出版社：The Japanese Society for Artificial Intelligence
摘要：In this paper, we propose the c AS, a new ACO algorithm, and evaluate the performance using TSP instances available at TSPLIB. The results show that c AS works well on the test instances and has performance that may be one of the most promising ACO algorithms. We also evaluate c AS when it is combined with LK local search heuristic using larger sized TSP instances. The results also show promising performance. c AS introduced two important schemes. One is to use the colony model divided into units, which has a stronger exploitation feature while maintaining a certain degree of diversity among units. The other is to use a scheme, we call cunning, when constructing new solutions, which can prevent premature stagnation by reducing strong positive feedback to the trail density.
关键词：ant colony optimization ; traveling salesman problem ; cunning ant ; donor ant ; local search
