Consistent Neighbourhood in a Tabu Search
We present a general approach for solving Constraint Optimization Problems. A Tabu Search is performed on a well-designed Consistent Neighbourhood built using Constraint Programming. After each variable assignment, the conflicting variables are deleted to maintain the consistency of the instantiated constraints. Hence, instead of allowing infeasible moves on complete configurations, it works on partial and consistent ones until a solution is found. This approach is successfully applied in solving real-life problems. Two ones are presented: the Frequency Assignment Problem with Polarization and the Agile Earth Observing Satellite Management Problem.