Comparison of Public Transport Network Design Methodologies Using Solution-Quality Evaluation
This article has been corrected.
VIEW CORRECTIONPublication: Journal of Transportation Engineering, Part A: Systems
Volume 144, Issue 8
Abstract
Because of the expected shift from ordinary to autonomous vehicles, the role of public transport (PT) will have to be enhanced, and thus there is a need to pay more attention to its design procedures and evaluation processes. This study compares previous models and methodologies by creating a quality-evaluation platform that enables a comparison of their solution qualities. The evaluation framework developed consists of an integration component between the criteria and objectives of the passengers, the agencies, and the authorities. A set of performance indicators is selected from the literature to build an evaluation rating system. Existing benchmark networks are adopted in the numerical experiments, and interesting findings are obtained. The evaluation results reveal that the quality of the solutions declines with an increase in the network size, and for large networks, the consideration of an unlimited capacity of transport modes is too simplified; this points to the need for a layer-by-layer analysis. In addition, this study shows the level of importance in making transfers. The methodology developed can help planners to improve and design better PT networks.
Get full access to this article
View all available purchase options and get full access to this article.
Acknowledgments
This work was financially supported by the Singapore National Research Foundation under its Campus for Research Excellence and Technological Enterprise (CREATE) program. The authors thank Prof. Avishai (Avi) Ceder, whose comments and insightful suggestions improved the direction and presentation of this paper. The authors also thank anonymous reviewers for their valuable comments.
References
Arbex, R. O., and C. B. da Cunha. 2015. “Efficient transit network design and frequencies setting multi-objective optimization by alternating objective genetic algorithm.” Transp. Res. Part B: Methodol. 81: 355–376. https://doi.org/10.1016/j.trb.2015.06.014.
Baaj, M. H., and H. S. Mahmassani. 1991. “An AI-based approach for transit route system planning and design.” J. Adv. Transp. 25 (2): 187–209. https://doi.org/10.1002/atr.5670250205.
Baaj, M. H., and H. S. Mahmassani. 1995. “Hybrid route generation heuristic algorithm for the design of transit networks.” Transp. Res. Part C: Emerging Technol. 3 (1): 31–50. https://doi.org/10.1016/0968-090X(94)00011-S.
Bagloee, S. A., and A. Ceder. 2011. “Transit-network design methodology for actual-size road networks.” Transp. Res. Part B: Methodol. 45 (10): 1787–1804. https://doi.org/10.1016/j.trb.2011.07.005.
Buba, A. T., and L. S. Lee. 2016. “Differential evolution for urban transit routing problem.” J. Comput. Commun. 4 (14): 11–25. https://doi.org/10.4236/jcc.2016.414002.
Carrese, S., and S. Gori. 2002. “An urban bus network design procedure.” In Transportation planning, edited by M. Patriksson and M. Labbé, 177–195. Boston, MA: Springer.
Ceder, A. 2016. Public transit planning and operation: Modeling, practice and behavior. Boca Raton, FL: CRC Press.
Ceder, A., and N. Wilson. 1986. “Bus network design.” Transp. Res. Part B: Methodol. 20 (4): 331–344. https://doi.org/10.1016/0191-2615(86)90047-0.
Chakroborty, P., and T. Wivedi. 2002. “Optimal route network design for transit systems using genetic algorithms.” Eng. Optim. 34 (1): 83–100. https://doi.org/10.1080/03052150210909.
Chew, J. S. C., L. S. Lee, and H. V. Seow. 2013. “Genetic algorithm for biobjective urban transit routing problem.” J. Appl. Math. 2013: 1–15. https://doi.org/10.1155/2013/698645.
Dijkstra, E. 1959. “A note on two problems in connexion with graphs.” Numerische Mathematik 1 (1): 269–271. https://doi.org/10.1007/BF01386390.
Fan, L., and C. L. Mumford. 2008. “A metaheuristic approach to the urban transit routing problem.” J. Heuristics 16 (3): 353–372. https://doi.org/10.1007/s10732-008-9089-8.
Fan, L., C. L. Mumford, and D. Evans. 2009. “A simple multi-objective optimization algorithm for the urban transit routing problem.” In Proc., 2009 IEEE Congress on Evolutionary Computation, 1–7. New York: IEEE.
Fan, W., and R. B. Machemehl. 2006. “Optimal transit route network design problem with variable transit demand: Genetic algorithm approach.” J. Transp. Eng. 132 (1): 40–51. https://doi.org/10.1061/(ASCE)0733-947X(2006)132:1(40).
Farahani, R. Z., E. Miandoabchi, W. Y. Szeto, and H. Rashidi. 2013. “A review of urban transportation network design problems.” Eur. J. Oper. Res. 229 (2): 281–302. https://doi.org/10.1016/j.ejor.2013.01.001.
Floyd, R. W. 1962. “Algorithm 97: Shortest path.” Commun. ACM 5 (6): 344–345. https://doi.org/10.1145/367766.368166.
Guihaire, V., and J.-K. Hao. 2008. “Transit network design and scheduling: A global review.” Transp. Res. Part A: Policy Pract. 42 (10): 1251–1273. https://doi.org/10.1016/j.tra.2008.03.011.
Gundaliya, P. J., P. Shrivastava, and P. L. Dhingra. 2000. Model for simultaneous routing and scheduling using genetic algorithm. Trieste, Italy: EUT Edizioni Università di Trieste.
Hosapujari, A. B., and A. Verma. 2013. “Development of a hub and spoke model for bus transit route network design.” Procedia-Social Behav. Sci. 104 (4): 835–844. https://doi.org/10.1016/j.sbspro.2013.11.178.
Ibarra-Rojas, O. J., F. Delgado, R. Giesen, and J. C. Muñoz. 2015. “Planning, operation, and control of bus transport systems: A literature review.” Transp. Res. Part B: Methodol. 77: 38–75. https://doi.org/10.1016/j.trb.2015.03.002.
Kechagiopoulos, P. N., and G. N. Beligiannis. 2014. “Solving the urban transit routing problem using a particle swarm optimization based algorithm.” Appl. Soft Comput. J. 21: 654–676. https://doi.org/10.1016/j.asoc.2014.04.005.
Kepaptsoglou, K., and M. Karlaftis. 2009. “Transit route network design problem: Review.” J. Transp. Eng. 135 (8): 491–505. https://doi.org/10.1061/(ASCE)0733-947X(2009)135:8(491).
Kidwai, F. A. 1998. Optimal design of bus transit network: Genetic algorithm approach. Kanpur, India: Indian Institute of Technology.
Kiliç, F., and M. Gök. 2014. “A demand based route generation algorithm for public transit network design.” Comput. Oper. Res. 51 (Nov): 21–29. https://doi.org/10.1016/j.cor.2014.05.001.
Kuo, Y. 2014. “Design method using hybrid of line-type and circular-type routes for transit network system optimization.” Top 22 (2): 600–613.
Lam, W. H. K., and M. G. H. Bell. 2002. Advanced modeling for transit operations and service planning. Bingley, West Yorkshire, UK: Emerald Group Publishing.
Lee, Y., and V. Vuchic. 2005. “Transit network design with variable demand.” J. Transp. Eng. 131 (1): 1–10. https://doi.org/10.1061/(ASCE)0733-947X(2005)131:1(1).
Liu, T., A. Ceder, J. Ma, and W. Guan. 2014a. “CBVC-B: A system for synchronizing public-transport transfers using vehicle-to-vehicle communication.” Procedia-Soc. Behav. Sci. 138: 241–250. https://doi.org/10.1016/j.sbspro.2014.07.201.
Liu, T., A. Ceder, J. Ma, and W. Guan. 2014b. “Synchronizing public transport transfers by using intervehicle communication scheme: Case study.” Transp. Res. Rec. 2417: 78–91. https://doi.org/10.3141/2417-09.
Majima, T., K. Takadama, D. Watanabe, and M. Katuhara. 2014. “Application of community detection method to generating public transport network.” In Proc., 8th Int. Conf. on Bio-Inspired Information and Communications Technologies (formerly BIONETICS), ACM, 243–250. Brussels, Belgium: Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering.
Majima, T., K. Takadama, D. Watanabe, and M. Katuhara. 2015. “Characteristic of passenger’s route selection and generation of public transport network.” SICE J. Control Meas. Syst. Integration 8 (1): 67–73. https://doi.org/10.9746/jcmsi.8.67.
Mandl, C. 1980. “Evaluation and optimization of urban public transportation networks.” Eur. J. Oper. Res. 5 (6): 396–404. https://doi.org/10.1016/0377-2217(80)90126-5.
Mumford, C. L. 2013. “New heuristic and evolutionary operators for the multi-objective urban transit routing problem.” In Proc., 2013 IEEE Congress on Evolutionary Computation, 939–946. New York: IEEE.
Mumford, C. L. 2016. Supplementary material for: New heuristic and evolutionary operators for the multi-objective urban transit routing problem, CEC 2013. Cancun, Mexico: IEEE.
Nakanishi, Y. 2003. A guidebook for developing a transit performance-measurement system. Washington, DC: National Research Council.
Nayeem, M. A., M. K. Rahman, and M. S. Rahman. 2014. “Transit network design by genetic algorithm with elitism.” Transp. Res. Part C: Emerging Technol. 46: 30–45. https://doi.org/10.1016/j.trc.2014.05.002.
Ngamchai, S., and D. J. Lovell. 2003. “Optimal time transfer in bus transit route network design using a genetic algorithm.” J. Transp. Eng. 129 (5): 510–521. https://doi.org/10.1061/(ASCE)0733-947X(2003)129:5(510).
Nikolić, M., and D. Teodorović. 2013. “Transit network design by Bee Colony Optimization.” Expert Syst. Appl. 40 (15): 5945–5955. https://doi.org/10.1016/j.eswa.2013.05.002.
Nikolić, M., and D. Teodorović. 2014. “A simultaneous transit network design and frequency setting: Computing with bees.” Expert Syst. Appl. 41 (16): 7200–7209. https://doi.org/10.1016/j.eswa.2014.05.034.
Ortuzar, J., and L. Willumsen. 1994. Modelling transport. Chichester, UK: Wiley.
Owais, M., G. Moussa, Y. Abbas, and M. El-Shabrawy. 2014. “Simple and effective solution methodology for transit network design problem.” Int. J. Comput. Appl. 89 (14): 32–40. https://doi.org/10.5120/15702-4681.
Pattnaik, S. B., S. Mohan, and V. M. Tom. 1998. “Urban bus transit route network design using genetic algorithm.” J. Transp. Eng. 124 (4): 368–375. https://doi.org/10.1061/(ASCE)0733-947X(1998)124:4(368).
Shih, M. C., and H. S. Mahmassani. 1994. Design methodology for bus transit networks with coordinated operations. Austin, TX: Texas Univ.
Szeto, W. Y., and Y. Wu. 2011. “A simultaneous bus route design and frequency setting problem for Tin Shui Wai, Hong Kong.” Eur. J. Oper. Res. 209 (2): 141–155. https://doi.org/10.1016/j.ejor.2010.08.020.
Talbi, E. 2009. Metaheuristics: From design to implementation. Hoboken, NJ: Wiley.
Tom, V., and S. Mohan. 2003. “Transit route network design using frequency coded genetic algorithm.” J. Transp. Eng. 129 (2): 186–195. https://doi.org/10.1061/(ASCE)0733-947X(2003)129:2(186).
Ul Abedin, Z., F. Busch, A. Rau, D. Z. W. Wang, and B. Du. 2017. “Input and experimental results files.” Accessed July 25, 2017. https://drive.google.com/open?id=0B_c5-eYXj3_YS0VxMlFZNzlTU2c.
Vuchic, V. R. 2005. Urban transit: Operations, planning and economics. Hoboken, NJ: Wiley.
Yen, J. Y. 1971. “Finding the K shortest loopless paths in a network.” Manage. Sci. 17 (11): 712–716. https://doi.org/10.1287/mnsc.17.11.712.
Zhang, J., H. Lu, and L. Fan. 2010. “The multi-objective optimization algorithm to a simple model of urban transit routing problem.” In Proc., 6th Int. Conf. on Natural Computation, 2812–2815. Yantai, China: IEEE.
Zhao, F., and X. Zeng. 2006. “Optimization of transit network layout and headway with a combined genetic algorithm and simulated annealing method.” Eng. Optim. 38 (6): 701–722. https://doi.org/10.1080/03052150600608917.
Zhao, F., and X. Zeng. 2007. “Optimization of user and operator cost for large-scale transit network.” J. Transp. Eng. 133 (4): 240–251. https://doi.org/10.1061/(ASCE)0733-947X(2007)133:4(240).
Zhao, H., and R. Jiang. 2015. “The Memetic algorithm for the optimization of urban transit network.” Expert Syst. Appl. 42 (7): 3760–3773. https://doi.org/10.1016/j.eswa.2014.11.056.
Information & Authors
Information
Published In
Journal of Transportation Engineering, Part A: Systems
Volume 144 • Issue 8 • August 2018
Copyright
©2018 American Society of Civil Engineers.
History
Received: Jul 28, 2017
Accepted: Feb 1, 2018
Published online: May 26, 2018
Published in print: Aug 1, 2018
Discussion open until: Oct 26, 2018
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.