科研之友
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摘要
The multi-objective service selection problem is a basic problem in Service Computing and it is NP-Hard. This paper proposes a novel Bi-Ant colony optimization (NBACO) algorithm for this problem. Two objective functions related to 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. It uses preposition skyline query (PSQ) algorithm for each service class to reduce the candidate services at the beginning of NBACO. The algorithm has been tested in nine cases and compared to the related MOACO algorithm and Co-Evolution algorithm for this problem. The efficiency of NBACO is greatly improved by using PSQ. The result demonstrates that our approach is effective and better than MOACO and Co-Evolution.
