598Accesses
10Citations
Abstract
In this paper, we develop a new fuzzy multi-criteria group decision making method using triangular intuitionistic fuzzy numbers (TIFNs) for determining critical path in a critical path problem (CPP). The CPP considered here involves both quantitative and qualitative assessments of the decision makers on multiple conflicting criteria. The intuitionistic fuzzy numbers are introduced since they consider both preferences and non-preferences simultaneously and are thus capable of representing qualitatively evaluated information more effectively than fuzzy sets. The proposed method involves fuzzy evaluation based on the extended preference relation of TIFNs using\((\alpha ,\beta )\)-cuts considered for preferences and non-preferences, respectively. The preference intensity function based on the extended preference relation of TIFNs leads to the strength and weakness index scores of the possible paths on given criteria. Furthermore, we define the total performance score of each project path using its strength and weakness index scores. The path that has the highest score is selected as the best alternative in terms of its criticality for the entire project to finish as per the chosen criteria. A numerical illustration is provided to demonstrate working of the proposed methodology.
This is a preview of subscription content,log in via an institution to check access.
Access this article
Subscribe and save
- Get 10 units per month
- Download Article/Chapter or eBook
- 1 Unit = 1 Article or 1 Chapter
- Cancel anytime
Buy Now
Price includes VAT (Japan)
Instant access to the full article PDF.


Similar content being viewed by others
References
Aggarwal, A., Chandra, S., & Mehra, A. (2014). Solving matrix games with I-fuzzy payoffs: Pareto-optimal security strategies approach.Fuzzy Information and Engineering,6, 167–192.
Ahuja, H. N., Dozzi, S. P., & Abourizk, S. M. (1994).Project management. New York: Wiley.
Atanassov, K. T. (1986). Intuitionistic fuzzy sets.Fuzzy Sets and Systems,20, 87–96.
Atanassov, K. T. (1999).Intuitionistic Fuzzy Sets. Heidelberg: Springer.
Avraham, S. (1997). Project segmentation-a tool for project management.International Journal of Project Management,15, 15–19.
Boffey, T. B. (1982).Graph theory in operations research. Hong Kong: The Macmillan Press Ltd.
Chanas, S., & Zielinski, P. (2001). Critical path analysis in the network with fuzzy activity times.Fuzzy Sets and Systems,122, 195–204.
Chanas, S., & Zielinski, P. (2002). The computational complexity of the criticality problems in a network with interval activity times.European Journal of Operational Research,136, 541–550.
Chen, S. P. (2007). Analysis of critical paths in a project networkwith fuzzy activity times.European Journal of Operational Research,183, 442–459.
Elizabeth, S., & Sujatha, L. (2015). Project scheduling method using triangular intuitionistic fuzzy numbers and triangular fuzzy number.Applied Mathematical Sciences,9, 185–198.
Jayagowri, P., & Geetharamani, G. (2014). A critical path problem using intuitionistic trapezoidal fuzzy number.Applied Mathematical Statistics,8, 2555–2562.
Jayagowri, P., & Geetharamani, G. (2015). Using metric distance ranking method to find intuitionistic fuzzy critical path.Journal of Applied Mathematics,2015(2015), 12.
Kaur, P., & Kumar, A. (2014). Linear programming approach for solving fuzzy critical path problems with fuzzy parameters.Applied Soft Computing,21, 309–319.
Kelley, J. E. (1961). Critical path planning and scheduling mathematical basis.Operations Research,9, 296–320.
Lee, H. S. (2005). A fuzzy multi-criteria decision making model for the selection of distribution center.Lecture Notes in Computer Science,3612, 1290–1299.
Liang, G. S., & Han, T. C. (2004). Fuzzy critical path for project network.Information and Management Sciences,15, 29–40.
Linstone, H. A., & Turoff, M. (1975).The Delphi method: Techniques and applications. Massachusetts: Addison Wesley.
Mehlawat, M. K., & Gupta, P. (2016). A new fuzzy group multi-criteria decision making method with an application to the critical path selection.The International Journal of Advance Manufacturing Technology,83, 1281–1296.
Mon, D. L., Cheng, C. H., & Lu, H. C. (1995). Application of fuzzy distribution on project management.Fuzzy Sets and Systems,73, 227–234.
Nasution, S. H. (2002). Fuzzy critical path method.IEEE Transactions on Systems, Man, and Cybernetics,24, 48–57.
Nehi, H. M. (2010). A new ranking method for intuitionistic fuzzy numbers.International Journal of Fuzzy Systems,12, 80–86.
Porchelvi, R. S., & Sudha, G. (2015). Critical path analysis in a project network using ranking method in intuitionistic fuzzy environment.International Journal of Advanced Research,3, 14–20.
Seikh, M. R., Pal, M., & Nayak, P. K. (2012). Application of triangular intuitionistic fuzzy numbers in bi-matrix games.International Journal of Pure and Applied Mathematics,79, 235–247.
Shankar, N. R., Sireesha, V., & Rao, P. P. B. (2010). An analytical method for finding critical path in a fuzzy project network.International Journal of Contemporary Mathematical Sciences,5, 953–962.
Slyeptsov, A. I., & Tyshchuk, T. A. (2003). Fuzzy temporal characteristics of operations for project management on the network models basis.European Journal of Operational Research,147, 253–265.
Soltani, A., & Haji, R. (2007). A project scheduling method based on fuzzy theory.Journal of Industrial and Systems Engineering,1, 70–80.
Taha, H. A. (2003).Operations research: An introduction (7th ed.). New Jersey: Prentice Hall.
Yoon, K. P., & Hwang, C. L. (1995).Multiple attribute decision making: An introduction. Thousand Oaks, CA: Sage Pub.
Yuan, Y. (1991). Criteria for evaluating fuzzy ranking methods.Fuzzy Sets and Systems,43, 139–157.
Zadeh, L. A. (1965). Fuzzy sets.Information and Control,8, 338–353.
Zadeh, L. A. (1975). The concept of a linguistic variable and its application to approximate reasoning-II.Information Sciences,8, 301–357.
Zielinski, P. (2005). On computing the latest starting times and floats of activities in a network with imprecise durations.Fuzzy Sets and Systems,150, 53–76.
Acknowledgements
Both the authors are thankful to the Editor and the reviewers for their valuable comments and detailed suggestions to improve the presentation of the paper. Further, first author acknowledges the support through Research and Development Grant received from University of Delhi, Delhi, India.
Author information
Authors and Affiliations
Department of Operational Research, University of Delhi, Delhi, India
Mukesh Kumar Mehlawat & Nishtha Grover
- Mukesh Kumar Mehlawat
You can also search for this author inPubMed Google Scholar
- Nishtha Grover
You can also search for this author inPubMed Google Scholar
Corresponding author
Correspondence toMukesh Kumar Mehlawat.
Rights and permissions
About this article
Cite this article
Mehlawat, M.K., Grover, N. Intuitionistic fuzzy multi-criteria group decision making with an application to critical path selection.Ann Oper Res269, 505–520 (2018). https://doi.org/10.1007/s10479-017-2477-4
Published:
Issue Date:
Share this article
Anyone you share the following link with will be able to read this content:
Sorry, a shareable link is not currently available for this article.
Provided by the Springer Nature SharedIt content-sharing initiative