With respect to intuitionistic fuzzy multiple attribute decision making problems with completely unknown weight information, some operational laws of intuitionistic fuzzy numbers, score function and accuracy function of intuitionistic fuzzy numbers are introduced. To determine the attribute weights, a model based on the information entropy, by which the attribute weights can be determined, is established. We utilize the intuitionistic fuzzy Hamacher weighted averaging (IFHWA) operator to fuse the intuitionistic fuzzy information corresponding to each alternative, and then rank the alternatives and select the most desirable one(s) according to the score function and accuracy function. Finally, an illustrative example for evaluating the logistics efficiency of agricultural products is given to verify the developed approach and to demonstrate its practicality and effectiveness.
ZadehLA. Fuzzy sets. Information and Control.1965; 8(3): 338-56.
2.
AtanassovKT. Intuitionistic fuzzy sets. Fuzzy Sets and Systems.1986; 20(1): 87-96.
3.
HeYDHeZHuangH. Decision making with the generalized intuitionistic fuzzy power interaction averaging operators. Soft Computing.2017; 21(5): 1129-44.
4.
LiMWuC. A Distance Model of Intuitionistic Fuzzy Cross Entropy to Solve Preference Problem on Alternatives. Mathematical Problems in Engineering. 2016.
5.
LiangRXHeSSWangJQChenKLiL. An extended MABAC method for multi-criteria group decision-making problems based on correlative inputs of intuitionistic fuzzy information. Computational & Applied Mathematics.2019; 38(3): 28.
6.
ZhangLHeYD. Extensions of intuitionistic fuzzy geometric interaction operators and their application to cognitive microcredit origination. Cognitive Computation.2019; 11(5): 748-60.
7.
ChenSMChengSHLanTC. Multicriteria decision making based on the TOPSIS method and similarity measures between intuitionistic fuzzy values. Information Sciences.2016; 367: 279-95.
8.
KhanMSLohaniQMD, Ieee. A Similarity Measure For Atanassov Intuitionistic Fuzzy Sets and its Application to Clustering. 2016. 232-9.
9.
GargH. Novel intuitionistic fuzzy decision making method based on an improved operation laws and its application. Engineering Applications of Artificial Intelligence.2017; 60: 164-74.
10.
LiPLiuJLiuSFSuXWuJ. Grey target method for intuitionistic fuzzy decision making based on grey incidence analysis. Journal of Grey System.2016; 28(4): 96-109.
11.
LeiFWeiGWLuJPWeiCWuJ. GRA method for probabilistic linguistic multiple attribute group decision making with incomplete weight information and its application to waste incineration plants location problem. International Journal of Computational Intelligence Systems.2019; 12(2): 1547-56.
12.
BaoTTXieXLLongPYWeiZK. MADM method based on prospect theory and evidential reasoning approach with unknown attribute weights under intuitionistic fuzzy environment. Expert Systems with Applications.2017; 88: 305-17.
13.
GuptaPAroraHDTiwariP. Generalized entropy for intuitionistic fuzzy sets. Malaysian Journal of Mathematical Sciences.2016; 10(2): 209-20.
14.
LuJPWeiCWuJWeiGW. TOPSIS method for probabilistic linguistic MAGDM with entropy weight and its application to supplier selection of new agricultural machinery products. Entropy.2019; 21(10): 953.
15.
GanJWLuoL. Using DEMATEL and intuitionistic fuzzy sets to identify critical factors influencing the recycling rate of end-of-life vehicles in China. Sustainability.2017; 9(10).
16.
GuptaPMehlawatMKGroverNChenW. Modified intuitionistic fuzzy SIR approach with an application to supplier selection. Journal of Intelligent & Fuzzy Systems.2017; 32(6): 4431-41.
17.
KrishankumarRRavichandranKSSaeidAB. A new extension to PROMETHEE under intuitionistic fuzzy environment for solving supplier selection problem with linguistic preferences. Applied Soft Computing.2017; 60: 564-76.
18.
LiuPLiuJChenS-M. Some intuitionistic fuzzy Dombi Bonferroni mean operators and their application to multi-attribute group decision making. Journal of the Operational Research Society.2018; 69(1): 1-24.
19.
WeiGWWuJWeiCWangJLuJP. Models for MADM With 2-Tuple Linguistic Neutrosophic Dombi Bonferroni Mean Operators. Ieee Access.2019; 7: 108878-905.
20.
HaoZNXuZSZhaoHZhangR. Novel intuitionistic fuzzy decision making models in the framework of decision field theory. Information Fusion.2017; 33: 57-70.
21.
GouXJXuZSLeiQ. New operational laws and aggregation method of intuitionistic fuzzy information. Journal of Intelligent & Fuzzy Systems.2016; 30(1): 129-41.
22.
JinFFNiZWChenHYLiYP. Approaches to group decision making with intuitionistic fuzzy preference relations based on multiplicative consistency. Knowledge-Based Systems.2016; 97: 48-59.
23.
LuoXWangXZ. Extended VIKOR Method for Intuitionistic Fuzzy Multiattribute Decision-Making Based on a New Distance Measure. Mathematical Problems in Engineering. 2017.
24.
WuLPGaoHWeiC. VIKOR method for financing risk assessment of rural tourism projects under interval-valued intuitionistic fuzzy environment. Journal of Intelligent & Fuzzy Systems.2019; 37(2): 2001-8.
25.
LuJPWeiC. TODIM method for performance appraisal on social-integration-based rural reconstruction with interval-valued intuitionistic fuzzy information. Journal of Intelligent & Fuzzy Systems.2019; 37(2): 1731-40.
26.
WuLPWangJGaoH. Models for competiveness evaluation of tourist destination with some interval-valued intuitionistic fuzzy Hamy mean operators. Journal of Intelligent & Fuzzy Systems.2019; 36(6): 5693-709.
27.
WuLPWeiGWWuJWeiC. Some interval-valued intuitionistic fuzzy dombi heronian mean operators and their application for evaluating the ecological value of forest ecological tourism demonstration areas. International Journal of Environmental Research and Public Health.2020; 17(3): 829.
28.
WangJWeiGWWeiCWeiY. Dual hesitant q-rung orthopair fuzzy muirhead mean operators in multiple attribute decision making. Ieee Access.2019; 7: 67139-66.
29.
HeTZhangSWeiGWangRWuJWeiC. CODAS method for 2-tuple linguistic pythagorean fuzzy multiple attribute group decision making and its application to financial management performance assessment. Technological and Economic Development of Economy.2020; 26(4): 920-32.
30.
WeiGLeiFLinRWangRWeiYWuJ, et al. Algorithms for probabilistic uncertain linguistic multiple attribute group decision making based on the GRA and CRITIC method: Application to location planning of electric vehicle charging stations. Economic Research-Ekonomska Istraživanja.2020; 33(1): 828-46.
31.
AtanassovKT. More on intuitionistic fuzzy-sets. Fuzzy Sets and Systems.1989; 33(1): 37-45.
32.
LiuHWWangGJ. Multi-criteria decision-making methods based on intuitionistic fuzzy sets. European Journal of Operational Research.2007; 179(1): 220-33.
33.
HuangJY. Intuitionistic fuzzy Hamacher aggregation operators and their application to multiple attribute decision making. Journal of Intelligent & Fuzzy Systems.2014; 27(1): 505-13.
34.
FurtanWH. Entropy, information and economics in firm decision-making. International Journal of Systems Science.1977; 8(10): 1105-12.
XuZSYagerRR. Some geometric aggregation operators based on intuitionistic fuzzy sets. International Journal of General Systems.2006; 35(4): 417-33.
37.
LiangRXHeSSWangJQChenKLiL. An extended MABAC method for multi-criteria group decision-making problems based on correlative inputs of intuitionistic fuzzy information. Computational & Applied Mathematics.2019; 38(3).
38.
WeiGW. GRA method for multiple attribute decision making with incomplete weight information in intuitionistic fuzzy setting. Knowledge-Based Systems.2010; 23(3): 243-7.
39.
WangPLiuPD. Some Maclaurin symmetric mean aggregation operators based on Schweizer-Sklar operations for intuitionistic fuzzy numbers and their application to decision making. Journal of Intelligent & Fuzzy Systems.2019; 36(4): 3801-24.
40.
WeiGWLuJPWeiCWuJ. Probabilistic linguistic GRA method for multiple attribute group decision making. Journal of Intelligent & Fuzzy Systems.2020; 38(4): 4721-32.
41.
ZhangSWeiGAlsaadiFEHayatTWeiCZhangZ. MABAC method for multiple attribute group decision making under picture 2-tuple linguistic environment. Soft Computing.2020; 24(8): 5819-29.
42.
MousaviSMAntuchevicieneJZavadskasEKVahdaniBHashemiH. A new decision model for cross-docking center location in logistics networks under interval-valued intuitionistic fuzzy uncertainty. Transport.2019; 34(1): 30-40.
43.
RoyJSharmaHKKarSZavadskasEKSaparauskasJ. An extended COPRAS model for multi-criteria decision-making problems and its application in web-based hotel evaluation and selection. Economic Research-Ekonomska Istrazivanja.2019; 32(1): 219-53.
44.
StanujkicDKarabasevicDSmarandacheFZavadskasEKMaksimovicM. An innovative approach to evaluation of the quality of websites in the tourism industry: A novel mcdm approach based on bipolar neutrosophic numbers and the hamming distance. Transformations in Business & Economics.2019; 18(1): 149-62.
45.
StanujkicDKarabasevicDZavadskasEKSmarandacheFCavallaroF. An approach to determining customer satisfaction in traditional serbian restaurants. Entrepreneurship and Sustainability Issues.2019; 6(3): 1127-38.
