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Evolutionary Computation in Combinatorial Optimization [electronic resource] : 11th European Conference, EvoCOP 2011, Torino, Italy, April 27-29, 2011. Proceedings / edited by Peter Merz, Jin-Kao Hao.

By: Contributor(s): Material type: TextTextSeries: Lecture Notes in Computer Science ; 6622Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2011Description: XIV, 263 p. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783642203640
Subject(s): Additional physical formats: Printed edition:: No titleDDC classification:
  • 005.1 23
LOC classification:
  • QA76.9.A43
Online resources: 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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E-Book E-Book Central Library Available E-47817

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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