Adaptive MOEA/D for QoS-Based Web Service Composition

QoS aware service composition is one of the main research problem related to

Service Oriented Computing (SOC)

. A certain functionality may be offered by several services having different Quality of Service (QoS) attributes. Although the QoS optimization problem is multiobjective by its nature, most approaches are based on single-objective optimization. Compared to single-objective algorithms, multiobjective evolutionary algorithms have the main advantage that the user has the possibility to select

a posteriori

one of the Pareto optimal solutions. A major challenge that arises is the dynamic nature of the problem of composing web services. The algorithms performance is highly influenced by the parameter settings. Manual tuning of these parameters is not feasible. An evolutionary multiobjective algorithm based on decomposition for solving this problem is proposed. To address the dynamic nature of this problem we consider the hybridization between an adaptive heuristics and the multiobjective algorithm. The proposed approach outperforms state of the art algorithms.