Logistics service scheduling with manufacturing provider selection in cloud manufacturing

In service-oriented manufacturing models, manufacturing resources in different enterprises are integrated and shared through network, cloud platforms, and logistics. On cloud manufacturing platforms, service providers offer on-demand manufacturing services to service demanders according to supply-demand matching results. As a special type of manufacturing services, logistics services provide transportation capabilities for production services and demanders. It is a critical issue to schedule logistics services efficiently, especially when manufacturer selections have been planned. This research focuses on the logistics scheduling problem in cloud manufacturing with pre-selected manufacturers. We analyze this optimization problem from aspects of tasks, production services, logistics services, and optimization objectives. Then a logistics scheduling method is proposed to reduce the average delivery time from manufacturers to customers. In the proposed method, the total time from start points of logistics to demanders is considered to reduce the average delivery time of all tasks. Based on four different scenarios, we build their scheduling models and run simulations to verify the effectiveness of the proposed method. Results show that the average task delivery time of the proposed method is shorter than three typical strategies.