A New Heuristic-based albeit Complete Method to Extract MUCs from Unsatisfiable CSPs

Abstract

When a constraint satisfaction problem (CSP) admits no solution, most current solvers express that the whole search space has been explored unsuccessfully but do not exhibit which constraints are actually contradicting one another and make the problem infeasible. In this paper, we improve a recent heuristic-based approach to compute infeasible minimal subparts of CSPs, also called minimally unsatisfiable cores (MUCs). The approach is based on the heuristic exploitation of the number of times each constraint has been falsified during previous failed search steps. It appears to improve the performance of the initial technique, which was the most efficient one until now