Essentials of Metaheuristics (Second Edition) Book PDF, ePub eBook

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Book Descriptions:
Interested in the Genetic Algorithm? Simulated Annealing? Ant Colony Optimization? Essentials of Metaheuristics covers these and other metaheuristics algorithms, and is intended for undergraduate students, programmers, and non-experts. The book covers a wide range of algorithms, representations, selection and modification operators, and related topics, and includes 71 figures and 135 algorithms great and small. Algorithms include: Gradient Ascent techniques, Hill-Climbing variants, Simulated Annealing, Tabu Search variants, Iterated Local Search, Evolution Strategies, the Genetic Algorithm, the Steady-State Genetic Algorithm, Differential Evolution, Particle Swarm Optimization, Genetic Programming variants, One- and Two-Population Competitive Coevolution, N-Population Cooperative Coevolution, Implicit Fitness Sharing, Deterministic Crowding, Nsga-Ii, Spea2, Grasp, Ant Colony Optimization variants, Guided Local Search, Lem, Pbil, Umda, cGa, Boa, Samuel, Zcs, Xcs, and Xcsf.

Essentials of Metaheuristics (Second Edition) by Sean Luke

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