Consideration of Searching Ability for Distributed Probabilistic Model-Building Genetic Algorithm

S. Hirai, H. Shimosaka, T. Hiroyasu, and M. Miki (Japan)


Optimization, Genetic Algorithms and Evolutionary Com putation, Distributed Processing Probabilistic Model Building.


Distributed Probabilistic Model-building Genetic Algo rithms (DPMBGAs) are a new type of Genetic Algorithm. In the DPMBGA, when the offspring are generated, Princi pal Component Analysis (PCA) considers the correlations among the design variables. Moreover, this model applies the island model to maintain population diversity. The ef fectiveness of DPMBGA has been demonstrated through optimization of continuous functions. This paper describes the effectiveness of the parameters in the DPMBGA. Ex periments indicated that these parameters are important factor for maintenance of the diversity of the population.

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