Multi-Objective Service Composition Using Enhanced Multi-Objective Differential Evolution Algorithm

In recent years, the optimization of multi-objective service composition in distributed systems has become an important issue. Existing work makes a smaller set Pareto-optimal solutions to represent Pareto Front (PF). However, they do not support complex mapping quality (QoS) objective space, thus having limitations providing representative solutions. We propose enhanced differential evolution algorithm seek with good proximity and distributivity. Specially, we dual strategy adjust usage different creation operators, maintain evolutionary pressure toward true PF. Then, reference vector neighbor search have fine-grained search. The proposed approach been tested on real-world dataset that locates