Assessment of Occupational Risks in Construction Sites Using Interval Type-2 Fuzzy Analytic Hierarchy Process

  • Joy Debnath
  • Animesh BiswasEmail author
Conference paper
Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 11)


This paper describes a method for assessing risk of the workers at construction sites using interval type-2 fuzzy analytic hierarchy process. Historical accident data, subjective judgments by the experts and relative importance of the risk factors are combined together to determine the current risk level of construction sites. The linguistic terms associated with the model are represented by interval type-2 trapezoidal fuzzy numbers. The proposed method can identify the risk factors which are most important in improving worker safety and, therefore, determines the areas on which the management should emphasize in order to improve the safety of the workers. The application potentiality of this model has been demonstrated by a case example of risk analysis of a construction industry.


Risk assessment Linguistic variables Type-2 trapezoidal fuzzy numbers Interval type-2 fuzzy analytic hierarchy process 



The authors are thankful to the anonymous reviewers for their comments and suggestions to improve the quality of the paper. The authors express their humble gratitude to Mr. Krishna Nirmalya Sen, President, American Society of Safety Engineers, India Chapter, for his expert opinion and kind cooperation in the process of execution of the developed model. This work is partially supported by DST-PURSE Programme of University of Kalyani, Kalyani, India.


  1. 1.
    Pinto, A., Nunes, I.L., Ribeiro, R.A.: Occupational risk assessment in construction industry—overview and reflection. Saf. Sci. 49, 616–624 (2011)CrossRefGoogle Scholar
  2. 2.
    Beriha, G.S., Patnaik, B., Mahapatra, S.S., Padhee, S.: Assessment of safety performances in Indian industries using fuzzy approach. Experts Syst. Appl. 39, 3311–3323 (2012)CrossRefGoogle Scholar
  3. 3.
    Thomas, A.V., Kalidindi, S.N., Ganesh, L.S.: Modelling and assessment of critical risks in BOT road projects. Constr. Manag. Econ. 24, 407–424 (2006)CrossRefGoogle Scholar
  4. 4.
    Saaty, T.L., Vargas, L.G.: The Analytic Hierarchy Process. McGraw-Hill, New York (1980)zbMATHGoogle Scholar
  5. 5.
    Majumder, D., Debnath, J., Biswas, A.: Risk analysis in construction sites using fuzzy reasoning and fuzzy analytic hierarchy process. Proc. Technol. 10, 604–614 (2013)CrossRefGoogle Scholar
  6. 6.
    Zadeh, L.A.: Fuzzy sets. Inf. Control 8, 338–353 (1965)CrossRefzbMATHGoogle Scholar
  7. 7.
    Mendel, J.M.: Uncertain Rule-Based fuzzy Logic Systems: Introduction and New Directions. Prentice-Hall, Upper Saddle River, NJ (2001)zbMATHGoogle Scholar
  8. 8.
    Mendel, J.M., John, R.I., Liu, F.L.: Interval type-2 fuzzy logical systems made simple. IEEE Trans. Fuzzy Syst. 14, 808–821 (2006)CrossRefGoogle Scholar
  9. 9.
    Abdullah, L., Najib, L.: A new type-2 fuzzy set of linguistic variables for the fuzzy analytic hierarchy process. Experts Syst. Appl. 41, 3297–3305 (2014)CrossRefGoogle Scholar
  10. 10.
    Mou, Q.: Method of Multi-Attribute Decision-Making and Its Application. Guangxi University, Nanning (2004)Google Scholar
  11. 11.
    Wang, W., Liu, X., Qin, Y.: Multi-attribute group decision making models under interval type-2 fuzzy environment. Knowl.-Based Syst. 30, 121–128 (2012)CrossRefGoogle Scholar
  12. 12.
    Jhon, R.I.: An appraisal of theory and applications. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 6, 563–576 (1998)CrossRefGoogle Scholar
  13. 13.
    Lee, L.W., Chen, S.M.: A new method for fuzzy multiple attributes group decision-making based on the arithmetic operations of interval type-2 fuzzy sets. In: Proceedings of the 2008 International Conference on Machine Learning and Cybernetics, China, Kunming, pp. 3084–3089 (2008)Google Scholar
  14. 14.
    Chen, S.M., Lee, L.W.: Fuzzy multiple attributes group decision-making based on the interval type-2 TOPSIS method. Experts Syst. Appl. 37, 2790–2798 (2010)CrossRefGoogle Scholar
  15. 15.
    Kahraman, C., Oztaysi, B., Sari, I.U., Turanoglu, E.: Fuzzy analytic hierarchy process with interval type-2 fuzzy sets. Knowl. Based Syst. 59, 48–57 (2014)CrossRefGoogle Scholar
  16. 16.
    Ross, T.J.: Fuzzy Logic with Engineering Applications. McGraw-Hill, New York (1995)Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.Department of MathematicsUniversity of KalyaniKalyaniIndia

Personalised recommendations