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» Evolutionary algorithms and matroid optimization problems
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GECCO
2009
Springer
132views Optimization» more  GECCO 2009»
14 years 2 months ago
Bringing evolutionary computation to industrial applications with guide
Evolutionary Computation is an exciting research field with the power to assist researchers in the task of solving hard optimization problems (i.e., problems where the exploitabl...
Luís Da Costa, Marc Schoenauer
GECCO
2010
Springer
169views Optimization» more  GECCO 2010»
13 years 10 months ago
Stochastic local search in continuous domains: questions to be answered when designing a novel algorithm
Several population-based methods (with origins in the world of evolutionary strategies and estimation-of-distribution algorithms) for black-box optimization in continuous domains ...
Petr Posik
IPPS
2003
IEEE
14 years 1 months ago
Parallel LAN/WAN Heuristics for Optimization
We present in this work a wide spectrum of results on analyzing the behavior of parallel heuristics for solving optimization problems. We focus on evolutionary algorithms as well ...
Enrique Alba, Gabriel Luque
NICSO
2010
Springer
13 years 12 months ago
Accelerated Genetic Algorithms with Markov Chains
t] Based on the mutation matrix formalism and past statistics of genetic algorithm, a Markov Chain transition probability matrix is introduced to provide a guided search for comple...
Guan Wang, Chen Chen, Kwok Yip Szeto
GECCO
2010
Springer
154views Optimization» more  GECCO 2010»
14 years 21 days ago
Evolutionary learning in networked multi-agent organizations
This study proposes a simple computational model of evolutionary learning in organizations informed by genetic algorithms. Agents who interact only with neighboring partners seek ...
Jae-Woo Kim