We study a multi-criteria fuzzy decision-making method based on weighted triangular intuitionistic
fuzzy number correlation coefficients. Under the scenario that criteria weights for alternatives are completely
unknown, triangular intuitionistic fuzzy method can not only supplement the insufficiency of the method based
on the distance but also endow more information to the estimation and reduce the loss of evaluation information.
Among the triangular numbers, two boundary numbers are the maximum and minimum values of the interval
respectively, and the medium number is the most possible value under subjective estimation. Using this method,
we propose a new way to obtain the criteria weights with more information quantity. By ranking the relative
closeness of the weighted correlation coefficients between each alternative, and the critical and ideal alternatives,
we show the method to figure out the most suitable alternative based on the expected criteria. An illustrative
example is also taken into account to prove the effectiveness of the model.
WU Di (吴迪), YAN Xiangbin (闫相斌), PENG Rui* (彭锐), MA Xiaoyang (马晓洋)
. Multi-Criteria Decision Making Based on Correlation Coefficient of Triangular Intuitionistic Fuzzy Numbers[J]. Journal of Shanghai Jiaotong University(Science), 2019
, 24(4)
: 480
-484
.
DOI: 10.1007/s12204-019-2098-y
[1] ZADEH L A. Fuzzy sets [J]. Information and Control,1965, 8(3): 338-353.
[2] ATANASSOV K T. New operations defined over theintuitionistic fuzzy sets [J]. Fuzzy Sets and Systems,1994, 61(2): 137-142.
[3] ATANASSOV K, GARGOV G. Interval valued intuitionisticfuzzy sets [J]. Fuzzy Sets and Systems, 1989,31(3): 343-349.
[4] YUAN Y, GUAN T, YAN X B, et al. Multi-criteriadecision making model based on interval-valued intuitionisticfuzzy number correlation coefficient [J]. Journalof Management Sciences in China, 2014, 17(4):11-18.
[5] BUSTINCE H, BURILLO P. Correlation of intervalvaluedintuitionistic fuzzy sets [J]. Fuzzy Sets and Systems,1995, 74(2): 237-244.
[6] SZMIDT E, KACPRZYK J. Distances between intuitionisticfuzzy sets [J]. Fuzzy Sets and Systems, 2000,114(3): 505-518.
[7] GRZEGORZEWSKI P. Distances between intuitionisticfuzzy sets and/or interval-valued fuzzy sets basedon the Hausdorff metric [J]. Fuzzy Sets and Systems,2004, 148(2): 319-328.
[8] PARK D G, KWUN Y C, PARK J H, et al. Correlationcoefficient of interval-valued intuitionistic fuzzysets and its application to multiple attribute group decisionmaking problems [J]. Mathematical and ComputerModelling, 2009, 50(9/10): 1279-1293.
[9] LI D F, CHENG C T. New similarity measures of intuitionisticfuzzy sets and application to pattern recognitions[J]. Pattern Recognition Letters, 2002, 23(1):221-225.
[10] WEI C P, TANG X J. An intuitionistic fuzzy groupdecision-making approach based on entropy and similaritymeasures [J]. International Journal of InformationTechnology and Decision Making, 2011, 10(6):1111-1130.
[11] XU Z S, CAI X Q. Nonlinear optimization models formultiple attribute group decision making with intuitionisticfuzzy information [J]. International Journalof Intelligent Systems, 2010, 25(2): 489-513.
[12] YUE Z L. Deriving decision maker’s weights basedon distance measure for interval-valued intuitionisticfuzzy group decision making [J]. Expert Systems withApplications, 201l, 38: 11665-11670.
[13] WANG Z J, LI K W, WANG W Z. An approach tomultiattribute decision making with interval-valued intuitionisticfuzzy assessments and incomplete weights[J]. Information Sciences, 2009, 179(17): 3026-3040.
[14] WEI G W, YI W D. Method for intuitionistic fuzzymultiple attribute decision making without weight informationbut with preference information on alternatives[J]. 2008 Chinese Control and Decision Conference(CCDC 2008). Yantai, China: IEEE, 2008: 1970-1975.
[15] SU Z X, CHEN M Y, XIA G P, et al. An interactivemethod for dynamic intuitionistic fuzzy multiattributegroup decision making [J]. Expert Systemswith Applications, 2011, 38(12): 15286-15295.
[16] ZENG S Z. Some intuitionistic fuzzy weighted distancemeasures and their application to group decision making[J]. Group Decision and Negotiation, 2013, 22(2):281-298.
