The development of cloud manufacturing provides more resource options for customized services. Cloud platforms need to allocate optimal resources for each manufacturing task. However, the manufacturing time of the resources selected by the current task may have been occupied by other tasks, and the task cannot be started at the original manufacturing time. This paper introduces a resource allocation method that considers a waiting strategy when resources are occupied. By introducing the waiting mechanism, the diversity of resource selection is increased so that high-quality resources in the cloud resource pool can be selected. To match the optimal resources, the differential evolution (DE) algorithm is used to optimize resource solutions considering manufacturing time, cost, and reliability to achieve resource optimization in the cloud manufacturing environment. Experiment results verified the superiority of the proposed methods in comparison with the method without considering task occupancy.