# Evaluation of an existing bus network using a transit network optimisation model: a case study of the Hiroshima City Bus network

- 461 Downloads
- 11 Citations

## Abstract

This study evaluates an existing bus network from the perspectives of passengers, operators, and overall system efficiency using the output of a previously developed transportation network optimisation model. This model is formulated as a bi-level optimisation problem with a transit assignment model as the lower problem. The upper problem is also formulated as bi-level optimisation problem to minimise costs for both passengers and operators, making it possible to evaluate the effects of reducing operator cost against passenger cost. A case study based on demand data for Hiroshima City confirms that the current bus network is close to the Pareto front, if the total costs to both passengers and operators are adopted as objective functions. However, the sensitivity analysis with regard to the OD pattern fluctuation indicates that passenger and operator costs in the current network are not always close to the Pareto front. Finally, the results suggests that, regardless of OD pattern fluctuation, reducing operator costs will increase passenger cost and increase inequity in service levels among passengers.

## Keywords

Bi-level optimisation formulation Existing bus network Numbered ticket-based travel demand data Transit assignment model Transit network configuration Frequency design## Notes

### Acknowledgments

This research was supported by a Grant-in-Aid for Scientific Research for Young Scientists (20760349) from the Japan Society for the Promotion of Science. The authors also thank Hiroshima City and the private bus companies for providing the data. We also thank three anonymous reviewers and the guest editors for insightful comments.

## References

- Beltran, B., Carrese, S., Cipriani, E., Petrelli, M.: Transit network design with allocation of green vehicles: a genetic algorithm approach. Transp. Res. C
**17**, 475–483 (2009)CrossRefGoogle Scholar - Boschmann, E.E., Kwan, M.P.: Toward socially sustainable urban transportation: progress and potentials. Int. J. Sustain. Transp.
**2**(3), 138–157 (2008)CrossRefGoogle Scholar - Deb, K., Agrawal, S., Pratap, A., Meyarivan, T.: A fast elitist non-dominated sorting genetic algorithm for multi-objective optimization: NSGA-II. In: Schoenauer, M. et al. (eds.) Parallel Problem Solving from Nature VI (PPSN-VI), pp. 849–858 (2000)Google Scholar
- Feng, T., Zhang, J., Fujiwara, A.: Comparison of transportation network optimization with different equity measures using bilevel programming approach. In: Proceedings of the 88th Annual Meeting of TRB, Washington, DC, DVD-ROM (2009)Google Scholar
- Gao, Z.Y., Sun, H., Shan, L.L.: A continuous equilibrium network design model and algorithm for transit systems. Transp. Res. B
**38**, 235–250 (2004)CrossRefGoogle Scholar - Guan, J.F., Yang, H., Wirasinghe, S.C.: Simultaneous optimization of transit line configuration and passenger line assignment. Transp. Res. B
**40**, 885–902 (2006)CrossRefGoogle Scholar - Ibeas, A., Dell’Olio, L., Alonso, B., Sainz, O.: Optimizing bus stop spacing in urban areas. Transp. Res. E
**46**, 446–458 (2010)CrossRefGoogle Scholar - Inagaki, J., Hasegawa, M., Kitajima, H.: A method of determining various solutions for routing application with a genetic algorithm. Trans. Inst. Electron. Inform. Commun. Eng.
**J82- D-I**(8), 1102–1111 (1999) (in Japanese)Google Scholar - Kepaptsoglou, K., Karlaftis, M.: Transit route network design problem: review. J. Transp. Eng. ASCE
**135**(8), 491–505 (2009)CrossRefGoogle Scholar - Kurauchi, F., Bell, M.G.H., Schmöcker, J.-D.: Capacity constrained transit assignment with common lines. J. Math. Modell. Algorithms
**2–4**, 309–327 (2003)CrossRefGoogle Scholar - Kurauchi, F., Hirai, M., Iida, Y.: Experimental analysis on mode choice behaviour for merged public transport systems. In: Proceedings of Infrastructure Planning Conference on Civil Engineering, 30, CD-ROM (Japanese) (2004)Google Scholar
- Nachtigall, K., Jerosch, K.: Simultaneous network line planning and traffic assignment. In: Fischetti M., Widmayer P. (eds.) ATMOS 2008: 8th Workshop on Algorithmic Approaches for Transportation Modeling, Optimization, and Systems, Dagstuhl, Germany (2008). http://drops.dagstuhl.de/opus/volltexte/2008/1589
- Petrelli, M.: A transit network design model for urban areas. In: Brebbia, C.A., Wadhwa, L.C. (eds.) Urban Transport X, pp. 163–172. WIT Press, UK (2004)Google Scholar
- Prabhat, S., Margaret, O.: A model for developing of optimized feeder routes and coordinated schedule: a genetic algorithm approach. Transp. Policy
**13**, 413–425 (2006)CrossRefGoogle Scholar - Shimamoto, H., Kurauchi, F., Iida, Y., Bell, M.G.H., Schmöcker, J.-D.: Evaluation of public transit congestion mitigation measures using passenger assignment model. J. East. Asia Transp. Stud.
**6**, 2076–2091 (2005)Google Scholar - Shimamoto, H., Kurauchi, F., Schmöcker, J.-D., Bell, M.G.H.: Optimisation of bus network configuration and frequency using transit assignment model. Transp. Res. C (2010) (submitted)Google Scholar
- Sumalee, A.: An innovative approach to option generation for road user charging scheme design: constrained and multi-criteria design. In: Proceedings of the 10
^{th}World Conference on Transportation Research, Istanbul, CD-ROM (2004)Google Scholar - Victoria Transport Policy Institute: Equity evaluation: perspectives and methods for evaluating the equity impact of transportation decisions. On-line TDM Encyclopedia (2010). http://www.vtpi.org/tdm/tdm13.htm. Accessed April 2010
- Viegas, J.M.: Making urban road pricing acceptable and effective: search for quality and equity in urban mobility. Transp. Policy
**8**, 289–294 (2001)CrossRefGoogle Scholar - Yang, Z., Yu, B., Cheng, C.: A parallel ant colony algorithm for bus network optimization. J. Comput. Aided Civil Infrastruct. Eng.
**22**, 44–55 (2007)CrossRefGoogle Scholar - Zhou, J., Lam, W.H.K.: A bi-level programming approach—optimal transit fare under line capacity constraints. J. Adv. Transp.
**35**, 105–124 (2000)CrossRefGoogle Scholar