Abstract: Constraint programming (CP) offers flexible and effective tools for modeling combinatorial optimization problems. At the same time, scheduling with sum type optimization criteria, such as total completion time is challenging for CP. In this paper we show how extending a standard CP solver by a global constraint on total completion time can boost the performance of CP on various, seemingly very different optimization problems, including job shop scheduling, scheduling with tool changes, or even container loading. Copyright c○2007 IFAC Keywords: Constraint-based scheduling, global constraint, total completion time, applications 1
