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.

在面向服务的制造模型中，通过网络，云平台和物流来集成和共享不同企业中的制造资源。在云制造平台上，服务提供商根据供需匹配结果向服务需求者提供按需制造服务。作为一种特殊的制造服务，物流服务为生产服务和需求者提供运输能力。有效安排物流服务至关重要，尤其是在计划了制造商选择时。这项研究的重点是预先选择制造商的云制造中的物流调度问题。我们从任务，生产服务，物流服务和优化目标等方面分析此优化问题。然后提出一种物流调度方法，以减少从制造商到客户的平均交货时间。在提出的方法中，考虑了从物流起点到需求者的总时间，以减少所有任务的平均交货时间。基于四种不同的情况，我们构建了它们的调度模型并进行了仿真，以验证所提出方法的有效性。结果表明，该方法的平均任务交付时间比三种典型策略短。我们建立他们的调度模型并运行仿真以验证所提出方法的有效性。结果表明，该方法的平均任务交付时间比三种典型策略短。我们建立他们的调度模型并运行仿真以验证所提出方法的有效性。结果表明，该方法的平均任务交付时间比三种典型策略短。