Study On Cloud Manufacturing-oriented Mixed-model Hybrid Shop Scheduling Problem

With the rapid development of the information technology,new manufacturing model such as Cloud Manufacturing will become main directions of future manufacturing.Cloud Manufacturing can realize the sharing of resources and sevices across corporations,thus provides a new way for improving the efficiency of the idle resources.With the era of customer demand diversified,mixed-model hybrid shop has become the choice for solving multi-species and small quantities production.But due to the mixed assembly demand of the flow shop,the idle resources is obvious in job shop.The emergence of Cloud Manufacturing provides a new opportunity for improving the utilization of dle resource,but also presents a new challenge of scheduling.Considering the collaborative scheduling of cloud service task and self-made task,the paper focused on solving the coordinated scheduling problem for Cloud Manufacturing-oriented Mixed-model Hybrid shop(CMMHS),the main research work is summarized as follows:(1)The entity model and characteristics of CMMHS was described.And the disturbed factors in the Cloud Manufacturing environment was analyzed.On this basis,the system crchitecture and workflow of CMMHS was established.Then,a capacity partition method based on clustering algorithm was given.(2)The pre-scheduling model was presented based on three objectives: minimizing the makespan,minimizing the total variation in parts consumption and maximizing the utilization rate of the job shop.In this model,different batch partitioning strategies were used to coordinate cloud service task and self-made task in part shop.Then,a hybrid Biogeography-based Optimization(BBO)algorithm with two level hierarchical structures was proposed to solve the model.Moreover,a mutation strategy of Differential Evolution(DE)algorithm was introduced to the transport operator of BBO to improve the searching efficiency.(3)The rescheduling model was constructed based on validity and stability scheduling index.Then,rescheduling strategy was presented based on rolling window technology and hybrid BBO to solve the model.(4)A CMMHS scheduling problem of refrigerator manufacturing enterprises was taken for an example to validate the model and algorithm.The research makes some contributions in key techniques of workshop resources optimization in Cloud Manufacturing environment.From the cloud service definition,the cooperative scheduling of cloud service task and self-made task,and the dynamic disturbance processing,the presented research form a whole process system.The presented key technology provid theoretical basis and decision support for improving the utilization ratio of CMMHS.