Skip to main content

Advertisement

Springer Nature Link
Log in

Pythagorean Fuzzy Based AHP-VIKOR Integration to Assess Rail Transportation Systems in Turkey

  • Published:
International Journal of Fuzzy Systems Aims and scope Submit manuscript

Abstract

Rail transit systems, one of the important public transportation (PT) systems, are widespread in large cities to satisfy passengers or commuters for their daily trips. However, rail transportation (RT) investments are costly, and the budgets are minimal. Thus assessing RT systems in big cities play a crucial role in deciding on the best RT investment. In this study, for the first time, a two-stage fuzzy set is used among the multi-criteria decision-making (MCDM) studies in the area of transportation. The proposed method is a unique technique integrating the Analytic Hierarchy Process (AHP) and Vise Kriterijumska Optimizacija I Kompromisno Resenje (VIKOR) techniques with an extension of Pythagorean fuzzy sets. In this manner, datasets from the observations of three rail lines in Antalya, one of the largest cities in Turkey, are applied to the proposed method. Fuzzy Analytic Hierarchy Process (FAHP), a commonly used MCDM method, is used to weighting four main criteria and thirteen sub-factors. AHP is strengthened by interval-valued Pythagorean fuzzy numbers (IVPFNs). The Fuzzy VIKOR (FVIKOR) approach is then applied for the prioritization of three rail line alternatives. Results are achieved by analyzing not only real RT service observations, also actual RT expenditures or costs. Consequently, the uncertainty in results is thus minimized. Outcomes of the case study reveal the most serviceable RT line in the city evaluating the main criteria, namely economy, comfort, environment, and safety. Therefore, the proposed approach methodologically contributes to adopting a new insight into the integration of MCDM methods with fuzzy set.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

Explore related subjects

Discover the latest articles, news and stories from top researchers in related subjects.

References

  1. Kennedy, C.A.: A comparison of the sustainability of public and private transportation systems: study of the Greater Toronto Area. Transportation (Amst). 29, 459–493 (2002)

    Google Scholar 

  2. Kuby, M., Barranda, A., Upchurch, C.: Factors influencing light-rail station boardings in the United States. Transp. Res. Part A Policy Pract. 38, 223–247 (2004)

    Google Scholar 

  3. Lam, S.H., Toan, T.D.: Land transport policy and public transport in Singapore. Transportation (Amst). 33, 171–188 (2006)

    Google Scholar 

  4. Cipriani, E., Gori, S., Petrelli, M.: Transit network design: a procedure and an application to a large urban area. Transp. Res. Part C Emerg. Technol. 20, 3–14 (2012)

    Google Scholar 

  5. Chang, Z., Phang, S.-Y.: Urban rail transit PPPs: lessons from East Asian cities. Transp. Res. Part A Policy Pract. 105, 106–122 (2017)

    Google Scholar 

  6. Janic, M.: Multicriteria evaluation of high-speed rail, transrapid Maglev and air passenger transport in Europe. Transp. Plan. Technol. 26, 491–512 (2003)

    Google Scholar 

  7. Gerçek, H., Karpak, B., Kılınçaslan, T.: A multiple criteria approach for the evaluation of the rail transit networks in Istanbul. Transportation (Amst). 31, 203–228 (2004)

    Google Scholar 

  8. Armstrong, R.J., Rodriguez, D.A.: An evaluation of the accessibility benefits of commuter rail in eastern Massachusetts using spatial hedonic price functions. Transportation (Amst). 33, 21–43 (2006)

    Google Scholar 

  9. Sari, I.U., Behret, H., Kahraman, C.: Risk governance of urban rail systems using fuzzy AHP: the case of Istanbul. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 20, 67–79 (2012)

    Google Scholar 

  10. Celik, E., Aydin, N., Gumus, A.T.: A multiattribute customer satisfaction evaluation approach for rail transit network: a real case study for Istanbul, Turkey. Transp. Policy. 36, 283–293 (2014)

    Google Scholar 

  11. Fraszczyk, A., Lamb, T., Marinov, M.: Are railways really that bad? An evaluation of rail systems performance in Europe with a focus on passenger rail. Transp. Res. Part A Policy Pract. 94, 573–591 (2016)

    Google Scholar 

  12. Shen, W., Xiao, W., Wang, X.: Passenger satisfaction evaluation model for urban rail transit: a structural equation modeling based on partial least squares. Transp. Policy 46, 20–31 (2016)

    Google Scholar 

  13. Aydin, N.: A fuzzy-based multi-dimensional and multi-period service quality evaluation outline for rail transit systems. Transp. Policy. 55, 87–98 (2017)

    Google Scholar 

  14. Huang, W., Shuai, B., Sun, Y., Wang, Y., Antwi, E.: Using entropy-TOPSIS method to evaluate urban rail transit system operation performance: the China case. Transp. Res. Part A Policy Pract. 111, 292–303 (2018)

    Google Scholar 

  15. Celik, E., Akyuz, E.: An interval type-2 fuzzy AHP and TOPSIS methods for decision-making problems in maritime transportation engineering: the case of ship loader. Ocean Eng. 155, 371–381 (2018)

    Google Scholar 

  16. Gul, M., Ak, M.F., Guneri, A.F.: Pythagorean fuzzy VIKOR-based approach for safety risk assessment in mine industry. J. Saf. Res. 69, 135–153 (2019)

    Google Scholar 

  17. Ak, M.F., Gul, M.: AHP–TOPSIS integration extended with Pythagorean fuzzy sets for information security risk analysis. Complex Intell. Syst. 5, 113–126 (2019)

    Google Scholar 

  18. Hyland, M.F., Mahmassani, H.S., Mjahed, L.B.: Analytical models of rail transportation service in the grain supply chain: deconstructing the operational and economic advantages of shuttle train service. Transp. Res. Part E Logist. Transp. Rev. 93, 294–315 (2016)

    Google Scholar 

  19. Heinold, A., Meisel, F.: Emission rates of intermodal rail/road and road-only transportation in Europe: a comprehensive simulation study. Transp. Res. Part D Transp. Environ. 65, 421–437 (2018)

    Google Scholar 

  20. Singh, P., Dulebenets, M.A., Pasha, J., Gonzalez, E.D.R.S., Lau, Y.-Y., Kampmann, R.: Deployment of autonomous trains in rail transportation: current trends and existing challenges. IEEE Access 9, 91427–91461 (2021)

    Google Scholar 

  21. Broniewicz, E., Ogrodnik, K.: Multi-criteria analysis of transport infrastructure projects. Transp. Res. Part D Transp. Environ. 83, 102351 (2020)

    Google Scholar 

  22. Matisziw, T.C., Demir, E.: Inferring network paths from point observations. Int. J. Geogr. Inf. Sci. (2012). https://doi.org/10.1080/13658816.2012.674137

    Article  Google Scholar 

  23. Matisziw, T.C., Demir, E.: Measuring spatial correspondence among network paths. Geogr. Anal. (2016). https://doi.org/10.1111/gean.12078

    Article  Google Scholar 

  24. Mardani, A., Zavadskas, E.K., Khalifah, Z., Jusoh, A., Nor, K.M.D.: Multiple criteria decision-making techniques in transportation systems: a systematic review of the state of the art literature. Transport 31, 359–385 (2016)

    Google Scholar 

  25. Celik, E., Bilisik, O.N., Erdogan, M., Gumus, A.T., Baracli, H.: An integrated novel interval type-2 fuzzy MCDM method to improve customer satisfaction in public transportation for Istanbul. Transp. Res. Part E Logist. Transp. Rev. 58, 28–51 (2013)

    Google Scholar 

  26. Keyvan Ekbatani, M., Cats, O.: Multi-criteria appraisal of multi-modal urban public transport systems. Transp. Res. Procedia, 10, 2015; 18th Euro Work. Gr. Transp. EWGT 2015, 14–16 July 2015, Delft (2015)

  27. Żak, J., Kruszyński, M.: Application of AHP and ELECTRE III/IV methods to multiple level, multiple criteria evaluation of urban transportation projects. Transp. Res. Procedia 10, 820–830 (2015)

    Google Scholar 

  28. Nassereddine, M., Eskandari, H.: An integrated MCDM approach to evaluate public transportation systems in Tehran. Transp. Res. Part A Policy Pract. 106, 427–439 (2017)

    Google Scholar 

  29. Awasthi, A., Omrani, H., Gerber, P.: Investigating ideal-solution based multicriteria decision making techniques for sustainability evaluation of urban mobility projects. Transp. Res. Part A Policy Pract. 116, 247–259 (2018)

    Google Scholar 

  30. Hamurcu, M., Eren, T.: Electric bus selection with multicriteria decision analysis for green transportation. Sustainability 12, 2777 (2020)

    Google Scholar 

  31. Kumar, A., Singh, G., Vaidya, O.S.: A comparative evaluation of public road transportation systems in India using multicriteria decision-making techniques. J. Adv. Transp. (2020). https://doi.org/10.1155/2020/8827186

    Article  Google Scholar 

  32. Seker, S., Aydin, N.: Sustainable public transportation system evaluation: a novel two-stage hybrid method based on IVIF-AHP and CODAS. Int. J. Fuzzy Syst. 22, 257–272 (2020)

    Google Scholar 

  33. Ghorbanzadeh, O., Moslem, S., Blaschke, T., Duleba, S.: Sustainable urban transport planning considering different stakeholder groups by an interval-AHP decision support model. Sustainability 11, 9 (2018)

    Google Scholar 

  34. Kiciński, M., Solecka, K.: Application of MCDA/MCDM methods for an integrated urban public transportation system—case study, city of Cracow. Arch. Transp. 46(2), 71–84 (2018)

    Google Scholar 

  35. Pérez-Dominguez, L., Durán, S.-N.A., López, R.R., Pérez-Olguin, I.J.C., Luviano-Cruz, D., Gómez, J.A.H.: Assessment urban transport service and Pythagorean fuzzy sets CODAS method: a case of study of Ciudad Juárez. Sustainability 13, 1281 (2021)

    Google Scholar 

  36. Wang, G., Tao, Y., Li, Y.: TOPSIS evaluation system of logistics transportation based on an ordered representation of the polygonal fuzzy set. Int. J. Fuzzy Syst. 22, 1565–1581 (2020)

    Google Scholar 

  37. Öztürk, F.: A hybrid type-2 fuzzy performance evaluation model for public transport services. Arab. J. Sci. Eng. 46, 10261–10279 (2021)

    Google Scholar 

  38. de Aquino, J.T., de Melo, F.J.C., Jerônimo, T.B., de Medeiros, D.D.: Evaluation of quality in public transport services: the use of quality dimensions as an input for fuzzy TOPSIS. Int. J. Fuzzy Syst. 21, 176–193 (2019)

    Google Scholar 

  39. Mavi, R.K., Zarbakhshnia, N., Khazraei, A.: Bus rapid transit (BRT): a simulation and multi criteria decision making (MCDM) approach. Transp. Policy. 72, 187–197 (2018)

    Google Scholar 

  40. Erdoğan, M., Kaya, I.: A combined fuzzy approach to determine the best region for a nuclear power plant in Turkey. Appl. Soft Comput. 39, 84–93 (2016)

    Google Scholar 

  41. Güner, S.: Measuring the quality of public transportation systems and ranking the bus transit routes using multi-criteria decision making techniques. Case Stud. Transp. Policy 6, 214–224 (2018)

    Google Scholar 

  42. Büyüközkan, G., Göçer, F., Feyzioğlu, O.: Cloud computing technology selection based on interval-valued intuitionistic fuzzy MCDM methods. Soft Comput. 22, 5091–5114 (2018)

    Google Scholar 

  43. Sennaroglu, B., Celebi, G.V.: A military airport location selection by AHP integrated PROMETHEE and VIKOR methods. Transp. Res. Part D Transp. Environ. 59, 160–173 (2018)

    Google Scholar 

  44. Deveci, M., Demirel, N.Ç., Ahmetoğlu, E.: Airline new route selection based on interval type-2 fuzzy MCDM: a case study of new route between Turkey-North American region destinations. J. Air Transp. Manag. 59, 83–99 (2017)

    Google Scholar 

  45. Chen, I.-S.: A combined MCDM model based on DEMATEL and ANP for the selection of airline service quality improvement criteria: a study based on the Taiwanese airline industry. J. Air Transp. Manag. 57, 7–18 (2016)

    Google Scholar 

  46. Ghorabaee, M.K., Amiri, M., Zavadskas, E.K., Turskis, Z., Antucheviciene, J.: A new hybrid simulation-based assignment approach for evaluating airlines with multiple service quality criteria. J. Air Transp. Manag. 63, 45–60 (2017)

    Google Scholar 

  47. Aydin, N., Celik, E., Gumus, A.T.: A hierarchical customer satisfaction framework for evaluating rail transit systems of Istanbul. Transp. Res. Part A Policy Pract. 77, 61–81 (2015)

    Google Scholar 

  48. Azadeh, A., Salehi, V., Kianpour, M.: Performance evaluation of rail transportation systems by considering resilience engineering factors: Tehran railway electrification system. Transp. Lett. 10, 12–25 (2018)

    Google Scholar 

  49. Özgür, Ö.: Performance analysis of rail transit investments in Turkey: İstanbul, Ankara, İzmir and Bursa. Transp. Policy. 18, 147–155 (2011)

    Google Scholar 

  50. Mandic, D., Jovanovic, P., Bugarinovic, M.: Two-phase model for multi-criteria project ranking: Serbian Railways case study. Transp. Policy. 36, 88–104 (2014)

    Google Scholar 

  51. Görçün, Ö.F.: Evaluation of the selection of proper metro and tram vehicle for urban transportation by using a novel integrated MCDM approach. Sci. Prog. (2021). https://doi.org/10.1177/0036850420950120

    Article  Google Scholar 

  52. Kilic, O., Çerçioğlu, H.: Application of compromise multiple criteria decision making methods for evaluation of TCDD’s railway lines projects. J. Fac. Eng. Arch. Gazi Univ. 31(1), 211–220 (2016)

    Google Scholar 

  53. Yücel, N., Taşabat, S.E.: The selection of railway system projects with multi criteria decision making methods: a case study for Istanbul. Procedia Comput. Sci. 158, 382–393 (2019)

    Google Scholar 

  54. Li, J., Xu, X., Yao, Z., Lu, Y.: Improving service quality with the fuzzy TOPSIS method: a case study of the Beijing rail transit system. IEEE Access 7, 114271–114284 (2019)

    Google Scholar 

  55. Stoilova, S., Munier, N., Kendra, M., Skrúcaný, T.: Multi-criteria evaluation of railway network performance in countries of the TEN-T orient–east med corridor. Sustainability 12, 1482 (2020)

    Google Scholar 

  56. Zhang, H., Sun, Q.: An integrated MCDM approach to train derailment risk response strategy selection. Symmetry (Basel) 12, 47 (2019)

    Google Scholar 

  57. Gul, M.: Application of Pythagorean fuzzy AHP and VIKOR methods in occupational health and safety risk assessment: the case of a gun and rifle barrel external surface oxidation and colouring unit. Int. J. Occup. Saf. Ergon. 26(4), 705–718 (2018)

    Google Scholar 

  58. Gul, M., Guven, B., Guneri, A.F.: A new Fine-Kinney-based risk assessment framework using FAHP-FVIKOR incorporation. J. Loss Prev. Process Ind. 53, 3–16 (2018)

    Google Scholar 

  59. Gul, M., Ak, M.F., Guneri, A.F.: Occupational health and safety risk assessment in hospitals: a case study using two-stage fuzzy multi-criteria approach. Hum. Ecol. Risk Assess. 23, 187–202 (2017)

    Google Scholar 

  60. Ayyildiz, E., Taskin, A.: A novel spherical fuzzy AHP-VIKOR methodology to determine serving petrol station selection during COVID-19 lockdown: a pilot study for İstanbul. Socioecon. Plan. Sci. 83, 101345 (2022)

    Google Scholar 

  61. Zhou, F., Chen, T.-Y.: An extended Pythagorean fuzzy VIKOR method with risk preference and a novel generalized distance measure for multicriteria decision-making problems. Neural Comput. Appl. 33, 11821–11844 (2021)

    Google Scholar 

  62. Gul, M., Ak, M.F.: A comparative outline for quantifying risk ratings in occupational health and safety risk assessment. J. Clean. Prod. 196, 653–664 (2018)

    Google Scholar 

  63. Ilbahar, E., Karaşan, A., Cebi, S., Kahraman, C.: A novel approach to risk assessment for occupational health and safety using Pythagorean fuzzy AHP & fuzzy inference system. Saf. Sci. 103, 124–136 (2018)

    Google Scholar 

  64. Opricovic, S., Tzeng, G.-H.: Compromise solution by MCDM methods: a comparative analysis of VIKOR and TOPSIS. Eur. J. Oper. Res. 156, 445–455 (2004)

    MATH  Google Scholar 

  65. Cui, F.-B., You, X.-Y., Shi, H., Liu, H.-C.: Optimal siting of electric vehicle charging stations using Pythagorean fuzzy VIKOR approach. Math. Probl. Eng. (2018). https://doi.org/10.1155/2018/9262067

    Article  Google Scholar 

Download references

Funding

No funding was received from any institution or organization for the article.

Author information

Authors and Affiliations

  1. Department of Civil Engineering, Antalya Bilim University, Antalya, Turkey

    Emre Demir

  2. Department of Industrial Engineering, Antalya Bilim University, Antalya, Turkey

    Muhammet Fatih Ak

  3. Institute of Postgraduate Education, Antalya Bilim University, Antalya, Turkey

    Kaan Sarı

Authors
  1. Emre Demir
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. Muhammet Fatih Ak
    View author publications

    You can also search for this author inPubMed Google Scholar

  3. Kaan Sarı
    View author publications

    You can also search for this author inPubMed Google Scholar

Corresponding author

Correspondence to Emre Demir.

Ethics declarations

Conflict of interest

The authors have no competing interests to declare that are relevant to the content of this article.

Rights and permissions

Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Demir, E., Ak, M.F. & Sarı, K. Pythagorean Fuzzy Based AHP-VIKOR Integration to Assess Rail Transportation Systems in Turkey. Int. J. Fuzzy Syst. 25, 620–632 (2023). https://doi.org/10.1007/s40815-022-01404-x

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40815-022-01404-x

Keywords