Dynamic constraint ordering heuristics for dynamic CSPs

Many research studies have shown that the choice of a relevant order of variables and/or values can significantly improve the efficiency of search algorithms. However, in Constraint Satisfaction Problems CSPs, constraint ordering heuristics have received less attention than variables and values ordering heuristics. In the literature, only some few contributions have been done on this area, and mainly as a preprocessing phase before starting the search process. In this paper, we show that constraint ordering heuristics are promising and able to make relevant choices during the search process within a Dynamic CSP . Our proposed approach, called Dynamic Constraint Ordering heuristic DCO, selects dynamically constraints which are likely to lead to conflicts. So, we apply a ”fail first” principle, in a manner that a dynamic intelligent backtracking event can be performed earlier. This method is able to guide a dynamic repair algorithm towards the hardest constraint subproblems and to tackle inconsistencies in order to correct solution assignment. The conducted experiments have confirmed that the proposed approach is interesting. Our results show clearly the efficiency of the heuristics combined with Partial-Order Dynamic Backtracking 6890 Saida Hammoujan et al. algorithm PDB on Meeting Scheduling Problems. The algorithms have been tested in terms of run-time, constraints checks and solution stabil-