Improved Grey Wolf Optimization Algorithm for Solving Cloud Manufacturing Scheduling Problem with Limit Logistics Resource

In the cloud manufacturing environment, the manufacturing resources and manufacturing capabilities of different companies are shared through the cloud platform in the form of services. Service providers supply on-demand manufacturing services to service demanders. As an inevitable part in the task execution process, logistics service affects the final completion time of the task. Effective arrangement of logistics services is a critical part in improving resource utilization and enhancing customer satisfaction. Aiming at the cloud manufacturing scheduling problem with restricted logistics resource, this paper proposes an Improved Gray Wolf Optimization (IGWO) algorithm to minimize the maximum completion time (makespan) with considering queuing in line during logistics transportation. A cloud manufacturing scheduling model with logistics services was presented in this article. The feasibility and effectiveness of the algorithm were verified by the experimental results from small to large scale.