Skip to Main Content
The existing service selection algorithms have defects such as inefficient, non-global optimization. And there are some shortages of particle swarm optimization used in the complex combinatorial optimization problems. In order to overcome the defects, Web services selection which based on user's preference and grouping particle swarm optimization is presented. It can analyze user's gentle preference in Web services. This algorithm in use of particle clustering, improves the global search capability in Web services and avoids rapid convergence or premature. At the same time, making use of fuzzy constraint to express the user's preferences, and ultimately it can enable users to choose from their preferences. Experimental results show that this algorithm can effectively improve the performance of service selection.