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Evolutionary Computation in Combinatorial Optimization: 12th European Conference, EvoCOP 2012, Málaga, Spain, April 11-13, 2012, Proceedings: Lecture Notes in Computer Science, cartea 7245

Editat de Jin-Kao Hao, Martin Middendorf
en Limba Engleză Paperback – 28 mar 2012
This book constitutes the refereed proceedings of the 12th European Conference on Evolutionary Computation in Combinatorial Optimization, EvoCOP 2012, held in Málaga, Spain, in April 2012, colocated with the Evo* 2012 events EuroGP, EvoBIO, EvoMUSART, and EvoApplications. . The 22 revised full papers presented were carefully reviewed and selected from 48 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, economic, 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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Specificații

ISBN-13: 9783642291234
ISBN-10: 3642291236
Pagini: 280
Ilustrații: XII, 264 p. 62 illus.
Dimensiuni: 155 x 235 x 20 mm
Greutate: 0.39 kg
Ediția:2012
Editura: Springer Berlin, Heidelberg
Colecția Springer
Seriile Lecture Notes in Computer Science, Theoretical Computer Science and General Issues

Locul publicării:Berlin, Heidelberg, Germany

Public țintă

Research

Textul de pe ultima copertă

This book constitutes the refereed proceedings of the 12th European Conference on Evolutionary Computation in Combinatorial Optimization, EvoCOP 2012, held in Málaga, Spain, in April 2012, colocated with the Evo* 2012 events EuroGP, EvoBIO, EvoMUSART, and EvoApplications. . The 22 revised full papers presented were carefully reviewed and selected from 48 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, economic, 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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State-of-the-art research Fast-track conference proceedings Unique visibility