Книга Evolutionary Computation in Combinatorial Optimization Carlos Cotta

Evolutionary Computation in Combinatorial Optimization

9th European Conference, EvoCOP 2009, Tubingen, Germany, April 15-17, 2009, Proceedings

Език: Английски език
Корици: С меки корици
Наличност: Външен склад
Изпращаме след 5-8 дни
52.68 103.02 лв
This book constitutes the refereed proceedings of the 9th European Conference on Evolutionary Comput...

Информация за книгата

Език
Английски език
Корици
Книга - С меки корици
Издадена
2009
страници
253
EAN
9783642010088
ISBN
3642010083
Enbook ID
01649527
Теглоt
415
Размери
155 x 235 x 15

Пълно описание

This book constitutes the refereed proceedings of the 9th European Conference on Evolutionary Computation in Combinatorial Optimization, EvoCOP 2009, held in Tübingen, Germany, in April 2009.§The 21 revised full papers presented were carefully reviewed and selected from 53 submissions. The papers present the latest research and discuss current developments and applications in metaheuristics - a paradigm to effectively solve difficult combinatorial optimization problems appearing in various industrial, economical, and scientific domains. Prominent examples of metaheuristics are evolutionary algorithms, simulated annealing, tabu search, scatter search, memetic algorithms, variable neighborhood search, iterated local search, greedy randomized adaptive search procedures, estimation of distribution algorithms and ant colony optimization.This book constitutes the refereed proceedings of the 9th European Conference on Evolutionary Computation in Combinatorial Optimization, EvoCOP 2009, held in Tübingen, Germany, in April 2009.§The 21 revised full papers presented were carefully reviewed and selected from 53 submissions. The papers present the latest research and discuss current developments and applications in metaheuristics - a paradigm to effectively solve difficult combinatorial optimization problems appearing in various industrial, economical, and scientific domains. Prominent examples of metaheuristics are evolutionary algorithms, simulated annealing, tabu search, scatter search, memetic algorithms, variable neighborhood search, iterated local search, greedy randomized adaptive search procedures, estimation of distribution algorithms and ant colony optimization.

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