RESEARCH GAPS IN MULTI-CRITERIA DECSION MAKING METHODS FOR RESEARCHERS AS AN AREAS OF INTEREST
DOI:
https://doi.org/10.15282/jmmst.v4i2.3601Keywords:
MCDM; Dicision maker’s weights; Criteria weights, Variable weight theoryAbstract
The increase in Multi criteria decision-making studies is reflecting its importance as an interested area for research. Even though a high number of revealed studies mainly in last decade, still this field have challenges that require attentions from researchers in future. Most of MCDM related studies did not consider determining DM weights or using subjective methods, and there is an absence of implementing sensitivity analysis to DM weights as well. In addition to the need to develop new methods that utilizing the web or mobile technologies to deal with complexity and uncertainty adhered to MCDM problems. This paper represents a trial to list current challenges in this field as areas of interest for researchers in future studies that aims to enhance the quality and effectiveness of decision-making process.
References
Saltelli , P. Annoni , I. Azzini , F. Campolongo , M. Ratto , S. Tarantola , Variance based sensitivity analysis of model output. Design and estimator for the total sen- sitivity index, Comput. Phys. Commun. 181 (2010) 259–270.
Atanassov, K. (1986). Intuitionistic fuzzy sets. Fuzzy Sets and Systems, 20, 87–96.
Atanassov, K., & Gargov, G. (1989). Interval valued intuitionistic fuzzy sets. Fuzzy Sets and Systems, 31, 343–349.
Dey , B. Bairagi , B. Sarkar , S.K. Sanyal , Group heterogeneity in multi member decision making model with an application to warehouse location selection in a supply chain, Comput. Ind. Eng. 105 (2017) 101–122 .
Bustince, H., & Burillo, P. (1996). Vague sets are intuitionistic fuzzy sets. Fuzzy Sets and Systems, 79, 403–405.
Chin K-S, Fu C, Wang Y. A method of determining attribute weights in evidential reasoning approach based on incompatibility among attributes. Computers & Industrial Engineering. 2015; 87(0):150–62. http://dx.doi.org/10.1016/j.cie.2015.04.016
Dong Q, Cooper O. A peer-to-peer dynamic adaptive consensus reaching model for the group AHP decision making. European Journal of Operational Research. 2016; 250(2):521–30. https://doi.org/10.1016/j.ejor.2015.09.016.
D.J. Power , R. Sharda , F. Burstein , Decision Support Systems, Wiley Online Library, 2015 .
E. Triantaphyllou , A. Sánchez , A sensitivity analysis approach for some determin- istic multi ‐criteria decision ‐making methods, Dec. Sci. 28 (1997) 151–194 .
E.U. Choo , B. Schoner , W.C. Wedley , Interpretation of criteria weights in multicri- teria decision making, Comput. Ind. Eng. 37 (3) (1999) 527–541 .
Eslaminasab Z., Hamzehee A, Determining appropriate weight for criteria in multi criteria group decision making problems using an Lp model and similarity measure. (2019) doi 10.22111/ijfs.2019.4643
F.E. Boran, S. Genç, M. Kurt and D. Akay, “A multi-criteria intuitionistic fuzzy group decision making for supplier selection with TOPSIS method”, Expert Systems with Applications, vol. 36(8), pp. 11363-11368, 2009.
Garg. H, Generalized Intuitionistic Fuzzy Entropy-Based Approach for Solving Multi-attribute Decision-Making Problems with Unknown Attribute Weights. (2017) http://sites.google.com/site/harishg58iitr/
Gau, W. L., & Buehrer, D. J. (1993). Vague sets. IEEE Transactions on Systems Man and Cybernetics, 23, 610–614.
GovindanK, RajendranS, SarkisJ, MurugesanP. Multicriteria decision making approaches for green supplier evaluation and selection: a literature review .JClean Prod2015;98:66–83.
H. Arian, H. Ashkan, L. Huchang, H. Francisco, An overview of MULTIMOORA for multi-criteria decision-making: Theory, developments, applications, and challenges. (2019) https://doi.org/10.1016/j.inffus.2018.12.002
Hatefi. Mohammad, Indifference threshold-based attribute ratio analysis: A method for assigning the weights to the attributes in multiple attribute decision making. (2019) https://doi.org/10.1016/j.asoc.2018.10.050
I.J. Pérez , F.J. Cabrerizo , E. Herrera-Viedma , A mobile decision support system for dynamic group decision-making problems, IEEE Trans. Syst. Man Cybern.-Part A: Syst. Hum. 40 (2010) 1244–1256 .
J. Lu , G. Zhang , D. Ruan , F. Wu , Multi-objective Group Decision Making: Methods, Software and Applications With Fuzzy Set Techniques, World Scientific, 2007 .
Janković A, Popović M, METHODS FOR ASSIGNING WEIGHTS TO DECISION MAKERS IN GROUP AHP DECISION-MAKING. (2019) doi.org/10.31181/dmame1901147j
Kapur. P.K, Sachdeva. Nitin, A Hybrid Intuitionistic Fuzzy and Entropy Weight Based Multi-Criteria Decision Model with TOPSIS. (2018) https://doi.org/10.1007/978-981-10-7323-6_27
Koksalmis. Emrah, Kabak. Özgür, Deriving decision makers’ weights in group decision making: An overview of objective methods. (2019) . https://doi.org/10.1016/j.inffus.2018.11.009
Li H, Li L, Wang J, mo Z, Li Y, Fuzzy decision making based on variable weights. Mathematical and Computer Modelling. 2004; 39(2–3):163–79. http://dx.doi.org/10.1016/S0895-7177(04)90005-2.
Li. Jing, Fang. Hong, Song. Wenyan, Sustainable supplier selection based on SSCM practices: A rough cloud TOPSIS approach. (2019) https://doi.org/10.1016/j.jclepro.2019.03.070
Liu S, Chan FTS, Ran W. Decision making for the selection of cloud vendor: An improved approach under group decision-making with integrated weights and objective/subjective attributes. Expert Systems with Applications. 2016; 55:37–47. http://dx.doi.org/10.1016/j.eswa.2016.01.059.
Liu S, Chan FTS, Ran W. Multi-attribute group decision-making with multi-granularity linguistic assessment information: An improved approach based on deviation and TOPSIS. Applied Mathematical Modelling. 2013; 37(24):10129–40. http://dx.doi.org/10.1016/j.apm.2013.05.051.
Liu S, Chan FTS, Ran W. Multi-attribute group decision-making with multi-granularity linguistic assessment information: An improved approach based on deviation and TOPSIS. Applied Mathematical Modelling. 2013; 37(24):10129–40. http://dx.doi.org/10.1016/j.apm.2013.05.051.
Liu. Sen, Yu. Wei, LiuID. Ling, Hu. Yanan, Variable weights theory and its application to multi-attribute group decision making with intuitionistic fuzzy numbers on determining decision maker’s weights. (2019) https://doi.org/10.1371/journal.pone.0212636
Memaria . Ashkan, Dargib . Ahmad, Jokara. Mohammad, Ahmad. Robiah, , Abdul Rahim. Abd. Rahman, Sustainable supplier selection: A multi-criteria intuitionistic fuzzy TOPSIS method. (2019) https://doi.org/10.1016/j.jmsy.2018.11.002
Mendel. M, Wu D, Computing withWords for Hierarchical and Distributed Decision-Making. (2010) DOI 10.2991/978-94-91216-29-9_9
Ö. Kabak , B. Ervural , Multiple attribute group decision making: A generic concep- tual framework and a classification scheme, Knowl.-Based Syst. (2017) .
Ö. Kabak , B. Ervural , Multiple attribute group decision making: A generic concep- tual framework and a classification scheme, Knowl.-Based Syst. (2017) .
R. Ginevicius, A new determining method for the criteria weights in multicriteria evaluation, Int. J. Inf. Technol. Decis. Mak. 10 (6) (2011) 1067–1095.
Shanon CE (1948) A mathematical theory of communication. Bell Syst Tech J 27(3):379–423
W.K.M. Brauers , E.K. Zavadskas , Robustness of MULTIMOORA: a method for mul- ti-objective optimization, Informatica 23 (1) (2012) 1–25 .
Wan S, Wang F, Dong J. Additive consistent interval-valued Atanassov intuitionistic fuzzy preference relation and likelihood comparison algorithm based group decision making. European Journal of Operational Research. 2017; 263(2):571–82. https://doi.org/10.1016/j.ejor.2017.05.022.
Wan S-P, Dong J-Y. Interval-valued intuitionistic fuzzy mathematical programming method for hybrid multi-criteria group decision making with interval-valued intuitionistic fuzzy truth degrees. Information Fusion. 2015; 26(0):49–65. http://dx.doi.org/10.1016/j.inffus.2015.01.006.
Y. Chen , J. Yu , S. Khan , Spatial sensitivity analysis of multi-criteria weights in GIS-based land suitability evaluation, Environ. Model. Softw, 25 (2010) 1582–1591 .
Yalcin .Ahmet, Kilic. Huseyin, Green Supplier Selection via an Integrated Multi-Attribute Decision Making Approach. (2019)
Yue C. Entropy-based weights on decision makers in group decision-making setting with hybrid preference representations. Applied Soft Computing. 2017; 60:737–49. https://doi.org/10.1016/j.asoc.2017.07.033.
Yue C. Entropy-based weights on decision makers in group decision-making setting with hybrid preference representations. Applied Soft Computing. 2017; 60:737–49. https://doi.org/10.1016/j.asoc.2017.07.033.
Yue Z. Developing a straightforward approach for group decision making based on determining weights of decision makers. Applied Mathematical Modelling. 2012; 36(9):4106–17. http://dx.doi.org/10.1016/j.apm.2011.11.041.
Z. Eslaminasab, A. Hamzehee, Determining appropriate weight for criteria in multi criteria group decision making problems using an Lp model and similarity measure. (2019)
Z. Xu , Linguistic Decision Making: Theory and Methods, Springer-Verlag, Berlin Heidelberg, 2012 .
Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8, 338–353.
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