J4 ›› 2013, Vol. 35 ›› Issue (3): 103-107.
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ZHAO Wei1,CAI Xingsheng1,2,QU Huiyan1
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Abstract:
An fast ant colony algorithm solving traveling salesman problem is presented. Firstly, this paper gives a new pheromone updating model. It reduces the complexity of the search process, improves the accuracy of the route searching. Secondly, by setting penalty function, to exclude irrelevant path so that the narrow scope of the search process. Experiments show that, this algorithm can get better optimal solution, and improve the convergence speed significantly.
Key words: ant colony algorithm;traveling salesman problem;pheromone updating;penalty function
ZHAO Wei1,CAI Xingsheng1,2,QU Huiyan1. An ant colony algorithm based on penalty function and new pheromone updating [J]. J4, 2013, 35(3): 103-107.
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http://joces.nudt.edu.cn/EN/Y2013/V35/I3/103