Nature-inspired Metaheuristic Algorithms

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  • Nature-inspired Metaheuristic Algorithms Book Detail

  • Author : Xin-She Yang
  • Release Date : 2010
  • Publisher : Luniver Press
  • Genre : Computers
  • Pages : 148
  • ISBN 13 : 1905986289
  • File Size : 23,23 MB

Nature-inspired Metaheuristic Algorithms by Xin-She Yang PDF Summary

Book Description: 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.

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Nature-inspired Metaheuristic Algorithms

Nature-inspired Metaheuristic Algorithms

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Modern metaheuristic algorithms such as bee algorithms and harmony search start to demonstrate their power in dealing with tough optimization problems and even

Nature-Inspired Metaheuristic Algorithms

Nature-Inspired Metaheuristic Algorithms

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Modern metaheuristic algorithms such as bee algorithms and harmony search start to demonstrate their power in dealing with tough optimization problems and even

Nature-Inspired Optimization Algorithms

Nature-Inspired Optimization Algorithms

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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