Optimal Grid Service Composition with Fuzzy Constraint and Performance Evaluation

A new method of intelligent optimization to solve grid service composition problem with uncertain time constraints based on fuzzy set is proposed.A fuzzy service time(FST) model is adopted to formalize the uncertain service time and deadline of user.A self-adaptive chaotic control strategy is incorporated into standard genetic algorithm(GA) because it's NP hard to solve FST.Analytical and experimental results showed that the convergence and prematurity of GA may be improved prominently by chaos.According to the improved entropy based performance evaluation strategy,the efficiency and stability of the resulting algorithm outperform the standard GA.