A Hybrid Memetic Approach for Fully Automated Multi-Objective Web Service Composition

Service-oriented architecture (SOA) has been widely employed in the field of software engineering, since it encourages attributes such as modularity and code reusability across different applications. Web service composition, where atomic services that accomplish simple tasks are combined into an application that fulfils a more complex function, is one popular application of SOA. Existing composition works focus on building functional and quality-optimised applications. A subset of these works use multi-objective evolutionary computing techniques to produce a Pareto front of compositions, though they assume that the basic structure of the composition workflow is already known. In our recent work, we removed this assumption by combining NSGA-II with a solution representation that allows for different workflow structures to be investigated. However, the multi-objective nature of the problem made it difficult to apply local search to further improve the results. In this paper we hybridise NSGA-II with MOEA/D, which allows the problem to be decomposed into multiple single-objective subproblems where a simple form of local search can be applied. Experiment results show that the use of local search improves the quality of the fronts produced by the hybrid approach for a number of composition tasks.