IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2022i1p193-d1012021.html
   My bibliography  Save this article

NOAH as an Innovative Tool for Modeling the Use of Suburban Railways

Author

Listed:
  • Maciej Kruszyna

    (Faculty of Civil Engineering, Wrocław University of Science and Technology (Politechnika Wrocławska), Wybrzeże Wyspiańskiego 27, 50-370 Wrocław, Poland)

Abstract

The paper presents an innovative method called the “Nest of Apes Heuristic” (NOAH) for modeling specific problems by combining technical aspects of transport systems with human decision-making. The method is inspired by nature. At the beginning of the paper, potential problems related to modeling a suburban rail system were presented. The literature review is supplemented with a short description of known heuristics. The basic terminology, procedures, and algorithm are then introduced in detail. The factors of the suburban rail system turn into “Monkeys”. Monkeys change their position in the nest, creating leaders and followers. This allows for the comparison of the factor sets in a real system. The case study area covers the vicinity of Wroclaw, the fourth largest city in Poland. Two experiments were conducted. The first takes into account the average values of the factors in order to observe the algorithm’s work and formulate the stopping criteria. The second is based on the current values of the factors. The purpose of this work was to evaluate these values and to assess the possibilities of changing them. The obtained results show that the new tool may be useful for modeling and analyzing such problems.

Suggested Citation

  • Maciej Kruszyna, 2022. "NOAH as an Innovative Tool for Modeling the Use of Suburban Railways," Sustainability, MDPI, vol. 15(1), pages 1-17, December.
    • Handle: RePEc:gam:jsusta:v:15:y:2022:i:1:p:193-:d:1012021
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/1/193/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/1/193/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Bob Hickish & David I. Fletcher & Robert F. Harrison, 2020. "Investigating Bayesian Optimization for rail network optimization," International Journal of Rail Transportation, Taylor & Francis Journals, vol. 8(4), pages 307-323, October.
    2. Shen, Weiwei & Xiao, Weizhou & Wang, Xin, 2016. "Passenger satisfaction evaluation model for Urban rail transit: A structural equation modeling based on partial least squares," Transport Policy, Elsevier, vol. 46(C), pages 20-31.
    3. Zhang, Yongxiang & D'Ariano, Andrea & He, Bisheng & Peng, Qiyuan, 2019. "Microscopic optimization model and algorithm for integrating train timetabling and track maintenance task scheduling," Transportation Research Part B: Methodological, Elsevier, vol. 127(C), pages 237-278.
    4. Zhang, Yongxiang & Peng, Qiyuan & Yao, Yu & Zhang, Xin & Zhou, Xuesong, 2019. "Solving cyclic train timetabling problem through model reformulation: Extended time-space network construct and Alternating Direction Method of Multipliers methods," Transportation Research Part B: Methodological, Elsevier, vol. 128(C), pages 344-379.
    5. Hoong Chuin Lau & Günther R. Raidl & Pascal Hentenryck, 2016. "New developments in metaheuristics and their applications," Journal of Heuristics, Springer, vol. 22(4), pages 359-363, August.
    6. Zhang, Qin & Lusby, Richard Martin & Shang, Pan & Zhu, Xiaoning, 2022. "A heuristic approach to integrate train timetabling, platforming, and railway network maintenance scheduling decisions," Transportation Research Part B: Methodological, Elsevier, vol. 158(C), pages 210-238.
    7. Wang, Yihui & D’Ariano, Andrea & Yin, Jiateng & Meng, Lingyun & Tang, Tao & Ning, Bin, 2018. "Passenger demand oriented train scheduling and rolling stock circulation planning for an urban rail transit line," Transportation Research Part B: Methodological, Elsevier, vol. 118(C), pages 193-227.
    8. Yan, Fei & Goverde, Rob M.P., 2019. "Combined line planning and train timetabling for strongly heterogeneous railway lines with direct connections," Transportation Research Part B: Methodological, Elsevier, vol. 127(C), pages 20-46.
    9. Adilson Elias Xavier & Vinicius Layter Xavier, 2016. "Flying elephants: a general method for solving non-differentiable problems," Journal of Heuristics, Springer, vol. 22(4), pages 649-664, August.
    10. Wei, Sheng & Zheng, Wei & Wang, Lei, 2021. "Understanding the configuration of bus networks in urban China from the perspective of network types and administrative division effect," Transport Policy, Elsevier, vol. 104(C), pages 1-17.
    11. Hansson, Joel & Pettersson-Löfstedt, Fredrik & Svensson, Helena & Wretstrand, Anders, 2021. "Replacing regional bus services with rail: Changes in rural public transport patronage in and around villages," Transport Policy, Elsevier, vol. 101(C), pages 89-99.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Mo, Pengli & D’Ariano, Andrea & Yang, Lixing & Veelenturf, Lucas P. & Gao, Ziyou, 2021. "An exact method for the integrated optimization of subway lines operation strategies with asymmetric passenger demand and operating costs," Transportation Research Part B: Methodological, Elsevier, vol. 149(C), pages 283-321.
    2. Zhang, Yongxiang & Peng, Qiyuan & Lu, Gongyuan & Zhong, Qingwei & Yan, Xu & Zhou, Xuesong, 2022. "Integrated line planning and train timetabling through price-based cross-resolution feedback mechanism," Transportation Research Part B: Methodological, Elsevier, vol. 155(C), pages 240-277.
    3. Bisheng He & Yongjun Zhu & Andrea D’Ariano & Keyu Wen & Lufeng Chen, 2023. "Dynamic Relational Graph Convolutional Network for Metro Passenger Flow Forecasting," SN Operations Research Forum, Springer, vol. 4(4), pages 1-27, December.
    4. Zhengwen Liao, 2023. "Rescheduling Out-of-Gauge Trains with Speed Restrictions and Temporal Blockades on the Opposite-Direction Track," Mathematics, MDPI, vol. 11(12), pages 1-26, June.
    5. Zhang, Qin & Lusby, Richard Martin & Shang, Pan & Zhu, Xiaoning, 2022. "A heuristic approach to integrate train timetabling, platforming, and railway network maintenance scheduling decisions," Transportation Research Part B: Methodological, Elsevier, vol. 158(C), pages 210-238.
    6. Pan Shang & Yu Yao & Liya Yang & Lingyun Meng & Pengli Mo, 2021. "Integrated Model for Timetabling and Circulation Planning on an Urban Rail Transit Line: a Coupled Network-Based Flow Formulation," Networks and Spatial Economics, Springer, vol. 21(2), pages 331-364, June.
    7. Zhang, Chuntian & Gao, Yuan & Cacchiani, Valentina & Yang, Lixing & Gao, Ziyou, 2023. "Train rescheduling for large-scale disruptions in a large-scale railway network," Transportation Research Part B: Methodological, Elsevier, vol. 174(C).
    8. Ji, Hangyu & Wang, Rui & Zhang, Chuntian & Yin, Jiateng & Ma, Lin & Yang, Lixing, 2024. "Optimization of train schedule with uncertain maintenance plans in high-speed railways: A stochastic programming approach," Omega, Elsevier, vol. 124(C).
    9. Han Zheng & Junhua Chen & Zhaocha Huang & Jianhao Zhu, 2022. "Joint Optimization of Multi-Cycle Timetable Considering Supply-to-Demand Relationship and Energy Consumption for Rail Express," Mathematics, MDPI, vol. 10(21), pages 1-29, November.
    10. Wang, Entai & Yang, Lixing & Yin, Jiateng & Zhang, Jinlei & Gao, Ziyou, 2024. "Passenger-oriented rolling stock scheduling in the metro system with multiple depots: Network flow based approaches," Transportation Research Part B: Methodological, Elsevier, vol. 180(C).
    11. Wang, Yihui & Zhao, Kangqi & D’Ariano, Andrea & Niu, Ru & Li, Shukai & Luan, Xiaojie, 2021. "Real-time integrated train rescheduling and rolling stock circulation planning for a metro line under disruptions," Transportation Research Part B: Methodological, Elsevier, vol. 152(C), pages 87-117.
    12. Yin, Jiateng & D’Ariano, Andrea & Wang, Yihui & Yang, Lixing & Tang, Tao, 2021. "Timetable coordination in a rail transit network with time-dependent passenger demand," European Journal of Operational Research, Elsevier, vol. 295(1), pages 183-202.
    13. Gao, Yuan & Xia, Jun & D’Ariano, Andrea & Yang, Lixing, 2022. "Weekly rolling stock planning in Chinese high-speed rail networks," Transportation Research Part B: Methodological, Elsevier, vol. 158(C), pages 295-322.
    14. Yuan, Yin & Li, Shukai & Yang, Lixing & Gao, Ziyou, 2022. "Real-time optimization of train regulation and passenger flow control for urban rail transit network under frequent disturbances," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 168(C).
    15. Huo, Jinbiao & Liu, Chengqi & Chen, Jingxu & Meng, Qiang & Wang, Jian & Liu, Zhiyuan, 2023. "Simulation-based dynamic origin–destination matrix estimation on freeways: A Bayesian optimization approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 173(C).
    16. Wang, Dian & D’Ariano, Andrea & Zhao, Jun & Zhong, Qingwei & Peng, Qiyuan, 2022. "Integrated rolling stock deadhead routing and timetabling in urban rail transit lines," European Journal of Operational Research, Elsevier, vol. 298(2), pages 526-559.
    17. Polinder, G.-J. & Cacchiani, V. & Schmidt, M.E. & Huisman, D., 2020. "An iterative heuristic for passenger-centric train timetabling with integrated adaption times," ERIM Report Series Research in Management ERS-2020-006-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    18. Tang, Lianhua & Li, Yantong & Bai, Danyu & Liu, Tao & Coelho, Leandro C., 2022. "Bi-objective optimization for a multi-period COVID-19 vaccination planning problem," Omega, Elsevier, vol. 110(C).
    19. Mudassir Shams & Bruno Carpentieri, 2024. "A High-Order Numerical Scheme for Efficiently Solving Nonlinear Vectorial Problems in Engineering Applications," Mathematics, MDPI, vol. 12(15), pages 1-33, July.
    20. Say-Wah Lee & Chuen-Wah Seow & Ke Xue, 2021. "Residents’ Sustainable City Evaluation, Satisfaction and Loyalty: Integrating Importance-Performance Analysis and Structural Equation Modelling," Sustainability, MDPI, vol. 13(12), pages 1-14, June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:15:y:2022:i:1:p:193-:d:1012021. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.