Nature inspired Metaheuristic Algorithms

This book PDF is perfect for those who love Computers genre, written by Xin-She Yang and published by Luniver Press which was released on 06 October 2022 with total hardcover pages 148. You could read this book directly on your devices with pdf, epub and kindle format, check detail and related Nature inspired Metaheuristic Algorithms books below.

Nature inspired Metaheuristic Algorithms
Author : Xin-She Yang
File Size : 44,9 Mb
Publisher : Luniver Press
Language : English
Release Date : 06 October 2022
ISBN : 9781905986286
Pages : 148 pages
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Nature inspired Metaheuristic Algorithms by Xin-She Yang Book PDF Summary

Modern metaheuristic algorithms such as bee algorithms and harmony search start to demonstrate their power in dealing with tough optimization problems and even NP-hard problems. This book reviews and introduces the state-of-the-art nature-inspired metaheuristic algorithms in optimization, including genetic algorithms, bee algorithms, particle swarm optimization, simulated annealing, ant colony optimization, harmony search, and firefly algorithms. We also briefly introduce the photosynthetic algorithm, the enzyme algorithm, and Tabu search. Worked examples with implementation have been used to show how each algorithm works. This book is thus an ideal textbook for an undergraduate and/or graduate course. As some of the algorithms such as the harmony search and firefly algorithms are at the forefront of current research, this book can also serve as a reference book for researchers.

Nature inspired Metaheuristic Algorithms

Modern metaheuristic algorithms such as bee algorithms and harmony search start to demonstrate their power in dealing with tough optimization problems and even NP-hard problems. This book reviews and introduces the state-of-the-art nature-inspired metaheuristic algorithms in optimization, including genetic algorithms, bee algorithms, particle swarm optimization, simulated annealing, ant colony optimization,

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Nature Inspired Metaheuristic Algorithms

Modern metaheuristic algorithms such as bee algorithms and harmony search start to demonstrate their power in dealing with tough optimization problems and even NP-hard problems. This book reviews and introduces the state-of-the-art nature-inspired metaheuristic algorithms in optimization, including genetic algorithms, bee algorithms, particle swarm optimization, simulated annealing, ant colony optimization,

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Nature-Inspired Optimization Algorithms provides a systematic introduction to all major nature-inspired algorithms for optimization. The book's unified approach, balancing algorithm introduction, theoretical background and practical implementation, complements extensive literature with well-chosen case studies to illustrate how these algorithms work. Topics include particle swarm optimization, ant and bee algorithms, simulated annealing,

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