Abstract
In this paper, we study a selection of admirable alternative consequence using specified alternatives, experts and criteria corresponding to the multi-criteria decision-making (MCDM) models. In this model, we select a process to established on Fuzzy Analytical Hierarchy Process (FAHP) method and Fuzzy Technique for Order Performance by Similarity to Ideal Solution (FTOPSIS) method is applied to get the weights through FAHP of each criterion by using pair wise comparison and FTOPSIS is applied for the closeness coefficients for final ranking of the solutions of chosen alternatives. Lastly, we demonstrated the result of the closeness coefficient solution and have defended our model to be structured and vigorous.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Simon HA (1977) The new science of management decision. Prentice-Hail, Englewood Cliffs, New Jersey, USA
Bellman RE, Zadeh LA (1970) Decision-making in a fuzzy environment. Manag Sci 17:141–164
Chen CT (2000) Extensions to the TOPSIS for group decision-making under fuzzy environment. Fuzzy Sets Syst 114:1–9
Chen SJ, Hwang CL (1992) Fuzzy multiple attribute decision making methods and application. Lecture Notes in Economics and Mathematical Systems, Springer, New York.
Hsu HM, Chen CT (1996) Aggregation of fuzzy opinions under group decision making. Fuzzy Sets Syst 79:279–285
Kacprzak J, Fedrizzi M, Nurmi H (1992) Group decision making and consensus under fuzzy preferences and fuzzy majority. Fuzzy Sets Syst 49:21–31
Liang GS (1992) Fuzzy MCDM based on ideal and anti-ideal notions. Eur J Oper Res 112:682–691
Tanino T (1984) Fuzzy preference in group decision making. Fuzzy Sets Syst 12:117–131
Wang YJ, Lee HS, Lin K (2003) Fuzzy TOPSIS for multi-criteria decision-making. Int Math J 3:367–379
Zadeh LA (1965) Fuzzy sets. Inf Control 8:338–353
Zimmermann HJ (1987) Fuzzy set, decision making and expert system. Kluwer, Boston
Hwang CL, Lin MJ (1987) Group decision making under multiple criteria: methods and applications. Springer-Verlag, Heidelberg
Saaty TL (1980) The analytic hierarchy process. planning, preference setting, resource allocation. McGraw-Hill
Zavadskas EK, Podvezko V (2016) Integrated determination of objective criteria weights in MCDM. Int J Inf Technol Decis Mak 15(2):267–283
Buckley JJ (1985) Fuzzy hierarchical analysis. Fuzzy Sets Syst 17(3):233–247
Buckley JJ, Feuring T, Hayashi Y (2001) Fuzzy hierarchical analysis revisited. Eur J Oper Res 129(1):48–64
Elomda BM, Hefny HA, Hassan HA (2013) An extension of fuzzy decision maps for multi-criteria decision-making. Egypt Inf J 14:147–155
Wu HY, Tzeng GH, Chen YH (2009) A fuzzy MCDM approach for evaluating banking performance based on balanced scorecard. Expert Syst Appl 36:10135–10147
Parida PK, Sahoo SK (2015) Fuzzy multiple attributes decision-making models using TOPSIS techniques. Int J Appl Eng Res 10(2):1433–1442
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Baral, S.P., Parida, P.K., Sahoo, S.K. (2023). Fuzzy TOPSIS Approaches for Multi-criteria Decision-Making Problems in Triangular Fuzzy Numbers. In: Saraswat, M., Chowdhury, C., Kumar Mandal, C., Gandomi, A.H. (eds) Proceedings of International Conference on Data Science and Applications. Lecture Notes in Networks and Systems, vol 551. Springer, Singapore. https://doi.org/10.1007/978-981-19-6631-6_33
Download citation
DOI: https://doi.org/10.1007/978-981-19-6631-6_33
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-19-6630-9
Online ISBN: 978-981-19-6631-6
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)