An ant colony optimization algorithm for selection problem

To tackle the QoS-based service selection problem, an efficient ant colony service selection algorithm called CASS is proposed in this paper. In this algorithm, a skyline query process is used to filtering the candidates related each service class and a clustering based shrinking process is used to guide the ant search directions. We evaluate our approach experimentally using standard real datasets and synthetically generated datasets, and compared with the recently proposed related service selection algorithms. It reveals very encouraging results in terms of the quality of solution, and the processing time required.