On the optimal convergence probability of univariate estimation of distribution algorithms

Authors:
Reza Rastegar
Affiliations:
Department of Mathematics, Iowa State University, Ames, Iowa 50011. rastegar@iastate.edu
Venue:
Evolutionary Computation
Year:
2011

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Abstract

In this paper we obtain bounds on the probability of convergence to the optimal solution for the compact genetic algorithm (cGA) and the population based incremental learning (PBIL). Moreover, we give a sufficient condition for convergence of these algorithms to the optimal solution and compute a range of possible values for algorithm parameters at which there is convergence to the optimal solution with a predefined confidence level.