Jigsaw inspired metaheuristic for selecting the optimal solution in web service composition

Abstract

This paper presents a new metaheuristic for selecting the optimal or near-optimal solution in semantic web service composition. The metaheuristic proposed here is inspired from the jigsaw cooperative learning strategy, which was successfully applied in the student learning process. The search space is modeled as an enhanced planning graph structure which encodes all the web service composition solutions for a given user request. To evaluate the quality of a solution, we use a fitness function that considers as evaluation criteria the QoS attributes and the semantic quality. We evaluated our jigsaw inspired metaheuristic on a set of scenarios with different complexities.