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, 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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accepted ant colony optimization ants bee colony begin Objective function colony optimization constrained optimization constraints convergence cooling crossover current best Deﬁne diﬀerent diﬃcult distance eﬀectively eﬃcient encoded end Figure enzyme algorithm evaluations example fireflies ﬁreﬂy algorithm ﬁrst ﬁtness function ﬁxed length ﬂashing food source forager bees formulated genetic algorithms global minimum global optimality gorithms harmony memory harmony search honey bee algorithm implementation initial locations inline function Lagrange multiplier light intensity local minimum Matlab maximize Maximum number metaheuristic metaheuristic algorithms minimization mutation nectar number of iterations Objective function f(x optimal solution optimiza optimization problems parameter particle swarm optimization pheromone concentration photosynthetic algorithm pitch adjusting population probability random randomly reaction rithms route shown in Fig simulated annealing stationary condition steepest descent method strings swap Tabu list Tabu search temperature test functions tion travelling salesman problem update values variations vector waggle dance worth pointing Xin-She