Title :
Theoretical study on diversity of population in parallel genetic algorithms
Author :
Pan, Mei Qin ; He, Guo Ping
Author_Institution :
Coll. of Inf. Sci. & Eng., Shandong Univ. of Sci. & Technol., China
Abstract :
In this paper, conditional probability density and marginal distribution are proposed as measures of population in genetic algorithms. The influence of selection, crossover and mutation on population distribution is analyzed. In addition, the recursive equations governing population density are derived, and a conclusion of global convergence is also shown.
Keywords :
convergence; genetic algorithms; probability; recursive estimation; conditional probability density; crossover; diversity of population; global convergence; marginal distribution; mutation; parallel genetic algorithms; population distribution; recursive equations; selection; Artificial intelligence; Convergence; Density measurement; Educational institutions; Equations; Genetic algorithms; Genetic mutations; Helium; Machine learning; Mathematical model;
Conference_Titel :
Machine Learning and Cybernetics, 2002. Proceedings. 2002 International Conference on
Print_ISBN :
0-7803-7508-4
DOI :
10.1109/ICMLC.2002.1176799
