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Evolutionary Computation in Combinatorial Optimization [electronic resource] : 12th European Conference, EvoCOP 2012, Málaga, Spain, April 11-13, 2012, Proceedings / edited by Jin-Kao Hao, Martin Middendorf.

Medverkande: Materialtyp: TextSerie: Utgivningsuppgift: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2012Utgåva: 1st ed. 2012Beskrivning: XII, 264 p. 62 illus. online resourceInnehållstyp:
  • text
Medietyp:
  • computer
Bärartyp:
  • online resource
ISBN:
  • 9783642291241
Ämnen: DDK-klassifikation:
  • 518.1 23
Onlineresurser: Sammanfattning: 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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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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