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EC
2006
97views ECommerce» more  EC 2006»
9 years 8 months ago
A Step Forward in Studying the Compact Genetic Algorithm
The compact Genetic Algorithm (cGA) is an Estimation of Distribution Algorithm that generates offspring population according to the estimated probabilistic model of the parent pop...
Reza Rastegar, Arash Hariri
GECCO
2008
Springer
127views Optimization» more  GECCO 2008»
9 years 9 months ago
Adaptive discretization on multidimensional continuous search spaces
This paper extends an adaptive discretization method, Spliton-Demand (SoD), to be capable of handling multidimensional continuous search spaces. The proposed extension is called m...
Jiun-Jiue Liou, Ying-Ping Chen
GECCO
2006
Springer
206views Optimization» more  GECCO 2006»
9 years 11 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
2004
Springer
175views Optimization» more  GECCO 2004»
10 years 1 months ago
An Architecture for Massive Parallelization of the Compact Genetic Algorithm
This paper presents an architecture which is suitable for a massive parallelization of the compact genetic algorithm. The approach is scalable, has low synchronization costs, and i...
Fernando G. Lobo, Cláudio F. Lima, Hugo Mar...
GECCO
2005
Springer
154views Optimization» more  GECCO 2005»
10 years 1 months ago
Combining competent crossover and mutation operators: a probabilistic model building approach
This paper presents an approach to combine competent crossover and mutation operators via probabilistic model building. Both operators are based on the probabilistic model buildin...
Cláudio F. Lima, Kumara Sastry, David E. Go...
GECCO
2005
Springer
126views Optimization» more  GECCO 2005»
10 years 1 months 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
2007
Springer
155views Optimization» more  GECCO 2007»
10 years 2 months ago
Towards billion-bit optimization via a parallel estimation of distribution algorithm
This paper presents a highly efficient, fully parallelized implementation of the compact genetic algorithm (cGA) to solve very large scale problems with millions to billions of va...
Kumara Sastry, David E. Goldberg, Xavier Llor&agra...
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