K. Tartibu , Modestus O. Okwu
    • Untertitel Studies in Computational Intelligence 927
    • Gewicht 477g
    • Herausgeber Springer International Publishing
    • Anzahl Seiten 204

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