Cluster Computing

, Volume 22, Supplement 2, pp 3673–3680 | Cite as

Study on ant colony optimization algorithm for “one-day tour” traffic line

  • Xiangming MaoEmail author


At present, the tourism industry in China is in a period of rapid development, and the choice of travel route has become an inevitable problem in the tourism industry. In order to reduce the cost of tourism and the impact of traffic pollution on the environment, it is necessary to optimize the choice of the travel route and promote the sustainable development of the tourism industry. Therefore, this paper takes “one day tour” as an example to study the optimization of tourist traffic lines. The objective function of the travel route optimization problem is improved by ant colony algorithm and principal component analysis. It selects ant line randomly and dynamically sets the parameters of heuristic elements, information dispersion coefficient and so on. Thus, the diversity of traffic route selection is guaranteed, and the problem that the ant colony algorithm is easy to reach the local optimal solution is solved easily. It is proved by the MATLAB experiment that the improved ant colony algorithm has greatly improved the performance of route optimization problem of the “one day tour”.


“One day tour” Tourist traffic line Ant colony algorithm Line optimization 


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© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.School of the Humanities & Social SciencesPanzhihua UniversityPanzhihuaChina

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