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GECCO
2007
Springer
183views Optimization» more  GECCO 2007»
14 years 1 months ago
Self-adaptive simulated binary crossover for real-parameter optimization
Simulated binary crossover (SBX) is a real-parameter recombination operator which is commonly used in the evolutionary algorithm (EA) literature. The operator involves a parameter...
Kalyanmoy Deb, Karthik Sindhya, Tatsuya Okabe
TSMC
2002
93views more  TSMC 2002»
13 years 7 months ago
Statistical analysis of the main parameters involved in the design of a genetic algorithm
Abstract--Most genetic algorithm (GA) users adjust the main parameters of the design of a GA (crossover and mutation probability, population size, number of generations, crossover,...
Ignacio Rojas, Jesús González, H&eac...
GECCO
2006
Springer
195views Optimization» more  GECCO 2006»
13 years 11 months ago
Studying XCS/BOA learning in Boolean functions: structure encoding and random Boolean functions
Recently, studies with the XCS classifier system on Boolean functions have shown that in certain types of functions simple crossover operators can lead to disruption and, conseque...
Martin V. Butz, Martin Pelikan
FOGA
1998
13 years 9 months ago
Understanding Interactions among Genetic Algorithm Parameters
Genetic algorithms (GAs) are multi-dimensional and stochastic search methods, involving complex interactions among their parameters. For last two decades, researchers have been tr...
Kalyanmoy Deb, Samir Agrawal
ICANNGA
2009
Springer
163views Algorithms» more  ICANNGA 2009»
13 years 11 months ago
Elitistic Evolution: An Efficient Heuristic for Global Optimization
A new evolutionary algorithm, Elitistic Evolution (termed EEv), is proposed in this paper. EEv is an evolutionary method for numerical optimization with adaptive behavior. EEv uses...
Francisco Viveros Jiménez, Efrén Mez...