Feng Wen
School of Information Science and Engineering, Shenyang Ligong University, Shenyang, China
Xingqiao Wang
School of Information Science and Engineering, Shenyang Ligong University, Shenyang, China
Yang Yu
School of Information Science and Engineering, Shenyang Ligong University, Shenyang, China
ABSTRACT
Multilevel networks methods can speed up the optimal route calculation by preprocessing and pre-computing the original traffic network. This study proposes a Genetic Algorithm based clustering method to construct the multilevel network to improve the existing methods. Three objectives are considered simultaneously including reducing the number of nodes, reducing the number of sections on high level network and reducing the variance between sub-networks. The experimental results show the efficiency of the proposed algorithm in this study.
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How to cite this article
Feng Wen, Xingqiao Wang and Yang Yu, 2013. A Genetic Algorithm Based Clustering Method for Generating Multilevel Traffic Network. Information Technology Journal, 12: 8609-8614.
DOI: 10.3923/itj.2013.8609.8614
URL: https://scialert.net/abstract/?doi=itj.2013.8609.8614
DOI: 10.3923/itj.2013.8609.8614
URL: https://scialert.net/abstract/?doi=itj.2013.8609.8614
REFERENCES
- Hart, P.E., N.J. Nilsson and B. Raphael, 1968. A formal basis for the heuristic determination of minimum cost paths. IEEE Trans. Syst. Cybernet., 4: 100-107.
CrossRefDirect Link - Huang, Z. and M.K. Ng, 1999. A Fuzzy k-Modes algorithm for clustering categorical data. IEEE Trans. Fuzzy Syst., 7: 446-452.
CrossRefDirect Link - Jung, S. and S. Pramanik, 2002. An efficient path computation model for hierarchically structured topographical road maps. IEEE Trans. Knowledge Data Eng., 14: 1029-1046.
Direct Link - Wen, F., S. Mabu and K. Hirasawa, 2011. A genetic algorithm based clustering method for optimal route calculation on multilevel networks. SICE J. Control Measurement Syst. Integration, 4: 83-88.
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