Hybridization of estimation of distribution algorithms with a repair method for solving constraint satisfaction problems

Estimation of Distribution Algorithms (EDAs) are new promising methods in the field of genetic and evolutionary algorithms. In the case of conventional Genetic and Evolutionary Algorithm studies to apply Constraint Satisfaction Problems (CSPs), it is well-known that the incorporation of the domain knowledge in the CSPs is quite effective. In this paper, we propose a hybridization method (memetic algorithm) of Estimation of Distribution Algorithms with a repair method. Experimental results on general CSPs tell us the effectiveness of the proposed method.