constraint abstractions into integer programming, and to discuss possible combinations of the two approaches. Combinatorial problems are ubiquitous in many real world applications like scheduling, planning, transportation, assignment, and many others. Besides special purpose algorithms to compute exact or approximate solutions, there exist also general approaches to solve this kind of problem. We are interested here in two such approaches: • Integer linear programming (ILP) • Finite domain constraint programming (CP(FD)) Integer linear programming has a long tradition in operations research and has produced a large number of impressive results during the last 40 years, see for example [37, 30]. Finite domain constraint programming is a promising new approach for solving complex combinatorial problems, which combines recent progress in programming language design, like constraint logic programming[29] or concurrent constraint programming,[42] with efficient constraint solving techni...