An improved TOPSIS method for metro station evacuation strategy selection in interval type-2 fuzzy environment

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Abstract

With the constant growth of urban construction, metro station has being playing an increasingly important role in the public transportation system. To ensure the safe operation and the safety of the people, it is necessary to analyze how to select a suitable evacuation strategy while emergency event occurs in a metro station. The evacuation strategy selection can be regarded as a multiple criteria group decision making problem, which involves some conflict evaluation criteria. This paper presents an improved TOPSIS method to handle the evacuation strategy selection problem of metro station based on interval type-2 fuzzy sets. Firstly, the TOPSIS method in interval type-2 fuzzy environment is introduced. Then the evacuation strategy selection model and the calculation steps for metro station in emergency situation are constructed. Finally, a numerical example about the evacuation strategy selection along with a sensitivity analysis about the parameters and a comparison analysis with Chen’s research is provided to verify the efficiency of the proposed method.

Keywords

Evacuation strategy Metro station TOPSIS method Interval type-2 fuzzy sets 
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Notes

Acknowledgements

This research is supported by National Social Science Foundation of China (Project No. 15AGL021), Research Center for Systems Science & Enterprise Development (Grant No. Xq17B07).

References

  1. 1.
    Qin, J., Liu, X.: Multi-attribute group decision making using combined ranking value under interval type-2 fuzzy environment. Inf. Sci. 297, 293–315 (2015)MathSciNetCrossRefMATHGoogle Scholar
  2. 2.
    Qin, J., Liu, X., Pedrycz, W.: A multiple attribute interval type-2 fuzzy group decision making and its application to supplier selection with extended LINMAP method. Soft Comput. 21(12), 3207–3226 (2016)CrossRefGoogle Scholar
  3. 3.
    Joshi, D., Kumar, S.: Interval-valued intuitionistic hesitant fuzzy Choquet integral based TOPSIS method for multi-criteria group decision making. Eur. J. Oper. Res. 248(1), 183–191 (2016)MathSciNetCrossRefMATHGoogle Scholar
  4. 4.
    Biswas, P., Pramanik, S., Giri, B.C.: TOPSIS method for multi-attribute group decision-making under single-valued neutrosophic environment. Neural Comput. Appl. 27(3), 727–737 (2016)CrossRefGoogle Scholar
  5. 5.
    Walczak, D., Rutkowska, A.: Project rankings for participatory budget based on the fuzzy TOPSIS method. Eur. J. Oper. Res. 260(2), 706–714 (2017)MathSciNetCrossRefGoogle Scholar
  6. 6.
    Elhassouny, A., Smarandache, F.: Neutrosophic-simplified-TOPSIS multi-criteria decision-making using combined simplified-TOPSIS method and neutrosophics. In: IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), pp. 2468–2474. IEEE (2016)Google Scholar
  7. 7.
    Lovell, D.J., Daganzo, C.F.: Access control on networks with unique origin-destination paths. Transp. Res. B Meth. 34(3), 185–202 (2000)CrossRefGoogle Scholar
  8. 8.
    Cepolina, E.M.: Phased evacuation: an optimization model which takes into account the capacity drop phenomenon in pedestrian flows. Fire Safety J. 44(4), 532–544 (2009)CrossRefGoogle Scholar
  9. 9.
    Noh, D., Koo, J., Kim, B.I.: An efficient partially dedicated strategy for evacuation of a heterogeneous population. Simul. Model. Pract. T. 62, 157–165 (2016)CrossRefGoogle Scholar
  10. 10.
    Koo, J., Kim, B.I., Kim, Y.S.: Estimating the effects of mental disorientation and physical fatigue in a semi-panic evacuation. Expert Syst. Appl. 41(5), 2379–2390 (2014)CrossRefGoogle Scholar
  11. 11.
    You, L., Hu, J., Gu, M., et al.: The simulation and analysis of small group effect in crowd evacuation. Phys. Lett. A. 380(41), 3340–3348 (2016)CrossRefGoogle Scholar
  12. 12.
    Wong, K.H.L., Luo, M.: Infrastructure protection and emergency response-computational tool in infrastructure emergency total evacuation analysis. Lecture Notes in Computer Science, vol. 3495, pp. 536–542 (2005)Google Scholar
  13. 13.
    So, S.K., Daganzo, C.F.: Managing evacuation routes. Transp. Res. B Meth. 44(4), 514–520 (2010)CrossRefGoogle Scholar
  14. 14.
    Abdelghany, A., Abdelghany, K., Mahmassani, H., et al.: Modeling framework for optimal evacuation of large-scale crowded pedestrian facilities. Eur. J. Oper. Res. 237(3), 1105–1118 (2014)MathSciNetCrossRefMATHGoogle Scholar
  15. 15.
    Zhang, L., Liu, M., Wu, X., et al.: Simulation-based route planning for pedestrian evacuation in metro stations: a case study. Autom. Constr. 71, 430–442 (2016)CrossRefGoogle Scholar
  16. 16.
    Fry, J., Binner, J.M.: Elementary modelling and behavioral analysis for emergency evacuations using social media. Eur. J. Oper. Res. 249(3), 1014–1023 (2016)CrossRefMATHGoogle Scholar
  17. 17.
    Vanlandegen, L.D., Chen, X.: Microsimulation of large-scale evacuations utilizing metro rail transit. Appl. Geogr. 32(2), 787–797 (2010)CrossRefGoogle Scholar
  18. 18.
    Chen, S., Lee, L.: Fuzzy multiple attributes group decision-making based on the interval type-2 TOPSIS method. Expert Syst. Appl. 37(4), 2790–2798 (2010)CrossRefGoogle Scholar
  19. 19.
    Chen, S., Yang, M., Lee, L., et al.: Fuzzy multiple attributes group decision-making based on ranking interval type-2 fuzzy sets. Expert Syst. Appl. 39(5), 5295–5308 (2012)CrossRefGoogle Scholar
  20. 20.
    Baykasoğlu, A., Gölcük, İ.: Development of an interval type-2 fuzzy sets based hierarchical MADM model by combining DEMATEL and TOPSIS. Expert Syst. Appl. 70, 37–51 (2017)CrossRefGoogle Scholar
  21. 21.
    Chen, T.: An interval type-2 fuzzy technique for order preference by similarity to ideal solutions using a likelihood-based comparison approach for multiple criteria decision analysis. Comput. Ind. Eng. 85, 57–72 (2015)CrossRefGoogle Scholar
  22. 22.
    Ghaemi, Nasab F., Rostamy-Malkhalifeh, M.: Extension of TOPSIS for group decision-making based on the type-2 fuzzy positive and negative ideal solutions. Int. J. Ind. Math. 2(3), 199–213 (2010)Google Scholar
  23. 23.
    Nehi, H.M., Keikha, A.: TOPSIS and Choquet integral hybrid technique for solving MAGDM problems with interval type-2 fuzzy numbers. J. Intell. Fuzzy Syst. 30(3), 1301–1310 (2016)CrossRefMATHGoogle Scholar
  24. 24.
    Zamri, N., Abdullah, L.: A new qualitative evaluation for an integrated interval type-2 fuzzy TOPSIS and MCGP. In: Recent Advances on Soft Computing and Data Mining, pp. 79–88. Springer International Publishing, New York (2014)Google Scholar
  25. 25.
    Sang, X., Liu, X.: An analytical solution to the TOPSIS model with interval type-2 fuzzy sets. Soft Comput. 20(3), 1213–1230 (2015)CrossRefMATHGoogle Scholar
  26. 26.
    Abdullah, L., Otheman, A.: A new entropy weight for sub-criteria in interval type-2 fuzzy TOPSIS and its application. Int. J. Intell. Syst. Appl. 5(2), 25 (2013)Google Scholar
  27. 27.
    Deveci, M., Demirel, N.C., 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)CrossRefGoogle Scholar
  28. 28.
    Wang, T., Chang, T.: Application of TOPSIS in evaluating initial training aircraft under a fuzzy environment. Expert Syst. Appl. 33(4), 870–880 (2007)CrossRefGoogle Scholar
  29. 29.
    Kahraman, C., Uçal Sarı İ.: Multicriteria environmental risk evaluation using type II fuzzy sets. In: Advances in Computational Intelligence, pp. 449–457 (2012)Google Scholar
  30. 30.
    Qin, Y., Zhang, Z., Liu, X., et al.: Dynamic risk assessment of metro station with interval type-2 fuzzy set and TOPSIS method. J. Intell. Fuzzy Syst. 29(1), 93–106 (2015)CrossRefGoogle Scholar
  31. 31.
    Lee, C., Wang, M., Hagras, H.: A type-2 fuzzy ontology and its application to personal diabetic-diet recommendation. IEEE Trans. Fuzzy Syst. 18(2), 374–395 (2010)Google Scholar
  32. 32.
    Chen, T., Chang, C., Lu, J.: The extended QUALIFLEX method for multiple criteria decision analysis based on interval type-2 fuzzy sets and applications to medical decision making. Eur. J. Oper. Res. 226(3), 615–625 (2013)MathSciNetCrossRefMATHGoogle Scholar
  33. 33.
    Mendel, J.M., Rajati, M.R., Sussner, P.: On clarifying some definitions and notations used for type-2 fuzzy sets as well as some recommended changes. Inform. Sci. 340, 337–345 (2016)MathSciNetCrossRefGoogle Scholar
  34. 34.
    Wu, D., Mendel, J.M.: Uncertainty measures for interval type-2 fuzzy sets. Inform. Sci. 177(23), 5378–5393 (2007)MathSciNetCrossRefMATHGoogle Scholar
  35. 35.
    Chen, S., Lee, L.: Fuzzy multiple attributes group decision-making based on the ranking values and the arithmetic operations of interval type-2 fuzzy sets. Expert Syst. Appl. 37(1), 824–833 (2010)MathSciNetCrossRefGoogle Scholar
  36. 36.
    Chen, T.: A signed-distance-based approach to importance assessment and multi-criteria group decision analysis based on interval type-2 fuzzy set. Knowl. Inform. Syst. 35, 193–231 (2013)CrossRefGoogle Scholar
  37. 37.
    Qin, J., Liu, X., Pedrycz, W.: An extended TODIM multi-criteria group decision making method for green supplier selection in interval type-2 fuzzy environment. Eur. J. Oper. Res. 258(2), 626–638 (2017)MathSciNetCrossRefGoogle Scholar
  38. 38.
    Kuo, T.: A modified TOPSIS with a different ranking index. Eur. J. Oper. Res. 260(1), 152–160 (2017)MathSciNetCrossRefGoogle Scholar

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© Springer Science+Business Media, LLC, part of Springer Nature 2017

Authors and Affiliations

  1. 1.School of ManagementWuhan University of TechnologyWuhanChina

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