[KSCI] Korea Science Citation Index Service

http://dx.doi.org/10.9708/jksci.2018.23.08.133

Non-periodic Subway Scheduling that Minimizes Operational Cost and Passenger Waiting Time

Hong, YunWoo (Yonsei School of Business, Yonsei University)
Chung, Yerim (Yonsei School of Business, Yonsei University)
Min, YunHong (Graduate School of Logistics, Incheon National University)

Publication Information

Journal of the Korea Society of Computer and Information / v.23, no.8, 2018 , pp. 133-142 More about this Journal

Abstract

Subway metro scheduling is one of the most important problems impacting passenger convenience today. To operate efficiently, the Seoul metro uses regular, periodic schedules for all lanes, both north and southbound. However, many past studies suggest that non-periodic scheduling would better optimize costs. Since the Seoul metro is continuously facing a deficit, adopting a non-periodic schedule may be necessary. Two objectives are presented; the first, to minimize the average passengers' waiting time, and the second, to minimize total costs, the sum of the passenger waiting time, and the operational costs. In this paper, we use passenger smart card data and a precise estimation of transfer times. To find the optimal time-table, a genetic algorithm is used to find the best solution for both objectives. Using Python 3.5 for the analysis, for the first objective, we are able to reduce the average waiting time, even when there are fewer trains. For the second objective, we are able to save about 4.5 thousand USD with six fewer trains.

Keywords

Transfer Passenger; Subway Scheduling; Timetabling; Optimization; Genetic Algorithm; Metro Operating Cost;

Citations & Related Records

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