A branching-cutting Cultural algorithm for weak-constraints optimization

Compared with common constraints, weak-constraint in the paper means the constraint should be satisfied only if it is possible. There are a lot of reality problem have weak-constraint. The good result of the problem is the feasible result which can meet weak-constraints as much as possible. The method of pruning the infeasible weak-constraints group to solve weak-constraints optimization problems is first proposed. Such exploitation of branching-cutting technique can make the weak-constraints optimization problems satisfy more weak-constraints and produce feasible results at a relatively low computational cost. Cultural algorithm is used to guide the search more efficiently in the paper. The results indicate that the approach is able to produce feasible results which satisfy more weak-constraints as much as possible.