A MULTI-CRITERIA EVALUATION FRAMEWORK FOR ALTERNATIVE MARMARAY TIMETABLE STRATEGIES UNDER FUZZY PASSENGER DEMAND

Vildan Kistik; Tuncay Can

doi:10.29228/JORE.59

A MULTI-CRITERIA EVALUATION FRAMEWORK FOR ALTERNATIVE MARMARAY TIMETABLE STRATEGIES UNDER FUZZY PASSENGER DEMAND

Abstract

In Istanbul, a metropolitan city characterized by intense traffic congestion, it is critically important to effectively meet passenger demand in order to provide a more comfortable and efficient transportation service. The Marmaray Line, as one of the most significant alternative rail systems designed to alleviate urban traffic congestion, has experienced a continuous increase in passenger capacity. Therefore, optimizing its operational performance has become essential. In this study, as an alternative to the existing timetable of the Marmaray Line, station congestion rates, train loading ratios, and passenger volume parameters were calculated using the indices defined within the study framework. Based on the projections obtained from these calculations, a new timetable was developed by incorporating fuzzy alighting and boarding rates instead of deterministic passenger flow assumptions. Subsequently, the timetable was improved through the formulation of an appropriate objective function and relevant constraints in order to obtain a superior alternative strategy vector. The proposed model was further solved using a Genetic Algorithm approach to enhance solution quality and robustness. The findings indicate that the proposed alternative scheduling strategy outperforms the existing system in terms of congestion reduction, capacity utilization, and overall operational efficiency

Keywords

References

Amit, I., & Goldfard, D. (1971). The Timetable Problem for Railways, Development in Operations Research,. Gordon and Breach, New York, 379-387.
Barrena, E., Coelho, D. C., & Laporte, G. (2014). Single-Line Rail Rapid Transit Timetabling Under Dynamic Passenger Demand. Transportation Research Part B: Methodological, 134-150.
Binder, S., Maknoon, Y., & Bierlaire, M. (2017). he Multi-Objective Railway Timetable Rescheduling Problem. Transportation Research Part C: Emerging Technologies, 78-94.
Cacchiani, V., Caprara, A., & Fischetti, M. (2012). A Lagrangian Heuristic for Robustness, with an Application to Train Timetabling. Transportation Science, 124-133.
Can, T. (2019). Matematik 1, Nedensellik Üzerine Diyaloglar. İstanbul: Beta.
Chai, S., Yin, J., D’Ariano, A., Samà, M., & Tang, T. (2023). Train schedule optimization for commuter-metro networks. Transportation Research Part C: Emerging Technologies, 155.
Charnes, A., & Miller, M. H. (1956). A Model For The Optimal Programming of Railway Freight Train Movements. Management Science, 3(1), 74-92.
Chung, J. W., Oh, S. M., & Choi, I. C. (2009). A Hybrid Genetic Algorithm for Train Sequencing in the Korean Railway. Omega(37), 555–565.

Cordeau, J. F., Toth, P., & Vigo, D. (1998). A Survey of Optimization Models for Train Routing and Scheduling. Transport Sciences , 380-404.
Ghoseiri, K., Szidarovszky, F., & Asgharpour, M. (2004). A Multi-Objective Train Scheduling Model and Solution. Transportation Research-B(38), 927-952.
Harrison, T., Midgley, W., Goodall, R., & Ward, C. (2021). Development and control of a rail vehicle model to reduce energy consumption and carbon dioxide emissions. Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit. 235. 1237-1248. 10.1177/095.440.9721993632.
Higgins, A., Kozan, E., & Ferreira, L. (1994). Optimal Scheduling of Trains on a Single Line Track. Transportation Research-B, 30(2), 147-161.
Hou, Y. W. (2020). Delay Recovery Model for High-Speed Trains with Compressed Train Dwell Time and Running Time. Rail. Eng. Science , 8, 424-438.
Hsu, S. (2010). Determinants of Passenger Transfer Waiting Time at Multi-Modal Connecting Statitons. Transportation Research Part E: Logistics and Transportation Review(46), 404-413.
Hu, Y., Li, W., & Luo, Q. (2024). Real-Time Adjustment Method for Metro Systems with Train Delays Based on Improved Q-Learning. Appl. Sci, 14(4).
Huang, Y., Ma, X., Su, S., & Tang, T. (2016). Optimization of Train Operation in Multiple Interstations with Multi-Population Genetic Algorithm. Energies, 14311–14329. .
istanbuldagez.com. (2022, Aralık 5). Marmaray Projesi Hat Bilgileri. Retrieved from İstanbul’da Gez: https:// www.istanbuldagez.com/wp-content/uploads/2013/10/3CA_marmaray-projesi-hat-bilgileri-2013- 1024x628.jpg
Jafarian-Moghaddam, A. (2021). Economical Speed for Optimizing the Travel Time and Energy Consumption in Train Scheduling using a Fuzzy Multi-Objective Model. . Urban Rail Transit, 7, 191-208.
Jia, L. M. (2017). Train Re-scheduling Based on an Improved Fuzzy Linear Programming Model. In: Train Operation in Emergencies. Advances in High-speed Rail Technology. Springer.
Jin, W., Sun, P., Yao, B., & Ding, R. (2024). A Train Timetable Optimization Method Considering Multi- Strategies for the Tidal Passenger Flow Phenomenon. Appl. Sci.
König, E. (2020). A review on railway delay management. Public Transp , 12, 335-361.
Khan, M. B., Zhang, D., Jun, M. s., & Li, Z. J. (2006). An Intelligent Search Technique to Train Scheduling Problem Based on Genetic Algorithm. International Conference on Emerging Technologies (pp. 593- 598). Peshavar: IEEE.
Kraay, D., Harker, P. T., & Chen, B. (1991). Optimal Pacing of Trains in Freight Railroads: Model Formulationand Solution. Operations Research(29), 82-99.
Lü, Z., & Hao, J.-K. (n.d.). Adaptive Tabu Search for Course Timetabling . European Journal of Operational Research, 200(1), 235-244.
Li, P., & Liu, B. (2008). Entropy of Credibility Distributions for Fuzzy Variables. Transactions on Fuzzy Systems, 16(1), 123-129.
Marmaray. (2020). Marmaray Hakkında. Retrieved from marmaray.gov.tr: https://marmaray.gov. tr/marmaray-hakkinda/#:~:text=Marmaray%20projesi%20ilk%20olarak%201860,yani%20 %E2%80%9CDeniz%20T%C3%BCneli%E2%80%9D%20denilmi%C5%9Ftir.
Mees, A. I. (1991). Railway Scheduling by Network Optimisation. Math1 Compat. Modelling, 15(1), 33-42.
Mills, R. G., Perkins, S. E., & Pudney, P. J. (1991). Dynamic Rescheduling of Long Haul Trains For Improved Timekeeping and Energy. Asia-Pacific Journal Operations Research(8), 146-165.
Nachtigall, K., & Voget, S. (1997). Minimizing Waiting Times in Integrated Fixed Interval Timetables Up- grading Railway Tracks. European Journal of Operations Research, 610-627.
Peterson, E., & Taylor, A. J. (1982). A Structured Model for Rail Line Simulation and Optimization. Transportation Science, 192-206.
Santos, A. D.-L., Laporte, G., & Mesa, J. (2012). Evaluating Passenger Robustness in A Rail Transit Network. Transportation Research Part C: Emerging Technologies (20), 34-46.
Saude, R. L., & Westerman, W. M. (1983). Computer Aided Train Dispatching: Decision Support Through Optimization. Interfaces, 13(6), 24-37.
Shang, P., Lİ, R., & Yang, L. (2016). Optimization of Urban Single-line Metro Timetable for Total Passenger Travel Time under Dynamic Passenger Demand. Procedia Engineering, 151-160.
Szpigel, B. (1973). Optimal train scheduling on a single line railway. Opns Res.(72), 344-351.
Tormos, P., Lova, A., Ingolotti, L., Abril, M., & Salido, M. A. (2008). A Genetic Algorithm for Railway Scheduling Problems. Studies in Computational Intelligence, 128, 255-2
Wong, R., Yuen, T., & Fung, K. (2008). Optimizing Timetable Synchronization for Rail Mass Transit. Transport Science, 42(1), 553-570.
Xu, J., & Zhou, X. (2011). Fuzzy-Like Multiple Objective Decision Making. Berlin: Springer Verlag.
Xu, X., Li, K., & Li, X. (2014). Research on Passenger Flow and Energy Consumption in a Subway System with Fuzzy Passenger Arrival Rates. Institution of Mechanical Engineers, 1-12.
Yang, L., & Li, K. (2009). Train Timetable Problem on a Single-Line Railway With Fuzzy Passenger Demand. IEEE Transactions on Fuzzy Systems , 617-629.
Yang, L., Gao, Z., & Li, K. (2010). Passenger Train Scheduling on a Single-Track or Partially Double-Track Railway with Stochastic Information. Engineering Optimization, 1003-1022.
Yang, L., Zhou, X., & Gao, Z. (2012). Rescheduling Trains with Scenario-Based Fuzzy Recovery Time Representation on Two-Way Double-Track Railways. Soft Computing, 605-616.
Zhang, H., & Ni, S. (2022). Train Scheduling Optimization for an Urban Rail Transit Line: A Simulated- Annealing Algorithm U

Details

Primary Language

English

Subjects

Econometrics (Other)

Journal Section

Research Article

Authors

Vildan Kistik ^*
0000-0001-6213-4619
Türkiye

Tuncay Can
0000-0002-4169-2563
Türkiye

Publication Date

October 20, 2026

Submission Date

February 22, 2026

Acceptance Date

June 2, 2026

Published in Issue

Year 2026 Volume: 10 Number: 2

DOI

https://doi.org/10.29228/JORE.59

IZ

https://izlik.org/JA25RE42YX

Cite

RIS / Bibtex

APA

Kistik, V., & Can, T. (2026). A MULTI-CRITERIA EVALUATION FRAMEWORK FOR ALTERNATIVE MARMARAY TIMETABLE STRATEGIES UNDER FUZZY PASSENGER DEMAND. Journal of Research in Economics, 10(2), 156-178. https://doi.org/10.29228/JORE.59

AMA

1.Kistik V, Can T. A MULTI-CRITERIA EVALUATION FRAMEWORK FOR ALTERNATIVE MARMARAY TIMETABLE STRATEGIES UNDER FUZZY PASSENGER DEMAND. JORE. 2026;10(2):156-178. doi:10.29228/JORE.59

Chicago

Kistik, Vildan, and Tuncay Can. 2026. “A MULTI-CRITERIA EVALUATION FRAMEWORK FOR ALTERNATIVE MARMARAY TIMETABLE STRATEGIES UNDER FUZZY PASSENGER DEMAND”. Journal of Research in Economics 10 (2): 156-78. https://doi.org/10.29228/JORE.59.

EndNote

Kistik V, Can T (October 1, 2026) A MULTI-CRITERIA EVALUATION FRAMEWORK FOR ALTERNATIVE MARMARAY TIMETABLE STRATEGIES UNDER FUZZY PASSENGER DEMAND. Journal of Research in Economics 10 2 156–178.

IEEE

[1]V. Kistik and T. Can, “A MULTI-CRITERIA EVALUATION FRAMEWORK FOR ALTERNATIVE MARMARAY TIMETABLE STRATEGIES UNDER FUZZY PASSENGER DEMAND”, JORE, vol. 10, no. 2, pp. 156–178, Oct. 2026, doi: 10.29228/JORE.59.

ISNAD

Kistik, Vildan - Can, Tuncay. “A MULTI-CRITERIA EVALUATION FRAMEWORK FOR ALTERNATIVE MARMARAY TIMETABLE STRATEGIES UNDER FUZZY PASSENGER DEMAND”. Journal of Research in Economics 10/2 (October 1, 2026): 156-178. https://doi.org/10.29228/JORE.59.

JAMA

1.Kistik V, Can T. A MULTI-CRITERIA EVALUATION FRAMEWORK FOR ALTERNATIVE MARMARAY TIMETABLE STRATEGIES UNDER FUZZY PASSENGER DEMAND. JORE. 2026;10:156–178.

MLA

Kistik, Vildan, and Tuncay Can. “A MULTI-CRITERIA EVALUATION FRAMEWORK FOR ALTERNATIVE MARMARAY TIMETABLE STRATEGIES UNDER FUZZY PASSENGER DEMAND”. Journal of Research in Economics, vol. 10, no. 2, Oct. 2026, pp. 156-78, doi:10.29228/JORE.59.

Vancouver

1.Vildan Kistik, Tuncay Can. A MULTI-CRITERIA EVALUATION FRAMEWORK FOR ALTERNATIVE MARMARAY TIMETABLE STRATEGIES UNDER FUZZY PASSENGER DEMAND. JORE. 2026 Oct. 1;10(2):156-78. doi:10.29228/JORE.59