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IJMLC 2013 Vol.3(1): 44-48 ISSN: 2010-3700
DOI: 10.7763/IJMLC.2013.V3.270

The Optimal Routing of Cars in the Car Navigation System by Taking the Combination of Divide and Conquer Method and Ant Colony Algorithm into Consideration

Pirayeh Yousefi and Roghayeh Zamani

Abstract—Abstract—In this paper we propose an optimal routing method for cars in car navigation system. The proposed method finds the paths with a combination of Divide and Conquer method and Ant Colony algorithm. In order to do this, the road network is divided to small areas. Then the learning operation is done in these small areas. Then different learnt paths are combined together to make the complete paths. This method causes balance and reduces the traffic in lanes of the pathes, because it not only consider lengths of the paths for learning operations, it also considers the other factor which is traffic condition of the lanes of the paths. Consequently this method reduces the average triptime of the cars in comparison with existing Ant Colony, Genetic and Dijkstra algorithms by reducing and balancing of road traffic. Therefore, some improvements in the average traveling time of vehicles are achieved. Also, this results in short and precise paths and learning stage becomes faster.

Index Terms—Ant Colony algorithm, controlling system, car navigation system, Divide and Conquer method, routing algorithm.

The authors are with the Marand Branch, Islamic Azad University, Marand, Iran (e-mail: p_yousefi@marandiau.ac.ir; r_zamani84@yahoo.com).

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Cite:Pirayeh Yousefi and Roghayeh Zamani, "The Optimal Routing of Cars in the Car Navigation System by Taking the Combination of Divide and Conquer Method and Ant Colony Algorithm into Consideration," International Journal of Machine Learning and Computing vol. 3, no. 1, pp. 44-48, 2013.

General Information

  • ISSN: 2010-3700 (Online)
  • Abbreviated Title: Int. J. Mach. Learn. Comput.
  • Frequency: Bimonthly
  • DOI: 10.18178/IJMLC
  • Editor-in-Chief: Dr. Lin Huang
  • Executive Editor:  Ms. Cherry L. Chen
  • Abstracing/Indexing: Scopus (since 2017), Inspec (IET), Google Scholar, Crossref, ProQuest, Electronic Journals Library.
  • E-mail: ijmlc@ejournal.net


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