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Mathematical Model Approaches for Train Assignment Problem on Ankara – Istanbul High-Speed Train Line

Year 2024, Issue: 20, 1 - 10, 31.07.2024
https://doi.org/10.47072/demiryolu.1395761

Abstract

In the railway sector, planners responsible for operations must efficiently and effectively manage train services between routes. Addressing this problem, this study proposes two binary mathematical programming models to assist railway companies in optimizing their operational processes. The objective of the first model is to allocate trains between two lines in a way that minimizes the total energy consumption among trains with different energy profiles. The second model aims to execute services on the route with the minimum number of trains. The proposed models were coded in the GAMS software and solved using the Cplex solver. To test the performance of the suggested solution approaches, it was conducted using high-speed train services data between Ankara and Istanbul. The obtained results were analyzed based on decision-makers' preferences.

References

  • [1] M. Boroun, S. Ramezani, N. V. Farahani, E. Hassannayebi, S. Abolmaali and M. Shakibayifar, “An efficient heuristic method for joint optimization of train scheduling and stop planning on double-track railway systems,” INFOR: Information Systems and Operational Research, vol.58 no.4, pp. 652-679, 2020.
  • [2] L. Yang, Y. Yao, H. Shi and P. Shang, “Dynamic passenger demand-oriented train scheduling optimization considering flexible short-turning strategy,” Journal of the Operational Research Society, vol.72, no.8, pp. 1707-1725, 2021.
  • [3] X. Xu, K. Li, L. Yang, and Z. Gao, “An efficient train scheduling algorithm on a single-track railway system” Journal of Scheduling, vol.22, pp. 85-105, 2019.
  • [4] Y. Huang, C. Mannino, L. Yang, and T. Tang, “ Coupling time-indexed and big-M formulations for real-time train scheduling during metro service disruptions,” Transportation Research Part B: Methodological, vol.133, pp.38-61, 2020.
  • [5] N. Gültekin, and T. Eren. “Demiryolu çizelgeleme probleminin modellenmesi ve çözümü,” Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, vol. 29, no.2, 235-242, 2014, doi:10.17341/gummfd.18951.
  • [6] Ö. Yalçınkaya. “Tren çizelgeleme problemi: bir modelleme ve çözüm yaklaşımı,” Demiryolu Mühendisliği, vol.3, pp. 75-80, 2016.
  • [7] F. Li, Z. Gao, K. Li, and D. Z. W. Wang. “Train routing model and algorithm combined with train acheduling” Journal of Transportation Engineering vol.139, no.1, 2013.
  • [8] A. R. Jafarian-Moghaddam, “Economical speed for optimizing the travel time and energy consumption in train scheduling using a fuzzy multi-objective model” Urban Rail Transit, vol.7, no.3, pp. 191-208, 2021.
  • [9] J. Zhou, X. Guo, and F. Li, “Urban rail train scheduling with smoothing energy consumption peaks and synchronization time minimization: Using novel time-shift control scheme” IEEE Access, vol.9, pp. 70142-70154, 2021.
  • [10] H. Zhang, L. Jia, L. Wang, and X. Xu, “Energy consumption optimization of train operation for railway systems: Algorithm development and real-world case study” Journal of Cleaner Production, vol.214, pp. 1024-1037, 2019.
  • [11] S. Zhan, P. Wang, S. C. Wong, and S. M. Lo, “Energy-efficient high-speed train rescheduling during a major disruption,” Transportation Research Part E: Logistics and Transportation Review, vol.157, 102492, 2022.
  • [12] P. Mo, L. Yang, A. D’Ariano, J. Yin, Y. Yao and Z. Gao, "Energy-efficient train scheduling and rolling stock circulation planning in a metro line: a linear programming approach," IEEE Transactions on Intelligent Transportation Systems, vol.21, no.9, pp. 3621-3633, 2020, doi: 10.1109/TITS.2019.2930085.
  • [13] B. Jin, X. Feng, Q. Wang, P. Sun and Q. Fang,” Train scheduling method to reduce substation energy consumption and peak power of metro transit systems,” Transportation Research Record, vol.2675, no.4, pp. 201-212, 2021, doi: 10.1177/0361198120974677.
  • [14] S. Hasanzadeh, S. F. Zarei and E. Najafi, "A train scheduling for energy optimization: Tehran metro system as a case study," IEEE Transactions on Intelligent Transportation Systems, vol. 24, no. 1, pp. 357-366, 2023, doi: 10.1109/TITS.2022.3215095.
  • [15] L. Zhang, D. He, Y. He, B. Liu, Y. Chen and S. Shan, “Real-time energy saving optimization method for urban rail transit train timetable under delay condition,” Energy, vol.258, 124853, 2022, doi: 10.1016/j.energy.2022.124853
  • [16] C. G. Corlu, R. de la Torre, A. Serrano-Hernandez, A.A. Juan, and J. Faulin, “Optimizing energy consumption in transportation: Literature review, insights, and research opportunities,” Energies, vol.13, no.5, 1115, 2020.
  • [17] P. M. Fernández, I. V. Sanchís, V. Yepes, and R. I. Franco, “A review of modelling and optimisation methods applied to railways energy consumption” Journal of Cleaner Production, vol. 222, pp. 153-162, 2019.
  • [18] Ö. Akbayır and F. H. Çakır, “Enerji verimliliği için tren direnci formüllerinin karşılaştırılması,” Mehmet Akif Ersoy Üniversitesi Fen Bilimleri Enstitüsü Dergisi, vol. 1, pp. 112-126, 2017.
  • [19] E. C. Schmidt, Freight train resistance, its relation to car weight. Vol. 43 of Engineering Experiment Station Illinois University, Urbana, Illinois 1910.
  • [20] S. Ateş, “Yüksek hizli demiryolu trafiğinin ürettiği bina titreşimlerinin saha koşullarinda ölçülmesi ve uluslararasi standartlara göre değerlendirilmesi,” Master Thesis, Department of Civil Engineering, Sakarya University, Sakarya, 2021.

Ankara – İstanbul YHT Hattındaki Tren Atama Problemi için Matematiksel Model Yaklaşımları

Year 2024, Issue: 20, 1 - 10, 31.07.2024
https://doi.org/10.47072/demiryolu.1395761

Abstract

Demiryolu sektöründe görev yapan planlamacılar, güzergahlar arasında yapılacak seferleri en verimli ve etkili şekilde yönetmek zorundadır. Bu çalışmada, demiryolu şirketlerinin operasyonel süreçlerini optimize etmelerine yardımcı olacak iki 0-1 tamsayılı matematiksel programlama modeli önerilmiştir. İlk modelin amacı, iki hat arasında yapılacak seferlere, farklı enerji tüketimine sahip trenler arasından toplam enerji tüketimini en küçükleyecek şekilde tren atamasını sağlamaktır. İkinci model ise, bu hattaki seferleri minimum sayıda trenle gerçekleştirmeyi amaçlamaktadır. Önerilen modeller, GAMS yazılımında kodlanmış ve Cplex çözücüsü kullanılmıştır. Ankara-İstanbul arasındaki yüksek hızlı tren seferleri ile ilgili veriler kullanılarak, önerilen çözüm yaklaşımlarının performansı test edilmiştir. Elde edilen sonuçlar karar vericilerin tercihlerine göre analiz edilmiştir.

References

  • [1] M. Boroun, S. Ramezani, N. V. Farahani, E. Hassannayebi, S. Abolmaali and M. Shakibayifar, “An efficient heuristic method for joint optimization of train scheduling and stop planning on double-track railway systems,” INFOR: Information Systems and Operational Research, vol.58 no.4, pp. 652-679, 2020.
  • [2] L. Yang, Y. Yao, H. Shi and P. Shang, “Dynamic passenger demand-oriented train scheduling optimization considering flexible short-turning strategy,” Journal of the Operational Research Society, vol.72, no.8, pp. 1707-1725, 2021.
  • [3] X. Xu, K. Li, L. Yang, and Z. Gao, “An efficient train scheduling algorithm on a single-track railway system” Journal of Scheduling, vol.22, pp. 85-105, 2019.
  • [4] Y. Huang, C. Mannino, L. Yang, and T. Tang, “ Coupling time-indexed and big-M formulations for real-time train scheduling during metro service disruptions,” Transportation Research Part B: Methodological, vol.133, pp.38-61, 2020.
  • [5] N. Gültekin, and T. Eren. “Demiryolu çizelgeleme probleminin modellenmesi ve çözümü,” Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, vol. 29, no.2, 235-242, 2014, doi:10.17341/gummfd.18951.
  • [6] Ö. Yalçınkaya. “Tren çizelgeleme problemi: bir modelleme ve çözüm yaklaşımı,” Demiryolu Mühendisliği, vol.3, pp. 75-80, 2016.
  • [7] F. Li, Z. Gao, K. Li, and D. Z. W. Wang. “Train routing model and algorithm combined with train acheduling” Journal of Transportation Engineering vol.139, no.1, 2013.
  • [8] A. R. Jafarian-Moghaddam, “Economical speed for optimizing the travel time and energy consumption in train scheduling using a fuzzy multi-objective model” Urban Rail Transit, vol.7, no.3, pp. 191-208, 2021.
  • [9] J. Zhou, X. Guo, and F. Li, “Urban rail train scheduling with smoothing energy consumption peaks and synchronization time minimization: Using novel time-shift control scheme” IEEE Access, vol.9, pp. 70142-70154, 2021.
  • [10] H. Zhang, L. Jia, L. Wang, and X. Xu, “Energy consumption optimization of train operation for railway systems: Algorithm development and real-world case study” Journal of Cleaner Production, vol.214, pp. 1024-1037, 2019.
  • [11] S. Zhan, P. Wang, S. C. Wong, and S. M. Lo, “Energy-efficient high-speed train rescheduling during a major disruption,” Transportation Research Part E: Logistics and Transportation Review, vol.157, 102492, 2022.
  • [12] P. Mo, L. Yang, A. D’Ariano, J. Yin, Y. Yao and Z. Gao, "Energy-efficient train scheduling and rolling stock circulation planning in a metro line: a linear programming approach," IEEE Transactions on Intelligent Transportation Systems, vol.21, no.9, pp. 3621-3633, 2020, doi: 10.1109/TITS.2019.2930085.
  • [13] B. Jin, X. Feng, Q. Wang, P. Sun and Q. Fang,” Train scheduling method to reduce substation energy consumption and peak power of metro transit systems,” Transportation Research Record, vol.2675, no.4, pp. 201-212, 2021, doi: 10.1177/0361198120974677.
  • [14] S. Hasanzadeh, S. F. Zarei and E. Najafi, "A train scheduling for energy optimization: Tehran metro system as a case study," IEEE Transactions on Intelligent Transportation Systems, vol. 24, no. 1, pp. 357-366, 2023, doi: 10.1109/TITS.2022.3215095.
  • [15] L. Zhang, D. He, Y. He, B. Liu, Y. Chen and S. Shan, “Real-time energy saving optimization method for urban rail transit train timetable under delay condition,” Energy, vol.258, 124853, 2022, doi: 10.1016/j.energy.2022.124853
  • [16] C. G. Corlu, R. de la Torre, A. Serrano-Hernandez, A.A. Juan, and J. Faulin, “Optimizing energy consumption in transportation: Literature review, insights, and research opportunities,” Energies, vol.13, no.5, 1115, 2020.
  • [17] P. M. Fernández, I. V. Sanchís, V. Yepes, and R. I. Franco, “A review of modelling and optimisation methods applied to railways energy consumption” Journal of Cleaner Production, vol. 222, pp. 153-162, 2019.
  • [18] Ö. Akbayır and F. H. Çakır, “Enerji verimliliği için tren direnci formüllerinin karşılaştırılması,” Mehmet Akif Ersoy Üniversitesi Fen Bilimleri Enstitüsü Dergisi, vol. 1, pp. 112-126, 2017.
  • [19] E. C. Schmidt, Freight train resistance, its relation to car weight. Vol. 43 of Engineering Experiment Station Illinois University, Urbana, Illinois 1910.
  • [20] S. Ateş, “Yüksek hizli demiryolu trafiğinin ürettiği bina titreşimlerinin saha koşullarinda ölçülmesi ve uluslararasi standartlara göre değerlendirilmesi,” Master Thesis, Department of Civil Engineering, Sakarya University, Sakarya, 2021.
There are 20 citations in total.

Details

Primary Language Turkish
Subjects Transportation Engineering, Industrial Engineering
Journal Section Article
Authors

Enver Kerem Kaya 0000-0002-1542-5170

Melike Sönmez 0000-0003-1901-5651

Emine Akyol Özer 0000-0002-9570-2886

Publication Date July 31, 2024
Submission Date November 24, 2023
Acceptance Date February 29, 2024
Published in Issue Year 2024 Issue: 20

Cite

IEEE E. K. Kaya, M. Sönmez, and E. Akyol Özer, “Ankara – İstanbul YHT Hattındaki Tren Atama Problemi için Matematiksel Model Yaklaşımları”, Demiryolu Mühendisliği, no. 20, pp. 1–10, July 2024, doi: 10.47072/demiryolu.1395761.