Jia Wang This email address is being protected from spambots. You need JavaScript enabled to view it.1 and You Wu1

1Institute of Transportation Engineering, Changsha University of Science & Technology, Changsha 410076, P.R. China


 

Received: January 16, 2017
Accepted: April 26, 2017
Publication Date: March 1, 2018

Download Citation: ||https://doi.org/10.6180/jase.201803_21(1).0007  

ABSTRACT


Urban and rural public transportation is an important link between urban and rural areas. The design of urban and rural public transportation network plays an important role in promoting the integration of urban and rural public transportation. In this paper, the urban and rural public transportation network optimization design considering both space and time constraints is put forward. Using large-scale data technology and internet technology, we determined time and space limits of the public transportation network. Based on the optimization of the direct transit efficiency, the secondary transfer efficiency and the number of lines, the optimization model is constructed. The tabu search algorithm for the model is designed and the efficiency of the algorithm is estimated. The test results show that the algorithm has a fast convergence rate and a stable result. The conclusion of this paper provides a good theoretical support for the rational design of urban and rural public transportation network. It is also conducive to promote the further development of urban and rural public transport.


Keywords: Urban and Rural Transit, Network Optimization, Space-time Constraint, Comprehensive Passenger Transport Hub, Tabu Search Algorithm


REFERENCES


  1. [1] Ramirez, A. I. and Seneviratne, P. N., “Transit Route Design Applications Using Geographic Information System,” Transportation Research Record, Vol. 1557, pp. 1014 (1996). doi: 10.3141/1557-02
  2. [2] Wang, W., Chen, S. Y. and Hu, X. J., “Research on the Method of Bus Traveling Guidance and Dispatching Based on “One Line Direct Line” Bus Mode,” Journal of Southeast University(Natural Science Edition),Vol. 38, No. 6, pp. 11101115 (2008).
  3. [3] Wang, W., Guo, Z. Y. and Chen, X. W., “"One Line Direct Line" Study on the Theoretical Framework of Public Transport System,” Transportation Engineering and Information,Vol.9,No.4,pp.159165(2009).
  4. [4] Patnaik, S. B., Mohan, S. and Tom, V. M., “Urban Bus Transit Route of Bus Routes Network Design Using Genetic Algorithm,” Journal of Transportation Engineering, Vol. 124, pp. 368375 (1998). doi: 10.1061/ (ASCE)0733-947X(1998)124:4(368)
  5. [5] He, S. X. and Fan B. Q., “Optimal Path Searching Algorithm in Transit Network,” Journal of Transportation Engineering and Information, Vol. 5, No. 1, pp. 2227 (2017).
  6. [6] Lee, Y. J. and Vuchic, V. R., “Transit Network Design with Variable Demand,” Journal of Transportation Engineering January, Vol. 131, No. 1, pp. 110 (2005). doi: 10.1061/(ASCE)0733-947X(2005)131:1(1)
  7. [7] Li, Y. F., Gao, Z. Y., Li, J., “Vehicle Routing Problem in Dynamic Urban Network with Real-time Traffic Information,” Systems Engineering-Theory & Practice, Vol. 33, No. 7, pp. 18131819 (2013).
  8. [8] Kaji, T., “Approach by Ant Tabu Agents for Traveling Salesman Problem,”22 IEEE Transactions on Systems Man and Cybernetics (2001). doi: 10.1109/ICSMC. 2001.972050
  9. [9] Kuan, S. N., Ong, H. L. and Ng, K. M., “Solving Feeder Bus Network Design Problem by Genetic Algorithms and Ant Colony Optimization,”Advances in Engineering Soft-ware, Vol. 37, No. 6, pp. 351359 (2006). doi: 10.1016/j.advengsoft.2005.10.003
  10. [10] Wang, T. J. and Wu K. J., “Study on Multi-depot Vehicle Routing Problem with Time Windows Based on Particle Swarm Optimization,”Computer Engineering and Applications, Vol. 48, No. 27, pp. 2730 (2012).
  11. [11] Glover, F., “Future Paths for Integer Programming and Links to Artificial Intelligence,” Computers and Operations Research, Vol. 13, pp. 533549 (1986). doi: 10. 1016/0305-0548(86)90048-1
  12. [12] Xiong, J., Guan, W. and Huang, A. L., “Research on Optimal Routing of Community Shuttle Connect Rail Transit Line,” Journal of Transportation Systems Engineering and Information Technology, Vol. 14, No. 1, pp. 166172 (2014).