Optimal Limited-stop Bus Routes Selection Using a Genetic Algorithm and Smart Card Data
place - asia, place - urban, mode - bus, technology - ticketing systems, infrastructure - stop
Limited-stop bus, genetic algorithm, smart card data, multiple regression analysis, public transportation, case study
In recent years, express bus service has come into the spotlight by overcoming slow bus operating speeds while maintaining its accessibility when it operates with local bus services. This study developed an optimal limited-stop bus routes selection (LSBRS) guideline as a scenario-based analysis and compared it with case study results. Smart card data and a genetic algorithm (GA) were used to develop the model with different scenarios. Then, total travel time savings as a result of implementing limited-stop bus service generated by the GA model were computed. The effectiveness of each factor was verified by multiple regression analysis, and the LSBRS methodology was determined. This methodology was applied to Suwon, Korea, as a case study. As a result, travel time savings were estimated to be 9.0–19.0%. The ranking of the total travel time savings proposed by the LSBRS methodology presented a similar tendency with that of the case-study analysis.
Permission to publish the abstract has been given by the Journal of Public Transportation, copyright remains with them.
Ye, Y., Choi, K., & Lee, Y. (2016). Optimal Limited-stop Bus Routes Selection Using a Genetic Algorithm and Smart Card Data. Journal of Public Transportation, Vol.19 (4), pp. 178-198.