Özet:
Currently, many production firms use third-party logistics (3PL) firms to manage logistics operations effectively. In general, 3PL provides a timetable which consists of delivery dates for each vehicle. Even when firms use their own transport, their vehicles may have pre-defined delivery times. Consequently, fixed delivery dates are commonly observed in practice, leading to a need for synchronizing the production planning decisions according to the delivery schedule and therefore, delivery dates. In related literature, most cases neglect the vehicle capacity, meaning that all jobs can be shipped at the first delivery date after their completion time. Furthermore, earliness is also neglected in many studies. But, it is more realistic to think that the jobs which are completed ahead of their delivery date and waiting for shipment may cause a space problem. Additionally, if the firm adopts just-in-time (JIT) production principles, then earliness must be considered. In our study, the problem becomes more realistic as we integrate such properties. The performance measure of the problem is chosen as the minimum total weighted tardiness and earliness. We develop two mixed-integer linear programming (MILP) models for the scheduling with fixed delivery dates, which is an extension of the NP-Hard scheduling problem. Firstly, we propose several methods to improve the solution quality obtained by a commercial MILP solver. Then we provide and test two heuristic methods, one decomposition-based another inspired by variable neighborhood search (VNS), for larger sized problems. For these problems, solutions close to those obtained by the solver within one-hour duration can be approximately reached using the proposed heuristic methods within a much shorter time.
