Optimisation of a Bus Network Configuration and Frequency Considering the Common Lines Problem

Abstract

Public transportation network reorganisation can be a key measure in designing more efficient networks and increasing the number of passengers. To date, several authors have proposed models for the “transit route network design problem” (TRNDP), and many of them use a transit assignment model as one component. However, not all models have considered the “common lines problem,” which is an essential feature in transit network assignment and is based on the concept that the fastest way to get to a destination is to take the first vehicle arriving among an “attractive” set of lines. Thus, we sought to reveal the features of considering the common lines problem by comparing results with and without considering the problem in a transit assignment model. For comparison, a model similar to a previous one was used, formulated as a bi-level optimisation problem, the upper problem of which is described as a multi-objective problem. As a result, although the solutions with and without considering the common lines showed almost the same Pareto front, we confirmed that a more direct service is provided if the common lines problem is considered whereas a less direct service is provided if it is not. With a small network case study, we found that considering the common lines problem in the TRNDP is important as it allows operators to provide more direct services.

Share and Cite:

H. Shimamoto, J. Schmöcker and F. Kurauchi, "Optimisation of a Bus Network Configuration and Frequency Considering the Common Lines Problem," Journal of Transportation Technologies, Vol. 2 No. 3, 2012, pp. 220-229. doi: 10.4236/jtts.2012.23024.

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1] J. Zhou, and W. H. K. Lam., “A BiLevel Programming Approach—Optimal Transit Fare under Line Capacity Constraints,” Journal of Advanced Transportation, Vol. 35, No. 2, 2000, pp. 105124. doi:10.1002/atr.5670350204
[2] H. Shimamoto, et al., “Evaluation of Public Transit Congestion Mitigation Measures Using Passenger Assignment Model,” Journal of Eastern Asia Transportation Studies, Vol. 6, 2005, pp. 20762091.
[3] Z. Y. Gao, et al., “A Continuous Equilibrium Network Design Model and Algorithm for Transit Systems,” Transportation Research Part B, Vol. 38, No. 3, 2004, pp. 235250. doi:10.1016/S01912615(03)000110
[4] K. Kepaptsoglou and M. Karlaftis, “Transit Route Network Design Problem: Review,” Journal of Transportation EngineeringASCE, Vol. 135, No. 8, 2009, pp. 491 505. doi:10.1061/(ASCE)0733947X(2009)135:8(491)
[5] Z. Yang, et al., “A Parallel Ant Colony Algorithm for Bus Network Optimization,” Journal of ComputerAided Civil and Infrastructure Engineering, Vol. 22, No. 1, 2007, pp. 4455. doi:10.1111/j.14678667.2006.00469.x
[6] M. Petrelli, “A Transit Network Design Model for Urban Areas,” In: C. A. Brebbia and L. C. Wadhwa, Eds., Urban Transport X, WIT Press, Southampton, 2004, pp. 163172.
[7] J. F. Guan, et al., “Simultaneous Optimization of Transit Line Configuration and Passenger Line Assignment,” Transportation Research Part B, Vol. 40, No. 10, 2006, pp. 885902. doi:10.1016/j.trb.2005.12.003
[8] K. Nachtigall and K. Jerosch, “Simultaneous Network Line Planning and Traffic Assignment,” 2008. http://drops.dagstuhl.de/opus/volltexte/2008/1589
[9] B. Beltran, et al., “Transit Network Design with Allocation of Green Vehicles: A Genetic Algorithm Approach,” Transportation Research Part C, Vol. 17, No. 5, 2009, pp. 475483. doi:10.1016/j.trc.2009.04.008
[10] H. Shimamoto, et al., “Evaluation of an Existing Bus Network Using a Transit Network Optimisation Model: A Case Study of the Hiroshima City Bus Network,” Trans portation, Vol. 37, No. 5, 2010, pp. 801823. doi:10.1007/s1111601092976
[11] F. Kurauchi, et al., “Capacity Constrained Transit As signment with Common Lines,” Journal of Mathematical Modelling and Algorithms, Vol. 2, No. 4, 2003, pp. 309 327. doi:10.1023/B:JMMA.0000020426.22501.c1
[12] H. Spiess and M. Florian, “Optimal Strategies: A New Assignment Model for Transit Networks,” Transportation Research Part B, Vol. 23, No. 2, 1989, pp. 83102. doi:10.1016/01912615(89)900349
[13] K. Deb, et al., “Fast Elitist NonDominated Sorting Genetic Algorithm for MultiObjective Optimization: NSGA II,” Parallel Problem Solving from Nature VI (PPSNVI), 2000, pp. 849858.
[14] J. Inagaki, et al., “A Method of Determining Various Solutions For Routing Application with a Genetic Algorithm (in Japanese),” Transactions of the Institute of Electronics, Information and Communication Engineers, Vol. 82, No. 8, 1999, pp. 11021111.
[15] F. Kurauchi, et al., “Experimental Analysis on Mode Choice Behaviour for Merged Public Transport Systems (CDRom, in Japanese),” Proceedings of Infrastructure Planning Conference on Civil Engineering, Vol. 30, 2004.

Copyright © 2024 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.