Introduction to Nature-Inspired Optimization

Author:   George Lindfield (Professor, School of Engineering and Applied Science, Aston University) ,  John Penny (Professor, School of Engineering and Applied Science, Aston University)
Publisher:   Elsevier Science Publishing Co Inc
ISBN:  

9780128036365


Pages:   256
Publication Date:   12 August 2017
Format:   Paperback
Availability:   Manufactured on demand   Availability explained
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Introduction to Nature-Inspired Optimization


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Overview

Introduction to Nature-Inspired Optimization brings together many of the innovative mathematical methods for non-linear optimization that have their origins in the way various species behave in order to optimize their chances of survival. The book describes each method, examines their strengths and weaknesses, and where appropriate, provides the MATLAB code to give practical insight into the detailed structure of these methods and how they work. Nature-inspired algorithms emulate processes that are found in the natural world, spurring interest for optimization. Lindfield/Penny provide concise coverage to all the major algorithms, including genetic algorithms, artificial bee colony algorithms, ant colony optimization and the cuckoo search algorithm, among others. This book provides a quick reference to practicing engineers, researchers and graduate students who work in the field of optimization.

Full Product Details

Author:   George Lindfield (Professor, School of Engineering and Applied Science, Aston University) ,  John Penny (Professor, School of Engineering and Applied Science, Aston University)
Publisher:   Elsevier Science Publishing Co Inc
Imprint:   Academic Press Inc
Weight:   0.520kg
ISBN:  

9780128036365


ISBN 10:   0128036362
Pages:   256
Publication Date:   12 August 2017
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of Contents

1. Introduction 2. Genetic algorithms (GAs). 3. Artificial bee colony (ABC) algorithm 4. The bat algorithm. 5. Strawberry optimization algorithm 6. Ant colony optimization (ACO) 7. Cuckoo search algorithm 8. Other algorithms and hybrid algorithms 9. General comparison of the nature of the methods

Reviews

Besides being very useful to those who are interested in discrete optimizations problems and applying various nature-inspired metaheuristics to them, the involved reader can also benefit from comparative studies of algorithms highlighting their strengths and weaknesses. The book is written in a clean and easily uderstandable, but still highly scientific language and it is beneficial reading for post-docs and researchers working with MATLAB and interested in metaheuristic approaches to optimization problems. --Zentralblatt MATH


"""Besides being very useful to those who are interested in discrete optimizations problems and applying various nature-inspired metaheuristics to them, the involved reader can also benefit from comparative studies of algorithms highlighting their strengths and weaknesses. The book is written in a clean and easily uderstandable, but still highly scientific language and it is beneficial reading for post-docs and researchers working with MATLAB and interested in metaheuristic approaches to optimization problems."" --Zentralblatt MATH"


Author Information

George Lindfield is a former lecturer in Mathematics and Computing at the School of Engineering and Applied Science, Aston University in the United Kingdom. John Penny is an Emeritus Professor of Mechanical Engineering at the School of Engineering and Applied Science, Aston University in the United Kingdom.

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