Research On Service Composition And Resource Scheduling Optimization For Cloud Manufacturing

With the rapid development of the Internet Economy,Economic Globalization and competition in the global market have entered a new stage.The manufacturing industry is in the dilemma of idle resources,high manufacturing costs of development,affected by many factors,such as relevant business models,manufacturing complexity,resource,environmental constraints and so on.Cloud Manufacturing is a new service-oriented,efficient,low-consumption and information-based intelligent networked manufacturing model to deal with the difficulties of the manufacturing industry Recently,there are many achievements in the research of manufacturing service composition on the demand side and manufacturing resource scheduling on the supply side of Cloud Manufacturing,However,few scholars have studied the problem of collaborative optimization of both sides in cloud manufacturing.In the Cloud Manufacturing scenario,only when the service composition on the demand side of Cloud Manufacturing and the resource scheduling problem on the supply side are solved completely,can we improve the resource utilization rate and maximize the benefit of enterprise manufacturing resources.Based on intelligent computing technology and service composition theory,this paper focuses on the modeling and solution of supply side and demand side of Cloud Manufacturing platformsFirst of all,on the demand side,aiming at solving the problems of the ignored potential relationship between Cloud Manufacturing services,lack of rationality of the service composition model and lack of effective improvement of service quality,the evaluation mechanism of Cloud Manufacturing service cooperation level is established and incorporated into the service composition optimization model as an optimization goal.Then a Cloud Manufacturing service composition optimization model based on service cooperation level is proposed.The simulation results show that CMSC-SCL can not only reduce the cost and time of Cloud Manufacturing,but also improve the reliability of Cloud Manufacturing productsSecondly,on the supply side,aiming at solving the problem of low real-time performance and low resource utilization in the process of Cloud Manufacturing resource scheduling,this paper studies the manufacturing resource scheduling problem in Cloud Manufacturing environment based on an intelligent optimization algorithm.Then a novel green Cloud Manufacturing resource scheduling model is constructed,which makes the Cloud Manufacturing process greener,more economical and more efficientFinally,the service composition and resource scheduling on both the supply side and demand side of the Cloud Manufacturing platform are studied collaboratively so that we construct a Bilateral-oriented Collaborative Optimization Model of Cloud Manufacturing(BCOM-CMfg).In addition,A Self-adaptive Multi-objective Pigeon-inspired Optimization(S-MOPIO)is proposed to solve the bilateral-oriented collaborative optimization model.The experimental results show that S-MOPIO can effectively solve the collaborative optimization model,which improves the reliability of the Cloud Manufacturing scheme and reduce manufacturing cost...