A VOP-based Value Analysis and Optimization Method for Service Selection and Composition

Service selection and composition are important issues to realize IT-enabled service systems. Service stakeholders obtain different service values in the solutions of service selection and composition with the same function but different QoS. The service value achieved from service systems is a critical factor to evaluate and to select the suitable services for the solution of service selection and composition. A value analysis and optimization method for service selection and composition based on value-oriented priority (VOP) is presented in this paper. Firstly, the quantitative analysis method of VOP-based service elements is presented, which includes value contribution analysis, sensitivity analysis and trade-off point analysis. Then the value optimization model for minimal cost is given for solving the problems between expected service values and the constraints of service systems. In order to solve this service value optimization problem, a VOP-based artificial bee colony (VOPABC) algorithm is proposed. Finally, the validity of VOPABC algorithm is proved through simulation experiments.