An Environment-Aware Particle Swarm Optimization Algorithm for Services Composition

• Published in: 2009 International Conference on Computational Intelligence and Software Engineering pp. 1 - 4
• Main Authors: Long, Jun, Gui, Weihua
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.12.2009
• Subjects: Birds; Constraint optimization; Convergence; Educational institutions; Evolution (biology); Information science; Linear programming; Optimization methods; Particle swarm optimization; Web services
• DOI: 10.1109/CISE.2009.5364842

The service composition composing the existing Web services to form new, satisfying different user requirements and value-added composition service has become new application requirement and popular research. The optimization of services composition is a nonlinear multi-objective optimization problem which has been proven to be NP-complete. It is preponderant to settle the multi-objective optimization using particle swarm optimization (PSO). But services composition that can not adapt complicated variety in general PSO algorithm has slow convergence speed and strict speed demand. The paper simulates the bird flocking environment-aware behavior in seeking food process. 1) Bird flocking orient the later seek food based on the former successful experience to avoid ineffective searching behaviour; 2)Bird flocking which have definite visual field can enough fly far, whilst they needn't local search such as PSO to increase the algorithm speed. It presented an environment-aware particle swarm optimization algorithm(EAPSO). EAPSO decreases unsteadiness resulting from random search and increases algorithm speed by method recollecting optimized population and increasing visual field. The simulation which is in the typical services composition stage shows that EAPSO is faster in convergence and more effective in global search.