Solving Constraint Satisfaction Problems by Memetic Algorithms Using Estimation of Distribution Algorithms

Abstract

Estimation of Distribution Algorithms, which employ probabilistic models to generate the next population, are new promising methods in the field of genetic and evolutionary algorithms. In the case of conventional Genetic and Evolutionary Algorithms are applied to Constraint Satisfaction Problems, it is well-known that the incorporation of the domain knowledge in the Constraint Satisfaction Problems is quite effective. In this paper, we constitute a memetic algorithm as a combination of the Estimation of Distribution Algorithm and a repair method. Experimental results on general Constraint Satisfaction Problems tell us the effectiveness of the proposed method.