| In the face of increasingly fierce global market competition and personalized customer needs,traditional manufacturing industry has transformed towards intelligent manufacturing.Cloud manufacturing is the extension and cross-integration of cloud computing and Internet of Things in the manufacturing industry,providing a new model and concept for manufacturing informatization.The scheduling of the cloud manufacturing workshop layer is an important supporting technology for the smooth implementation of the cloud manufacturing scheduling scheme.It is the key how to undertake cloud tasks,coordinate scheduling of own tasks and outsourcing cloud tasks from the perspective of enterprises and make full use of the remaining manufacturing resources in the workshop of the enterprise to helping enterprises enhance their competitiveness and rapid transformation.Aiming at the optimization problem of open shop scheduling in cloud manufacturing environment,this thesis proposes a singleobjective open shop scheduling model based on task priority and a multi-objective flexible open shop scheduling model based on the number of processes.The main research contents was as follows:(1)On the basis of this research,the characteristics of open workshop scheduling and traditional workshop scheduling in cloud manufacturing environment are analyzed,and an open workshop scheduling framework in cloud manufacturing environment is established.(2)Aiming at the open shop scheduling problem in cloud manufacturing,considering the optimization of shop workpiece processing,the collaborative scheduling of workshop production tasks and cloud platform tasks,and comprehensively considering the characteristics of the workshop production tasks and the cloud platform tasks.A mixed integer programming of the open shop in the cloud manufacturing is established,which regards the weighted completion time of the total tasks as the indicators.CPLEX is employed to generate optimal solutions for small-scale simulation experiments,improved mayfly algorithm(IMA)is used to solve large-scale simulation experiments and compared with genetic algorithm(GA),particle swarm algorithm(PSO)and mayfly algorithm(MA).Finally,the effectiveness of the model and improved mayfly algorithm are verified.(3)Flexible open shop scheduling problem presents new problem characteristics in a cloud manufacturing environment.A multi-objective production scheduling model is proposed considering the collaborative scheduling of workshop tasks and cloud platform tasks,energy consumption and utilization of surplus manufacturing resources of the enterprise in the cloud manufacturing environment.The optimization objectives consist of the minimization of total weighted completion time,the minimization of total consumption cost,and the maximization of machine utilization.A two-layer encoding scheme and population evolution strategy are designed based on the multi-objective mayfly algorithm(MMA).A series of random experiments are conducted to demonstrate the effectiveness of the proposed algorithm. |
