Study On Multi-User Oriented Manufacturing Cloud Service Configuration Model And Optimization Method

Manufacturing cloud service selection and scheduling is the core module of the cloud manufacturing system.Facing users’ large-scale manufacturing tasks,an efficient resource allocation management plan plays an extremely important role in the operating efficiency of the cloud manufacturing system.How to optimize the selection of various production resources to meet the differentiated needs of users has important theoretical significance and practical application value for achieving optimized resource allocation and improving the management level of cloud platform operators.Although rich research results have been achieved on the multi-task-oriented manufacturing cloud service configuration model and method in the cloud environment,the existing multi-task-oriented manufacturing cloud service configuration framework is very difficult due to the uncertainty of user preferences and the differences in user needs.It is difficult to meet the actual production requirements,and due to the diversity of the virtual service pool,there are higher requirements for the optimization of the algorithm.Therefore,this paper proposes a multi-user-oriented manufacturing cloud service configuration model based on the multi-task-oriented manufacturing cloud service configuration framework.Based on the multi task oriented manufacturing cloud service configuration framework,this paper proposes a multi-user oriented manufacturing cloud service configuration model.Firstly,in view of the uncertainty of the environment and the ambiguity of multi-user preferences,a multi-user preference-oriented manufacturing cloud service matching recommendation model is established.The dual hesitant fuzzy theory(DHFT)is used to transform the user preferences into the satisfaction degree,and the candidate set of manufacturing cloud services satisfying the user preferences is selected from the massive cloud services.Then,according to the different delivery demand of multi-user,a multi-user dual objective manufacturing cloud service selection and scheduling mathematical model is established with the aim of minimizing total completion time and total cost.Based on the characteristics of the problem,a multi-objective hybrid bee colony algorithm(MOHABC)is designed to solve the problem,a population guidance strategy is used to accelerate the convergence of the algorithm in the hiring bee stage,In the following bee stage,four heuristic search strategies are designed to increase the population diversity.Simulation results show that excellent performance of the MOHABC in convergence and diversity,it can provide high-quality optimization solutions for cloud platform operators.Compared with the multi task oriented manufacturing cloud service configuration model,the multi-user oriented manufacturing service configuration model is more general and explanatory since it integrates user characteristics and considers the coordination between user tasks.The research model and method can improve user satisfaction and provide effective guidance for cloud platform managers to make optimal decisions.The multi-user oriented manufacturing cloud service configuration model and method can improve user satisfaction and provide effective guidance for cloud platform managers to make optimal decisions.For large-scale resource allocation problems,cloud platform managers should focus on users when modeling and optimizing,integrate user characteristics into the model,and design heuristic search strategies according to the problem characteristics for decision-making.