Trust-driven Service Scheduling Optimization In Collaborative Manufacturing

In recent years,with the gradual development of collaborative manufacturing mode,although it brought a new model of rapid and efficient cooperation,still faced with several important issues: the trust crisis between collaborative enterprises,uneven distribution of enterprise benefits and collaborative manufacturing resources can not be reasonably configured etc.In the collaborative process of manufacturing enterprises,the scheduling optimization problem of resource services has become the focus of collaborative enterprises due to the complexity of resources,dynamic and timeliness.However,in the service scheduling optimization,there is little research on the issue of trust.Therefore,the specific work of this paper is as follows:Firstly,based on the trust problem of service in collaborative manufacturing mode,this paper constructs the trust synthesis model of service.Firstly,the trust evaluation model is introduced,and the weight of each attribute of the service is determined by entropy weight method and subjective weighting method.The comprehensive trust value is divided into direct trust value,recommended trust value and QoS feedback trust value.Secondly,according to the interaction between the service entities and the time decay function,calculate the direct trust value.The recommended trust value is calculated by combining the weight similarity between the service user and the service recommender to the service attributes.The QoS feedback trust value of the resource service is reflected by setting both the service availability and the service integrity.Finally,combining the subjective weighting method and the different combination process of service,to calculate the synthetic trust degree of the composite service.Secondly,based on the study of service synthesis trust,this paper proposes a decomposition model of composite service trust value.In order to solve the decomposition of the trust value of the composite service,the AHP method is used to transform the composition service flow into the tree structure process,so as to determine the decomposition weight of each service.And combined with the service error influence,historical performance and the service weight influence of calculating synthesize trust value,to calculate each service's value of trust evaluation.Finally,aiming at the problem of service scheduling optimization in collaborativemanufacturing environment,this paper proposes a new model of service trust composition and decomposition,and combines the scheduling algorithm of service composition to solve.As one of the QoS parameters,the trust is added to the QoS parameters of the service composition,and a trust-driven service scheduling optimization strategy is proposed.In order to verify the feasibility and effectiveness of the scheduling optimization strategy proposed in this paper,we compare it with the discrete particle swarm optimization algorithm.The validity of the service scheduling is verified by analyzing the data of the experimental results,and it is proved that the discrete hybrid leapfrog algorithm is better in solving the combinatorial optimization problem.