SUBMISSION TO ICEC ' 98 , TOPIC : APPLICATIONS OF EVOLUTIONARY COMPUTATION 1 Optimization by hybridization of a geneticalgorithm with constraint satisfaction

| We introduce a new optimization method based on a Genetic Algorithm (GA) mixed with Constraint Satisfaction Problem (CSP) techniques. The approach is designed for combinatorial problems whose search spaces are too large and/or objective functions too complex for usual CSP techniques and whose constraints are too complex for conventional genetic algorithm. The main idea is the handling of sub-domains of the CSP variables by the genetic algorithm. The population of the genetic algorithm is made up of strings of sub-domains whose tness are computed through the resolution of the corresponding \sub-CSPs" which are somehow much easier than the original problem. We provide basic and dedicated recombina-tion and mutation operators with various degrees of robustness. The rst set of experimentations adresses a na ve formulation of the Vehicle Routing Problem (VRP) and the Radio Link Frequency As-signement Problem (RLFAP). The results are quite encouraging as we outperform CSP techniques and genetic algorithm alone.