Optimization of Urban Bus Stations Using Genetic Algorithm and GIS (Case Study: Tehran 6th District)

Document Type : Research Paper

Authors

1 Assisstant professor in Department of Remote Sensing and GIS, College of Geography, University of Tehran

2 Ph.D. Student of Remote Sensing and Geographic Information Systems (GIS), Faculty of Geography, University of Tehran

Abstract

The design of standard bus stations is one of the most important issues that increase bus performance at the stations, reduce the take-off time and take passengers, and less negatively influence the traffic on other vehicles. In this research, we tried to find suitable locations for establishing subway station candidates in the city of Tehran 6 with GIS functions and ANP network analysis decision making. Using genetic algorithm and target functions, we aimed to optimize the candidate stations. In order to increase the accuracy of the research, the study area was divided into two areas of strong and weak concentration of service centers and commercial centers. the results showed that according to the network length and station spacing standards, area 6 requires 306 to 208 stations. Of the 291 stations, 247 stations, and 212 existing stations, 147 stations were optimized they can maximize demand coverage for demographic centers and absorbent centers.

Keywords


Ashtiani, H. Z. and Iravani, H. 2002. “Application of dwell time functions in transit assignment model”. Transportation Research Record, J. Transport. Res. Board, 1817: 88-92.
Baaj, M. H. and Mahmassani, H. S. 1991. “An AI based approach for transit route system planning and design”. J. Adv. Transport., 25(2): 187-210.
Fitzpatrick, K., Hall, K., Perkinson, D., Nowlin, L. and Koppa, R. 1996. “TCRP report 19: Guidelines for the location and design of bus stops”. Transport. Res. Board of the Nat. Acad., Washington, DC.
Goodchild, M. F., Steyaert, L. T. and Parks, B. O. 1996. “GIS and environmental modeling: Progress and research issues”. John Wiley and Sons.
Hall, C. H. 2006. “A framework for evaluation and design of an integrated public transportion”. Institute of Technology, Linkopings University, Norrkping, Sweden.
Huang, Z. and Liu, X. 2014. “A hierarchical approach to optimizing bus stop distribution in large and fast developing cities”. ISPRS Int. J. Geo-Inform., 3(2): 554-564.
Ibeas, Á., dell’Olio, L., Alonso, B., & Sainz, O. (2010). Optimizing bus stop spacing in urban areas. Transportation research part E: logistics and transportation review, 46(3), 446-458.
Lee, L. W. and Kim, S. H. 2000. “Using analytic network process and goal programming for interdependent information system project selection”. Comp. Oper. Res, 27; 367-382.
Saaty, T. L. 1980. The analytic hierarchy process: Planning, priority setting, resource allocation”. McGraw-Hill, New York, 287 p.
Wei, X. 2010. “Optimizing bus stop locations in Wuhan, China”. MSc. Thesis, International Institute for Geo-Information Science and Earth Observation, Enschede, The Netherlands.
Zhu, Z., Guo, X., Chen, H., Zeng, J. and Wu, J. 2017. “Optimization of urban mini-bus stop spacing: A case study of Shanghai (China)”. Tech. Gaz., 24(3): 949-955.