Minimizing conflicts: a heuristic repair method for constraint satisfaction and scheduling problems
Constraint-based reasoning
Practical Handbook of Genetic Algorithms
Practical Handbook of Genetic Algorithms
Estimation of Distribution Algorithms: A New Tool for Evolutionary Computation
Estimation of Distribution Algorithms: A New Tool for Evolutionary Computation
From Recombination of Genes to the Estimation of Distributions I. Binary Parameters
PPSN IV Proceedings of the 4th International Conference on Parallel Problem Solving from Nature
Combinatonal Optimization by Learning and Simulation of Bayesian Networks
UAI '00 Proceedings of the 16th Conference on Uncertainty in Artificial Intelligence
Bayesian optimization algorithm: from single level to hierarchy
Bayesian optimization algorithm: from single level to hierarchy
Fda -a scalable evolutionary algorithm for the optimization of additively decomposed functions
Evolutionary Computation
Genetic state-space search for constrained optimization problems
IJCAI'93 Proceedings of the 13th international joint conference on Artifical intelligence - Volume 2
Solving constraint satisfaction problems using hybrid evolutionarysearch
IEEE Transactions on Evolutionary Computation
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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.