A novel Bi-Ant colony optimization algorithm for solving multi-objective service selection problem

The multi-objective service selection problem is a basic problem in Service Computing and is NP-Hard. This paper proposes a novel Bi-Ant colony optimization multi-objective service selection algorithm for this problem. Two objective functions related with response time and cost attributes are considered. For each objective, a heuristic function and a pheromone updating policy are defined against the characteristics of this problem. Then, a combined state transition rule is designed based on them. The algorithm has been tested in nine cases and compared with the related MOACO algorithm for this problem. The result demonstrates that our approach is effective and better than MOACO.