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 19 April 2024 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
Nature inspired Metaheuristic Algorithms
Author : Xin-She Yang
File Size : 54,7 Mb
Publisher : Luniver Press
Language : English
Release Date : 19 April 2024
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

Nature inspired Metaheuristic Algorithms by Xin-She Yang

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 Methods for Metaheuristics Optimization

Nature Inspired Methods for Metaheuristics Optimization by Fouad Bennis,Rajib Kumar Bhattacharjya

This book gathers together a set of chapters covering recent development in optimization methods that are inspired by nature. The first group of chapters describes in detail different meta-heuristic algorithms, and shows their applicability using some test or real-world problems. The second part of the book is especially focused on

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Nature inspired Methods for Metaheuristics Optimization

Nature inspired Methods for Metaheuristics Optimization by Anonim

This book gathers together a set of chapters covering recent development in optimization methods that are inspired by nature. The first group of chapters describes in detail different meta-heuristic algorithms, and shows their applicability using some test or real-world problems. The second part of the book is especially focused on

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Search and Optimization by Metaheuristics

Search and Optimization by Metaheuristics by Ke-Lin Du,M. N. S. Swamy

This textbook provides a comprehensive introduction to nature-inspired metaheuristic methods for search and optimization, including the latest trends in evolutionary algorithms and other forms of natural computing. Over 100 different types of these methods are discussed in detail. The authors emphasize non-standard optimization problems and utilize a natural approach to the

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Nature Inspired Optimization Algorithms

Nature Inspired Optimization Algorithms by Xin-She Yang

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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Mathematical Foundations of Nature Inspired Algorithms

Mathematical Foundations of Nature Inspired Algorithms by Xin-She Yang,Xing-Shi He

This book presents a systematic approach to analyze nature-inspired algorithms. Beginning with an introduction to optimization methods and algorithms, this book moves on to provide a unified framework of mathematical analysis for convergence and stability. Specific nature-inspired algorithms include: swarm intelligence, ant colony optimization, particle swarm optimization, bee-inspired algorithms, bat

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Nature inspired Methods for Stochastic Robust and Dynamic Optimization

Nature inspired Methods for Stochastic Robust and Dynamic Optimization by Javier Del Ser Lorente,Eneko Osaba

Nature-inspired algorithms have a great popularity in the current scientific community, being the focused scope of many research contributions in the literature year by year. The rationale behind the acquired momentum by this broad family of methods lies on their outstanding performance evinced in hundreds of research fields and problem

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Nature Inspired Metaheuristic Algorithms for Engineering Optimization Applications

Nature Inspired Metaheuristic Algorithms for Engineering Optimization Applications by Serdar Carbas,Abdurrahim Toktas,Deniz Ustun

This book engages in an ongoing topic, such as the implementation of nature-inspired metaheuristic algorithms, with a main concentration on optimization problems in different fields of engineering optimization applications. The chapters of the book provide concise overviews of various nature-inspired metaheuristic algorithms, defining their profits in obtaining the optimal solutions

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