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Evolutionary Computation in Combinatorial Optimization [electronic resource] :11th European Conference, EvoCOP 2011, Torino, Italy, April 27-29, 2011. Proceedings /

Contributor(s): Merz, Peter [editor.] | Hao, Jin-Kao [editor.] | SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Lecture Notes in Computer Science: 6622Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2011.Description: XIV, 263 p. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783642203640.Subject(s): Computer science | Computers | Algorithms | Computer science -- Mathematics | Mathematical statistics | Pattern recognition | Computer Science | Algorithm Analysis and Problem Complexity | Computation by Abstract Devices | Pattern Recognition | Discrete Mathematics in Computer Science | Probability and Statistics in Computer ScienceOnline resources: Click here to access online In: Springer eBooksSummary: This book constitutes the refereed proceedings of the 11th European Conference on Evolutionary Computation in Combinatorial Optimization, EvoCOP 2011, held in Torino, Italy, in April 2011. The 22 revised full papers presented were carefully reviewed and selected from 42 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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This book constitutes the refereed proceedings of the 11th European Conference on Evolutionary Computation in Combinatorial Optimization, EvoCOP 2011, held in Torino, Italy, in April 2011. The 22 revised full papers presented were carefully reviewed and selected from 42 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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