Limtanyakul, Kamol2009-10-222009-10-222009-10-22http://hdl.handle.net/2003/2646510.17877/DE290R-15874In the automotive industry, a manufacturer must perform several hundreds of tests on prototypes of a vehicle before starting its mass production. These tests must be allocated to suitable prototypes and ordered to satisfy temporal constraints and various kinds of test dependencies. To reduce costs, the manufacturer is interested in using the minimum number of prototypes. We apply Constraint Programming (CP) and a hybrid approach to solve the scheduling problem. Our CP method can achieve good feasible solutions even for our largest instances within a reasonable time. In comparison with existing methods, we can improve the solutions for most of our instances and reduce the average number of required prototypes. The hybrid approach uses mixed integer linear programming (MILP) to solve the planning part and CP to find the complete schedule. Although the hybrid approach is not as robust as CP with respect to data characteristics and additional constraints, it can complement CP in finding a better lower bound.enSchedulingAutomobile industryConstraint programmingHybrid approachInteger Programming004doctoral thesisSchedulingAutomobilindustrieConstraint programmingTestmethodeModellierungurn:nbn:de:hbz:290-2003/26465-2