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GECCO
2007
Springer
181views Optimization» more  GECCO 2007»
16 years 26 days ago
A study on metamodeling techniques, ensembles, and multi-surrogates in evolutionary computation
Surrogate-Assisted Memetic Algorithm(SAMA) is a hybrid evolutionary algorithm, particularly a memetic algorithm that employs surrogate models in the optimization search. Since mos...
Dudy Lim, Yew-Soon Ong, Yaochu Jin, Bernhard Sendh...
GECCO
2005
Springer
143views Optimization» more  GECCO 2005»
16 years 7 days ago
Advanced models of cellular genetic algorithms evaluated on SAT
Cellular genetic algorithms (cGAs) are mainly characterized by their spatially decentralized population, in which individuals can only interact with their neighbors. In this work,...
Enrique Alba, Hugo Alfonso, Bernabé Dorrons...
GECCO
2005
Springer
126views Optimization» more  GECCO 2005»
16 years 7 days ago
Not all linear functions are equally difficult for the compact genetic algorithm
Estimation of distribution algorithms (EDAs) try to solve an optimization problem by finding a probability distribution focussed around its optima. For this purpose they conduct ...
Stefan Droste
GECCO
2006
Springer
206views Optimization» more  GECCO 2006»
15 years 10 months ago
Adaptive discretization for probabilistic model building genetic algorithms
This paper proposes an adaptive discretization method, called Split-on-Demand (SoD), to enable the probabilistic model building genetic algorithm (PMBGA) to solve optimization pro...
Chao-Hong Chen, Wei-Nan Liu, Ying-Ping Chen
GECCO
2006
Springer
138views Optimization» more  GECCO 2006»
15 years 10 months ago
Does overfitting affect performance in estimation of distribution algorithms
Estimation of Distribution Algorithms (EDAs) are a class of evolutionary algorithms that use machine learning techniques to solve optimization problems. Machine learning is used t...
Hao Wu, Jonathan L. Shapiro