Nature-Inspired Metaheuristic AlgorithmsLuniver Press, 2008 - 116 halaman 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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accelerated PSO accepted Algorithm begin end ant colony optimization ants Artificial Bee Colony attractiveness banana function begin end Objective Cambridge University cities colony optimization Computer constraints convergence cooling crossover current best Define efficient encoded end Objective function Engineering Enzyme Algorithm evaluations example Figure firefly algorithm flashing food source forager bees formulated genetic algorithms global minimum global optimality gorithm harmony memory harmony search heuristic honey bee algorithm implementation initial locations inline function light intensity linear Mathematical Matlab and Octave Maximum number metaheuristic metaheuristic algorithms method minimization mutation nectar number of iterations Objective function f(x optimal solution optimiza optimization problems parameter particle swarm optimization pheromone pheromone concentration photosynthetic algorithm pitch adjusting PSO algorithms random randomly rithms route shown in Fig simulated annealing substrate swap Swarm Intelligence Tabu list Tabu search temperature test functions tion travelling salesman problem update values variations vector Vmax waggle dance Xin-She