Enhancing set constraint solvers with bound consistency

Abstract

Constraint solvers have proved to be a powerful tool for both expressing and solving complex problems in many contexts, in particular in Automated Planning and Scheduling. In this work, we propose new constraints to enhancing an implementation of a constraint solver for sets of integers (ic_sets) embedded in the ECLiPSe system. This way, we confer a new vision of modelling that in particular allows a task to be planned on alternate days. In addition, these new constraints make finite domain and finite sets domains to cooperate, reducing the search space and improving the efficiency of the existing set solvers for some specific cases. We report on a prototype implementation and apply these constraints to modelling scheduling problems as benchmarks for a performance analysis. Experiments reveal a relevant improvement with respect to the standard ic_sets solver which only features cardinality as cooperation mechanism between domains. Both enhanced expressiveness and performance are key points for practical applications of such solvers.