Research On Resources Scheduling In Cloud Manufacturing

The efficient use of manufacturing resources has gradually become an important development direction of the manufacturing industry in the new century,and the service-oriented and intellectualized manufacturing industry is the two trend of the development of manufacturing industry at present.In order to overcome the problems of the low-end industrial chain,low production efficiency,high energy consumption,and lack of innovation ability in modern manufacturing,cloud manufacturing came into being.As one of the core problems of cloud manufacturing,the quality of resource scheduling will directly affect the cost,efficiency and quality of cloud manufacturing services.Therefore,this topic carries out relevant research on resource scheduling under cloud manufacturing environment.The main research content is as follows:(1)The research on static resource scheduling under cloud manufacturing.Considering the target and constraint conditions of cloud manufacturing resource scheduling,a multi-objective static resource scheduling model is set up,and an improved genetic algorithm is designed to find the global optimal solution.And compared with the results of traditional models and algorithms,it verifies the applicability of the model and the effectiveness of the algorithm.(2)The research on dynamic resource scheduling under cloud manufacturing.For the dynamic disturbance problem in the cloud manufacturing environment,in this topic,a multi-objective dynamic resource scheduling model is established;And a hybrid-driven dynamic scheduling strategy combining periodic driving and event driving is adopted,which makes re-scheduling to be periodically driven by the scheduling mechanism of the phased sequencing priority rules,and to be Triggered by the driving mechanism of the combination of the delay rate of manufacturing progress with the utilization ratio of manufacturing resources;Subsequently,a simulated annealing-genetic algorithm is used to solve the problem.Finally,a dynamic example is used to verify the applicability and superiority of the dynamic scheduling strategy.