A framework for guided complete search for solving constraint satisfaction problems and some of its instances

Systematic tree search augmented with constraint propagation has been regarded as the de facto standard approach to solve constraint satisfaction problems (CSPs). The property of completeness of tree search is superior to incomplete stochastic local search, although local search approach is more efficient in general. Many heuristics techniques have been developed to improve the efficiency of the tree search approach. We propose a framework for combining and coordinating a complete tree search solver and a different solver in order to produce a complete and efficient CSP solver. Three different instances of the framework have been suggested including combining complete tree search with stochastic search, mathematical programming approach respectively. The experimental results show that this highly integrated hybrid scheme greatly improve the efficiency of constraint solving process in terms of both computation time and number of backtracking.