DOI: 10.3724/SP.J.1016.2013.01031

Chinese Journal of Computers (计算机学报) 2013/36:5 PP.1031-1046

Web Service Composition Based on Modified Particle Swarm Optimization

Web service composition optimization is a typical NP-complete problem. PSO algorithm is widely used in the research field of continuous optimization, but rarely seen in Web service composition problem. In this paper, we propose a new modified particle swarm optimization algorithm called MDPSO based on sub-particle circular orbit and zero-value inertial weight, which is applied in Web service composition optimization problem. MDPSO adopts trigonometric-function-based non-linear dynamic learning factors and a prediction method for population premature convergence, which can keep better balance between the local exploring ability and the global converging ability of particles. Finally, a novel algorithm evaluation method is presented in the experiment. These concepts and methods provide a new thinking route for application researches of WSC problem. Experimental results show that MDPSO algorithm can achieve better performance than traditional PSO algorithms in WSC optimization. Some useful conclusions are obtained through the analysis and explanation of the experimental data, which lay a solid foundation for further researches.

Key words:Web service composition,particle swarm optimization,sub-particle circular orbit,non-linear dynamic learning factor,anti-premature convergence

ReleaseDate:2014-07-21 17:03:11