A constraint satisfaction problem requires a value, selected from a given finite domain, to be assigned to each variable in the problem, so that all constraints relating the variables are satisfied. The main feature of any constraint solver is constraint propagation, it embeds any reasoning which consists in explicitly forbidding values or combinations of values for some variables of a problem because a given subset of its constraints cannot be satisfied otherwise. It is very important to apply constraint propagation as efficiently as possible. In this paper, we present a hybrid solver based on a Branch and Bound algorithm combined with constraint propagation to reduce the search space. Some rules trigger constraint propagation based on some observations of the solving process. The results show that is possible to make reasonable use of constraint propagation.