Volume 7 Number 5 (May 2012)
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JCP 2012 Vol.7(5): 1191-1195 ISSN: 1796-203X
doi: 10.4304/jcp.7.5.1191-1195

Improved P-hub Network Model and GA Solution Based on Rough Set Theory

Qing Liu1, Tongshui Wu2, Xianfei Luo2
1NanJing University of Aeronautics and Astronautics/College of Civil Aviation, Nanjing, China
2Civil Aviation university of China/College of Economics and Management, Tianjin, China


Abstract—To solve NP-hard 0-1 discrete optimization problems of the uncapacitated multiple allocation p-hub median network (UMpHMP), this paper proposed an improved p-hub network model based on β - approximate rough set data mining technology to reduce the range of hub choice from n alternative hubs to the limited q(q < n) airports, which greatly reduces total number of the variables and constraints for the models. As one of the classical shortest path problems, the genetic algorithm was developed to solve the improved model. In order to illustrate the effective of new model, an experimental example of domestic 15 cities route network designing for airlines was given, the simulation results show the established index number can be abbreviated to 4 main attributes by β - reduction, and the efficiency

Index Terms—P-hub network, UMpHMP, Rough set, Genetic algorithm.

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Cite: Qing Liu, Tongshui Wu, Xianfei Luo, "Improved P-hub Network Model and GA Solution Based on Rough Set Theory," Journal of Computers vol. 7, no. 5, pp. 1191-1195, 2012.

General Information

ISSN: 1796-203X
Abbreviated Title: J.Comput.
Frequency: Monthly
Editor-in-Chief: Prof. Liansheng Tan
Executive Editor: Ms. Nina Lee
Abstracting/ Indexing: DBLP, EBSCO,  ProQuest, INSPEC, ULRICH's Periodicals Directory, WorldCat, CNKI,etc
E-mail: jcp@iap.org
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