Computational Intelligence-based Optimization Algorithms: From Theory to Practice

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Babak Zolghadr-Asli (University of Exeter, UK, and University of Queensland, Australia)

Computational Intelligence-based Optimization Algorithms

From Theory to Practice

Babak Zolghadr-Asli (University of Exeter, UK, and University of Queensland, Australia)

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English

CRC Press
11 October 2023

Applied mathematics; Computing: general; Algorithms & data structures; Mathematical theory of computation

Computational intelligence-based optimization methods, also known as metaheuristic optimization algorithms, are a popular topic in mathematical programming.

These methods have bridged the gap between various approaches and created a new school of thought to solve real-world optimization problems. In this book, we have selected some of the most effective and renowned algorithms in the literature. These algorithms are not only practical but also provide thought-provoking theoretical ideas to help readers understand how they solve optimization problems. Each chapter includes a brief review of the algorithm’s background and the fields it has been used in.

Additionally, Python code is provided for all algorithms at the end of each chapter, making this book a valuable resource for beginner and intermediate programmers looking to understand these algorithms.

By: Babak Zolghadr-Asli (University of Exeter UK and University of Queensland Australia)
Imprint: CRC Press
Country of Publication: United Kingdom
Dimensions: Height: 234mm, Width: 156mm,
Weight: 820g
ISBN: 9781032544168
ISBN 10: 1032544163
Pages: 338
Publication Date: 11 October 2023
Audience: Professional and scholarly , Undergraduate
Format: Hardback
Publisher's Status: Active

Babak Zolghadr-Asli is currently a joint researcher under the QUEX program, working at the Sustainable Minerals Institute at The University of Queensland in Australia and The Centre for Water Systems at The University of Exeter in the UK. His primary research interest is to incorporate computational and artificial intelligence to understand the sustainable management of water resources.