Evolutionary Computation in Combinatorial Optimization 11th European Conference, EvoCOP 2011, Torino, Italy, April 27-29, 2011, Proceedings /
Evolutionary Computation in Combinatorial Optimization 11th European Conference, EvoCOP 2011, Torino, Italy, April 27-29, 2011, Proceedings / [electronic resource] :
edited by Peter Merz, Jin-Kao Hao.
- 1st ed. 2011.
- XIV, 263 p. online resource.
- Theoretical Computer Science and General Issues, 6622 2512-2029 ; .
- Theoretical Computer Science and General Issues, 6622 .
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.
9783642203640
10.1007/978-3-642-20364-0 doi
Algorithms.
Computer science.
Pattern recognition systems.
Computer science--Mathematics.
Discrete mathematics.
Mathematical statistics.
Algorithms.
Theory of Computation.
Automated Pattern Recognition.
Discrete Mathematics in Computer Science.
Probability and Statistics in Computer Science.
QA76.9.A43
518.1
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.
9783642203640
10.1007/978-3-642-20364-0 doi
Algorithms.
Computer science.
Pattern recognition systems.
Computer science--Mathematics.
Discrete mathematics.
Mathematical statistics.
Algorithms.
Theory of Computation.
Automated Pattern Recognition.
Discrete Mathematics in Computer Science.
Probability and Statistics in Computer Science.
QA76.9.A43
518.1