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Article

Optimal Fare Setting for Congestion Mitigation and Revenue Maximization in the Seoul Subway Line 2 Using the Non-dominated Sorting Genetic Algorithm II

NSGA-II를 활용한 서울시 지하철 2호선 혼잡 완화와 수익 증대를 위한 최적 요금 산정

Sungjin YOON1
,
Jooyong LEE2*
윤 성진1
,
이 주용2*
1Student, Department of Urban & Transportation Engineering, College of Creative Engineering, Kyonggi University, Gyeonggi 16227, Korea
2Assistant Professor, Department of Urban & Transportation Engineering, College of Creative Engineering, Kyonggi University, Gyeonggi 16227, Korea
1경기대학교 도시·교통공학과 학사과정
2경기대학교 스마트시티공학부 도시·교통공학전공 조교수
*Corresponding Author
31 October 2025. pp. 667-676
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Abstract

The Seoul Subway is currently experiencing increased social costs and financial deficits due to severe congestion and an inefficient fare structure. In response, this study applies the Non-Dominated Sorting Genetic Algorithm II to determine optimal time-based fares for Seoul Subway Line 2. Non-Dominated Sorting Genetic Algorithm II is a multi-objective optimization technique capable of handling conflicting objectives simultaneously; here, it is used in conjunction with congestion data and fare elasticity to analyze how a variable fare system influences demand. The results show that introducing time-based variable fares can effectively redistribute passengers from congested to less congested periods, while also improving profitability compared to the existing fare system. Moreover, by examining the Pareto front, this study identifies several optimal solutions for the two competing objectives and conducts a detailed comparison of representative solutions that achieve a balance between congestion mitigation and revenue enhancement. These findings enable the proposal of concrete fare strategies that can be adopted when implementing a variable fare system. The significance of this research lies in demonstrating that a time-based variable fare strategy can simultaneously alleviate congestion and enhance financial stability, and it suggests the potential for expansion to other lines or different modes of transportation in the future.

Keywords
congestion mitigation
NSGA-II
revenue enhancement
Seoul Subway Line 2
subway fare

서울시 지하철은 높은 혼잡도와 요금 체계의 비효율성으로 인해 사회적 비용 증가와 재정 적자가 발생하고 있다. 이를 해결하기 위해 본 연구에서는 NSGA-II (Non-dominated Sorting Genetic Algorithm-II)를 활용하여 서울시 지하철 2호선의 시간대별 최적 요금을 산정하였다. NSGA-II는 서로 상충하는 목표를 동시에 고려할 수 있는 다목적 최적화 기법으로, 본 연구에서는 혼잡도 자료와 요금 탄력성 등을 연계하여 차등 요금에 따른 수요 변화를 분석하였다. 그 결과, 차등 요금제를 통해 혼잡한 시간대의 이용객을 비혼잡 시간대로 효과적으로 분산시키는 동시에 기존 요금체계 대비 수익성이 향상되었음을 확인하였다. 또한, 파레토 프런트를 통해 상충하는 두 목표 간의 여러 최적 해를 도출하였으며, 그 중 각 목적을 대표하는 최적 해가 제시하는 혼잡 완화와 수익 증가 간의 균형점을 구체적으로 비교하였다. 이를 통해 차등 요금제 도입 시 적용 가능한 구체적인 요금 설계안을 도출할 수 있다. 본 연구에서는 시간대별 차등 요금제를 도입함으로써 혼잡 완화와 재정적 안정성을 동시에 도모할 수 있음을 보인 점에서 의의가 있으며, 이는 향후 다른 노선 혹은 교통수단으로의 확장 적용 가능성도 시사한다.

키워드
서울시 지하철 2호선
혼잡 완화
수익 증대
지하철 요금
NSGA-II
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Information
  • Publisher :Korean Society of Transportation
  • Publisher(Ko) :대한교통학회
  • Journal Title :Journal of Korean Society of Transportation
  • Journal Title(Ko) :대한교통학회지
  • Volume : 43
  • No :5
  • Pages :667-676
  • Received Date : 2025-04-08
  • Revised Date : 2025-04-16
  • Accepted Date : 2025-05-09
  • DOI :https://doi.org/10.7470/jkst.2025.43.5.667
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