Nature-Inspired Metaheuristic Algorithms

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Luniver Press, 2008 - Computers - 116 pages
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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 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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Contents

Genetic Algorithms
21
Ant Algorithms
33
Bee Algorithms
41
Swarm Optimization
49
Simulated Annealing
61
Harmony Search
71
Firefly Algorithm
79
Other Metaheuristic Algorithms
91
Bibliography
109
Index
115
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