| Ant coloy algorithm is a new heuristic algorithm, which shows several characteristics such as positive feedback makes it easier to find better solutions. Simulations demonstrate that it is a robust algorithm base on population and a promising way for optimization.Which is successfully used to solve some NP-Hard combinatorialoptimization problems through simulating the process of ants searching for food. This contribution presents the principe , the charactertics, the construction and reauzation method about the basic modle AS(Ant System) of the ant colony algorithm. Expermental analyses are carried out on the reasonable selection on the parameters of this algorithm and basic principles for the parameter selection are provided, but ant colony algorithm has much deficiency,specially it is easy to fall into the local best, its calculation is complicated and its shortcoming in solving the continual-space problem. This paper in accordance with relevant extension principles on this issue by improving.Extension is a theoretical and methodological science of researching and dealing with incompatiatible problem, which is the transverse science throughout the natural science and social science. It is the laws and methods from the perspective of qualitative and quantitative study on the two issues to resolve contradictions by using formal tools. As with the relationship between the number of forms, there is room for the existence of mathematics, there extension of the battlefield. Therefore this paper is try to solve the contradiction in the selction of the ant colony algorithm parameters by using extension. By application of add-and-delete, expand-and-reduce, separate extension transformation in extension to adjust the important parameters of the ant coloy algorithm. Thus it is an effective solution to solve the contradictions in the algorithm. The simalations for TSP problem shows that the improved algorithm can find better paths at higher convergence speed. |
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