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GECCO
2006
Springer
206views Optimization» more  GECCO 2006»
13 years 9 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
CORR
2004
Springer
108views Education» more  CORR 2004»
13 years 5 months ago
Efficiency Enhancement of Probabilistic Model Building Genetic Algorithms
Abstract. This paper presents two different efficiency-enhancement techniques for probabilistic model building genetic algorithms. The first technique proposes the use of a mutatio...
Kumara Sastry, David E. Goldberg, Martin Pelikan
GECCO
2003
Springer
118views Optimization» more  GECCO 2003»
13 years 10 months ago
Distributed Probabilistic Model-Building Genetic Algorithm
In this paper, a new model of Probabilistic Model-Building Genetic Algorithms (PMBGAs), Distributed PMBGA (DPMBGA), is proposed. In the DPMBGA, the correlation among the design var...
Tomoyuki Hiroyasu, Mitsunori Miki, Masaki Sano, Hi...
GECCO
2005
Springer
154views Optimization» more  GECCO 2005»
13 years 11 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...
SIGIR
2004
ACM
13 years 10 months ago
GaP: a factor model for discrete data
We present a probabilistic model for a document corpus that combines many of the desirable features of previous models. The model is called “GaP” for Gamma-Poisson, the distri...
John F. Canny