Method Towards Service Composition Optimization on Cost-effective using Mixed Flower Pollination Algorithm

Web services have been widely used in various industries in recent years. Faced with a large number of services with the same functions and different quality, Web service composition optimization is an important technical approach for the widespread application of Web services. Most of the existing researches regard the service composition as a single-objective optimization problem, but this does not meet the diverse needs of users. In response to the complex needs of users, quality of service and service cost are chosen as two optimization goals to achieve a cost-effective oriented service composition. For this purpose, a mixed flower pollination algorithm (MFPA) is proposed. In this paper, the original flower pollination algorithm is combined with the fast non-dominated sorting and population selection strategy to solve the Pareto optimal set. In addition, differential evolution strategy and random disturbance strategy are added during the execution of the algorithm to improve the optimization ability. The experimental results show that MFPA has more advantages in the field of service composition with multi-objective optimization than other algorithms for multi-objective optimizations.