Approaches to Multiple Attribute Decision Making with Interval-Valued 2-Tuple Linguistic Pythagorean Fuzzy Information
Abstract
:1. Introduction
2. Preliminaries
2.1. 2-Tuple Linguistic Sets
2.2. Pythagorean Fuzzy Sets
- (1)
- if, then;
- (2)
- if, then
- (i)
- if, then;
- (ii)
- if, then.
2.3. Interval-Valued Pythagorean Fuzzy Sets
2.4. Interval-Valued 2-Tuple Linguistic Pythagorean Fuzzy Sets
- (1)
- (2)
- (3)
- (4)
- (5)
- (1)
- (2)
- (3)
- (4)
2.5. Maclaurin Symmetric Mean Operators
3. Interval-Valued 2-Tuple Linguistic Pythagorean Fuzzy MSM and Interval-Valued 2-Tuple Linguistic Pythagorean Fuzzy Weighted MSM Operators
3.1. The IV2TLPFMSM Operator
- ①
- ②
3.2. The IV2TLPFWMSM Operator
- ①
- ②
4. The Interval-Valued 2-Tuple Linguistic Pythagorean Fuzzy Generalized MSM (IV2TLPFGMSM) and Interval-Valued 2-Tuple Linguistic Pythagorean Fuzzy Weighted GMSM (IV2TLPFWGMSM) Operators
4.1. IV2TLPFGMSM Operator
- ①
- ②
4.2. The IV2TLPFWGMSM Operator
- ①
- ②
5. The IV2TLPFDMSM and IV2TLPFWDMSM Operators
5.1. IV2TLPFDMSM Operator
- ①
- ②
5.2. The IV2TLPFWDMSM Operator
- ①
- ②
6. Numerical Example and Comparative Analysis
6.1. Numerical Example
6.2. Influence of the Parameter on the Final Result
6.3. Comparative Analysis
7. Conclusions
Author Contributions
Funding
Conflicts of Interest
References
- Atanassov, K. Intuitionistic fuzzy sets. Fuzzy Sets Syst. 1986, 20, 87–96. [Google Scholar] [CrossRef]
- Atanassov, K. Two theorems for intuitionistic fuzzy sets. Fuzzy Sets Syst. 2000, 110, 267–269. [Google Scholar] [CrossRef]
- Zadeh, L.A. Fuzzy sets. Inf. Control 1965, 8, 338–356. [Google Scholar] [CrossRef]
- Yager, R.R. Pythagorean fuzzy subsets. In Proceedings of the Joint IFSA World Congress and NAFIPS Annual Meeting, Edmonton, AB, Canada, 24–28 June 2013; pp. 57–61. [Google Scholar]
- Yager, R.R. Pythagorean membership grades in multicriteria decision making. IEEE Trans. Fuzzy Syst. 2014, 22, 958–965. [Google Scholar] [CrossRef]
- Zhang, X.L.; Xu, Z.S. Extension of TOPSIS to multiple criteria decision making with Pythagorean fuzzy sets. Int. J. Intell. Syst. 2014, 29, 1061–1078. [Google Scholar] [CrossRef]
- Peng, X.; Yang, Y. Some results for Pythagorean Fuzzy Sets. Int. J. Intell. Syst. 2015, 30, 1133–1160. [Google Scholar] [CrossRef]
- Ren, P.; Xu, Z.; Gou, X. Pythagorean fuzzy TODIM approach to multi-criteria decision making. Appl. Soft Comput. 2016, 42, 246–259. [Google Scholar] [CrossRef]
- Garg, H. A New Generalized Pythagorean Fuzzy Information Aggregation Using Einstein Operations and Its Application to Decision Making. Int. J. Intell. Syst. 2016, 31, 886–920. [Google Scholar] [CrossRef]
- Zhang, X. Multicriteria Pythagorean fuzzy decision analysis: A hierarchical QUALIFLEX approach with the closeness index-based ranking methods. Inf. Sci. 2016, 330, 104–124. [Google Scholar] [CrossRef]
- Chen, T.-Y. Remoteness index-based Pythagorean fuzzy VIKOR methods with a generalized distance measure for multiple criteria decision analysis. Inf. Fusion 2018, 41, 129–150. [Google Scholar] [CrossRef]
- Peng, X.; Yang, Y. Pythagorean Fuzzy Choquet Integral Based MABAC Method for Multiple Attribute Group Decision Making. Int. J. Intell. Syst. 2016, 31, 989–1020. [Google Scholar] [CrossRef]
- Zeng, S.; Chen, J.; Li, X. A Hybrid Method for Pythagorean Fuzzy Multiple-Criteria Decision Making. Int. J. Inf. Technol. Decis. Mak. 2016, 15, 403–422. [Google Scholar] [CrossRef]
- Garg, H. A novel accuracy function under interval-valued Pythagorean fuzzy environment for solving multicriteria decision making problem. J. Intell. Fuzzy Syst. 2016, 31, 529–540. [Google Scholar] [CrossRef]
- Wei, G.W. Pythagorean fuzzy interaction aggregation operators and their application to multiple attribute decision making. J. Intell. Fuzzy Syst. 2017, 33, 2119–2132. [Google Scholar] [CrossRef]
- Wei, G.W.; Alsaadi, F.E.; Hayat, T.; Alsaedi, A. Picture 2-tuple linguistic aggregation operators in multiple attribute decision making. Soft Comput. 2018, 22, 989–1002. [Google Scholar] [CrossRef]
- Wei, G.W. Picture uncertain linguistic Bonferroni mean operators and their application to multiple attribute decision making. Kybernetes 2017, 46, 1777–1800. [Google Scholar] [CrossRef]
- Wei, G.W. Interval-valued dual hesitant fuzzy uncertain linguistic aggregation operators in multiple attribute decision making. J. Intell. Fuzzy Syst. 2017, 33, 1881–1893. [Google Scholar] [CrossRef]
- Wei, G.W. Picture 2-tuple linguistic Bonferroni mean operators and their application to multiple attribute decision making. Int. J. Fuzzy Syst. 2017, 19, 997–1010. [Google Scholar] [CrossRef]
- Wei, G.W.; Lu, M.; Alsaadi, F.E.; Hayat, T.; Alsaedi, A. Pythagorean 2-tuple linguistic aggregation operators in multiple attribute decision making. J. Intell. Fuzzy Syst. 2017, 33, 1129–1142. [Google Scholar] [CrossRef]
- Lu, M.; Wei, G.W.; Alsaadi, F.E.; Hayat, T.; Alsaedi, A. Bipolar 2-tuple linguistic aggregation operators in multiple attribute decision making. J. Intell. Fuzzy Syst. 2017, 33, 1197–1207. [Google Scholar] [CrossRef]
- Wei, G.W. Picture fuzzy aggregation operators and their application to multiple attribute decision making. J. Intell. Fuzzy Syst. 2017, 33, 713–724. [Google Scholar] [CrossRef]
- Wei, G.W. Interval valued hesitant fuzzy uncertain linguistic aggregation operators in multiple attribute decision making. Int. J. Mach. Learn. Cybern. 2016, 7, 1093–1114. [Google Scholar] [CrossRef]
- Wei, G.W.; Alsaadi, F.E.; Hayat, T.; Alsaedi, A. Hesitant fuzzy linguistic arithmetic aggregation operators in multiple attribute decision making. Iran. J. Fuzzy Syst. 2016, 13, 1–16. [Google Scholar]
- Wei, G.W.; Lu, M. Pythagorean fuzzy power aggregation operators in multiple attribute decision making. Int. J. Intell. Syst. 2018, 33, 169–186. [Google Scholar] [CrossRef]
- Yager, R.R. The power average operator. IEEE Trans. Syst. Man, Cybern. Part A 2001, 31, 724–731. [Google Scholar] [CrossRef]
- Xu, Z.S.; Yager, R.R. Power-Geometric operators and their use in group decision making. IEEE Trans. Fuzzy Syst. 2010, 18, 94–105. [Google Scholar]
- Garg, H. Complex Intuitionistic Fuzzy Power Aggregation Operators and Their Applications in Multi-Criteria Decision-Making, Expert Systems; Wiley: Hoboken, NJ, USA, 2018. [Google Scholar] [CrossRef]
- Wei, G.W.; Zhao, X.F.; Wang, H.J.; Lin, R. Fuzzy power aggregating operators and their application to multiple attribute group decision making. Technol. Econ. Dev. Econ. 2013, 19, 377–396. [Google Scholar] [CrossRef]
- Wei, G.W.; Lu, M. Pythagorean Fuzzy Maclaurin Symmetric Mean Operators in multiple attribute decision making. Int. J. Intell. Syst. 2018, 33, 1043–1070. [Google Scholar] [CrossRef]
- Maclaurin, C. A second letter to Martin Folkes, Esq.; concerning the roots of equations, with demonstration of other rules of algebra. Philos. Trans. R. Soc. Lond. Ser A 1729, 36, 59–96. [Google Scholar]
- Wan, S.; Jin, Z.; Dong, J. Pythagorean fuzzy mathematical programming method for multi-attribute group decision making with Pythagorean fuzzy truth degrees. Knowl. Inf. Syst. 2018, 55, 437–466. [Google Scholar] [CrossRef]
- Peng, X.; Dai, J. Approaches to Pythagorean Fuzzy Stochastic Multi-criteria Decision Making Based on Prospect Theory and Regret Theory with New Distance Measure and Score Function. Int. J. Intell. Syst. 2017, 32, 1187–1214. [Google Scholar] [CrossRef]
- Garg, H. A Linear Programming Method Based on an Improved Score Function for Interval-Valued Pythagorean Fuzzy Numbers and Its Application to Decision-Making. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 2018, 26, 67–80. [Google Scholar] [CrossRef]
- Chen, T.-Y. An Interval-Valued Pythagorean Fuzzy Outranking Method with a Closeness-Based Assignment Model for Multiple Criteria Decision Making. Int. J. Intell. Syst. 2018, 33, 126–168. [Google Scholar] [CrossRef]
- Garg, H. A Novel Improved Accuracy Function for Interval Valued Pythagorean Fuzzy Sets and Its Applications in the Decision-Making Process. Int. J. Intell. Syst. 2017, 32, 1247–1260. [Google Scholar] [CrossRef]
- Zhang, H. The multiattribute group decision making method based on aggregation operators with interval-valued 2-tuple linguistic information. Math. Comput. Model. 2012, 56, 27–35. [Google Scholar] [CrossRef]
- Herrera, F.; Martinez, L. A 2-tuple fuzzy linguistic representation model for computing with words. IEEE Trans. Fuzzy Syst. 2000, 8, 746–752. [Google Scholar]
- Herrera, F.; Martinez, L. An approach for combining linguistic and numerical information based on the 2-tuple fuzzy linguistic representation model in decision-making. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 2000, 8, 539–562. [Google Scholar] [CrossRef]
- Detemple, D.; Robertson, J. On generalized symmetric means of two variables. Univ. Beograd. Publ. Elektrotehn. Fak. Ser. Mat. Fiz. 1979, No. 634/677. 236–238. [Google Scholar]
- Bapat, R.B. Symmetrical function means and permanents. Linear Algebra Its Appl. 1993, 182, 101–108. [Google Scholar] [CrossRef]
- Abu-Saris, R.; Hajja, M. On Gauss compounding of symmetric weighted arithmetic means. J. Math. Anal. Appl. 2006, 322, 729–734. [Google Scholar] [CrossRef]
- Cuttler, A.; Greene, C.; Skandera, M. Inequalities for symmetric means. Eur. J. Comb. 2011, 32, 745–761. [Google Scholar] [CrossRef]
- Qin, J.D.; Liu, X.W. Approaches to uncertain linguistic multiple attribute decision making based on dual Maclaurin symmetric mean. J. Intell. Fuzzy Syst. 2015, 29, 171–186. [Google Scholar] [CrossRef]
- Wei, G.W.; Alsaadi, F.E.; Hayat, T.; Alsaedi, A. Bipolar fuzzy Hamacher aggregation operators in multiple attribute decision making. Int. J. Fuzzy Syst. 2018, 20, 1–12. [Google Scholar] [CrossRef]
- Verma, R. Multiple attribute group decision making based on generalized trapezoid fuzzy linguistic prioritized weighted average operator. Int. J. Mach. Learn. Cybern. 2017, 8, 1993–2007. [Google Scholar] [CrossRef]
- Wei, G.W. Some similarity measures for picture fuzzy sets and their applications. Iran. J. Fuzzy Syst. 2018, 15, 77–89. [Google Scholar]
- Akram, M.; Shahzadi, S. Novel intuitionistic fuzzy soft multiple-attribute decision-making methods. Neural Comput. Appl. 2018, 29, 435–447. [Google Scholar] [CrossRef]
- Wei, G.W.; Alsaadi, F.E.; Hayat, T.; Alsaedi, A. Projection models for multiple attribute decision making with picture fuzzy information. Int. J. Mach. Learn. Cybern. 2018, 9, 713–719. [Google Scholar] [CrossRef]
- Chen, T. The inclusion-based TOPSIS method with interval-valued intuitionistic fuzzy sets for multiple criteria group decision making. Appl. Soft Comput. 2015, 26, 57–73. [Google Scholar] [CrossRef]
- Wei, G.W.; Gao, H. The generalized Dice similarity measures for picture fuzzy sets and their applications. Informatica 2018, 29, 1–18. [Google Scholar] [CrossRef]
- Park, J.H.; Kwark, H.E.; Kwun, Y.C. Entropy and Cross-entropy for Generalized Hesitant Fuzzy Information and Their Use in Multiple Attribute Decision Making. Int. J. Intell. Syst. 2017, 32, 266–290. [Google Scholar] [CrossRef]
- Wei, G.; Wei, Y. Some single-valued neutrosophic dombi prioritized weighted aggregation operators in multiple attribute decision making. J. Intell. Fuzzy Syst. 2018, 35, 2001–2013. [Google Scholar] [CrossRef]
- Al-Quran, A.; Hassan, N. The Complex Neutrosophic Soft Expert Relation and Its Multiple Attribute Decision-Making Method. Entropy 2018, 20, 101. [Google Scholar] [CrossRef]
- Gao, H.; Wei, G.W.; Huang, Y.H. Dual hesitant bipolar fuzzy Hamacher prioritized aggregation operators in multiple attribute decision making. IEEE Access 2018, 6, 11508–11522. [Google Scholar] [CrossRef]
- Wang, C.; Chen, S. A new multiple attribute decision making method based on linear programming methodology and novel score function and novel accuracy function of interval-valued intuitionistic fuzzy values. Inf. Sci. 2018, 438, 145–155. [Google Scholar] [CrossRef]
- Huang, Y.H.; Wei, G.W. TODIM Method for Pythagorean 2-tuple Linguistic Multiple Attribute Decision Making. J. Intell. Fuzzy Syst. 2018, 35, 901–915. [Google Scholar] [CrossRef]
- Wu, S.; Wang, J.; Wei, G.; Wei, Y. Research on Construction Engineering Project Risk Assessment with Some 2-Tuple Linguistic Neutrosophic Hamy Mean Operators. Sustainability 2018, 10, 1536. [Google Scholar] [CrossRef]
- Wang, J.; Wei, G.W.; Wei, Y. Models for Green Supplier Selection with Some 2-Tuple Linguistic Neutrosophic Number Bonferroni Mean Operators. Symmetry 2018, 10, 131. [Google Scholar] [CrossRef]
- Merigo, J.M.; Gil-Lafuente, A.M. Fuzzy induced generalized aggregation operators and its application in multi-person decision making. Expert Syst. Appl. 2011, 38, 9761–9772. [Google Scholar] [CrossRef]
- Garg, H. Linguistic Pythagorean fuzzy sets and its applications in multi attribute decision making process. Int. J. Intell. Syst. 2018, 33, 1234–1263. [Google Scholar] [CrossRef]
- Wang, C.; Chen, S. Multiple attribute decision making based on interval-valued intuitionistic fuzzy sets, linear programming methodology, and the extended TOPSIS method. Inf. Sci. 2017, 397, 155–167. [Google Scholar] [CrossRef]
- Garg, H. New Logarithmic operational laws and their aggregation operators for Pythagorean fuzzy set and their applications. Int. J. Intell. Syst. 2018, 33, 653–683. [Google Scholar] [CrossRef]
- Wei, G.W.; Gao, H.; Wei, Y. Some q-Rung Orthopair Fuzzy Heronian Mean Operators in Multiple Attribute Decision Making. Int. J. Intell. Syst. 2018, 33, 1426–1458. [Google Scholar] [CrossRef]
- Garg, H. Some methods for strategic decision-making problems with immediate probabilities in Pythagorean fuzzy environment. Int. J. Intell. Syst. 2018, 33, 687–712. [Google Scholar] [CrossRef]
- Mohagheghi, V.; Mousavi, S.M.; Vahdani, B. Enhancing decision-making flexibility by introducing a new last aggregation evaluating approach based on multi-criteria group decision making and Pythagorean fuzzy sets. Appl. Soft Comput. 2017, 61, 527–535. [Google Scholar] [CrossRef]
- Deng, X.M.; Wei, G.; Gao, H.; Wang, J. Models for safety assessment of construction project with some 2-tuple linguistic Pythagorean fuzzy Bonferroni mean operators. IEEE Access 2018, 6, 52105–52137. [Google Scholar] [CrossRef]
- Garg, H. Pythagorean fuzzy Maclaurin symmetric mean operators and its applications to multiattribute decision making process. Int. J. Intell. Syst. 2018. [Google Scholar] [CrossRef]
- Gao, H. Pythagorean Fuzzy Hamacher Prioritized Aggregation Operators in Multiple Attribute Decision Making. J. Intell. Fuzzy Syst. 2018, 35, 2229–2245. [Google Scholar] [CrossRef]
- Garg, H.; Arora, R. Novel scaled prioritized intuitionistic fuzzy soft interaction averaging aggregation operators and their application to multi criteria decision making. Eng. Appl. AI 2018, 71, 100–112. [Google Scholar] [CrossRef]
- Garg, H. Confidence levels based Pythagorean fuzzy aggregation operators and its application to decision-making process. Comput. Math. Organ. Theory 2017, 23, 546–571. [Google Scholar] [CrossRef]
- Baloglu, U.B.; Demir, Y. An Agent-Based Pythagorean Fuzzy Approach for Demand Analysis with Incomplete Information. Int. J. Intell. Syst. 2018, 33, 983–997. [Google Scholar] [CrossRef]
- Tang, X.Y.; Wei, G.W. Models for green supplier selection in green supply chain management with Pythagorean 2-tuple linguistic information. IEEE Access 2018, 6, 18042–18060. [Google Scholar] [CrossRef]
- Wang, J.; Wei, G.; Lu, M. TODIM Method for Multiple Attribute Group Decision Making under 2-Tuple Linguistic Neutrosophic Environment. Symmetry 2018, 10, 486. [Google Scholar] [CrossRef]
- Hao, Y.; Chen, X. Study on the ranking problems in multiple attribute decision making based on interval-valued intuitionistic fuzzy numbers. Int. J. Intell. Syst. 2018, 33, 560–572. [Google Scholar] [CrossRef]
- Wei, G.W. Picture fuzzy Hamacher aggregation operators and their application to multiple attribute decision making. Fundam. Inform. 2018, 157, 271–320. [Google Scholar] [CrossRef]
- Wei, G.W.; Gao, H.; Wang, J.; Huang, Y.H. Research on Risk Evaluation of Enterprise Human Capital Investment with Interval-valued bipolar 2-tuple linguistic Information. IEEE Access 2018, 6, 35697–35712. [Google Scholar] [CrossRef]
- Beliakov, G.; James, S.; Mordelov´a, J.; Ruckschlossov´a, T.; Yager, R.R. Generalized Bonferroni mean operators in multicriteria aggregation. Fuzzy Sets Syst. 2010, 161, 2227–2242. [Google Scholar] [CrossRef]
- Wei, G.W. Some cosine similarity measures for picture fuzzy sets and their applications to strategic decision making. Informatica 2017, 28, 547–564. [Google Scholar] [CrossRef]
- Garg, H. Generalized Pythagorean Fuzzy Geometric Aggregation Operators Using Einsteint-Norm and t-Conorm for Multicriteria Decision-Making Process. Int. J. Intell. Syst. 2017, 32, 597–630. [Google Scholar] [CrossRef]
- Garg, H. Some picture fuzzy aggregation operators and their applications to multicriteria decision-making. Arabian J. Sci. Eng. 2017, 42, 5275–5290. [Google Scholar] [CrossRef]
- Wei, G.W.; Wei, Y. Similarity measures of Pythagorean fuzzy sets based on cosine function and their applications. Int. J. Intell. Syst. 2018, 33, 634–652. [Google Scholar] [CrossRef]
- Garg, H. Novel intuitionistic fuzzy decision making method based on an improved operation laws and its application. Eng. Appl. AI 2017, 60, 164–174. [Google Scholar] [CrossRef]
- Smarandache, F. Neutrosophic Perspectives: Triplets, Duplets, Multisets, Hybrid. Operators, Modal Logic., Hedge Algebras. And Applications; Amazon.com: Seattle, WA, USA, 2017; Pons Editions, 1st ed.; June 2017; 324p. 2nd ed.; September 2017; 346p. [Google Scholar]
A1 | {[(s2,0),(s3,0)],[(s1,0),(s2,0)]} | {[(s2,0),(s4,0)],[(s2,0),(s3,0)]} |
A2 | {[(s1,0),(s2,0)],[(s2,0),(s3,0)]} | {[(s2,0),(s3,0)],[(s1,0),(s2,0)]} |
A3 | {[(s3,0),(s4,0)],[(s1,0),(s2,0)]} | {[(s3,0),(s5,0)],[(s1,0),(s2,0)]} |
A4 | {[(s2,0),(s3,0)],[(s1,0),(s2,0)]} | {[(s2,0),(s3,0)],[(s2,0),(s3,0)]} |
A5 | {[(s1,0),(s2,0)],[(s2,0),(s3,0)]} | {[(s2,0),(s4,0)],[(s2,0),(s3,0)]} |
A1 | {[(s1,0),(s2,0)],[(s1,0),(s3,0)]} | {[(s2,0),(s3,0)],[(s1,0),(s2,0)]} |
A2 | {[(s2,0),(s3,0)],[(s1,0),(s4,0)]} | {[(s1,0),(s2,0)],[(s2,0),(s3,0)]} |
A3 | {[(s3,0),(s4,0)],[(s2,0),(s4,0)]} | {[(s1,0),(s2,0)],[(s2,0),(s3,0)]} |
A4 | {[(s1,0),(s2,0)],[(s1,0),(s3,0)]} | {[(s1,0),(s2,0)],[(s2,0),(s3,0)]} |
A5 | {[(s1,0),(s2,0)],[(s1,0),(s4,0)]} | {[(s1,0),(s2,0)],[(s1,0),(s3,0)]} |
Aggregation Operator | Green Supplier | Operation Results |
---|---|---|
IV2TLPFWMSM | A1 | {[(s1,0.4990),(s3,−0.3639)],[(s2,0.0079),(s3,0.2511)]} |
A2 | {[(s1,0.4130),(s2,0.2682)],[(s2,0.3463),(s4,−0.2297)]} | |
A3 | {[(s2,0.2948),(s3,0.4641)],[(s2,0.3800),(s4,−0.4372)]} | |
A4 | {[(s1,0.3026),(s2,0.1673)],[(s2,0.0079),(s3,0.4758)]} | |
A5 | {[(s1,0.1226),(s2,0.2467)],[(s2,0.2644),(s4,−0.0822)]} | |
IV2TLPFWGMSM | A1 | {[(s4,0.2143),(s5,−0.2477)],[(s1,0.0561),(s2,−0.1623)]} |
A2 | {[(s4,0.1090),(s5,−0.4737)],[(s1,0.1838),(s2,0.0989)]} | |
A3 | {[(s5,−0.4698),(s5,0.1698)],[(s1,0.2394),(s2,0.−0307)]} | |
A4 | {[(s4,0.0031),(s5,0.−4490)],[(s1,0.0561),(s2,−0.0399)]} | |
A5 | {[(s4,−0.1988),(s5,−0.3714)],[(s1,0.1872),(s2,0.2531)]} | |
IV2TLPFWDMSM | A1 | {[(s2,−0.4993),(s3,−0.3427)],[(s2,0.0023),(s3,0.2460)]} |
A2 | {[(s1,0.3906),(s2,0.2675)],[(s2,0.3993),(s4,−0.2651)]} | |
A3 | {[(s2,0.3027),(s3,0.4920)],[(s2,0.3663),(s4,−0.4670)]} | |
A4 | {[(s1,0.3020),(s2,0.1752)],[(s2,0.0023),(s3,0.4677)]} | |
A5 | {[(s1,0.1240),(s2,0.2680)],[(s2,0.2492),(s4,−0.0989)]} |
IV2TLPFWMSM | IV2TLPFWGMSM | IV2TLPFWDMSM | |
---|---|---|---|
A1 | 0.6800 | 0.8693 | 0.6809 |
A2 | 0.6424 | 0.8409 | 0.6421 |
A3 | 0.7017 | 0.8891 | 0.7042 |
A4 | 0.6577 | 0.8489 | 0.6582 |
A5 | 0.6337 | 0.8391 | 0.6354 |
Methods | Ordering |
---|---|
IV2TLPFWMSM | A3>A1>A4>A2>A5 |
IV2TLPFWGMSM | A3>A1>A4>A2>A5 |
IV2TLPFWDMSM | A3>A1>A4>A2>A5 |
s(A1) | s(A2) | s(A3) | s(A4) | s(A5) | Ordering | |
---|---|---|---|---|---|---|
K = 1 | 0.6909 | 0.6717 | 0.7366 | 0.6655 | 0.6567 | A3>A1>A2>A4>A5 |
K = 2 | 0.6800 | 0.6424 | 0.7017 | 0.6577 | 0.6337 | A3>A1>A4>A2>A5 |
K = 3 | 0.6755 | 0.6286 | 0.6884 | 0.6539 | 0.6243 | A3>A1>A4>A2>A5 |
K = 4 | 0.6724 | 0.6210 | 0.6748 | 0.6514 | 0.6176 | A3>A1>A4>A2>A5 |
s(A1) | s(A2) | s(A3) | s(A4) | s(A5) | Ordering | |
---|---|---|---|---|---|---|
K = 1 | 0.4948 | 0.4729 | 0.5184 | 0.4723 | 0.4537 | A3>A1>A2>A4>A5 |
K = 2 | 0.8693 | 0.8409 | 0.8891 | 0.8489 | 0.8391 | A3>A1>A4>A2>A5 |
K = 3 | 0.8140 | 0.7821 | 0.8383 | 0.7914 | 0.7766 | A3>A1>A4>A2>A5 |
K = 4 | 0.7573 | 0.7337 | 0.7906 | 0.7391 | 0.7205 | A3>A1>A4>A2>A5 |
s(A1) | s(A2) | s(A3) | s(A4) | s(A5) | Ordering | |
---|---|---|---|---|---|---|
K = 1 | 0.6724 | 0.6210 | 0.6748 | 0.6514 | 0.6176 | A3>A1>A4>A2>A5 |
K = 2 | 0.6809 | 0.6421 | 0.7042 | 0.6582 | 0.6354 | A3>A1>A4>A2>A5 |
K = 3 | 0.6863 | 0.6580 | 0.7195 | 0.6622 | 0.6465 | A3>A1>A4>A2>A5 |
K = 4 | 0.6909 | 0.6717 | 0.7366 | 0.6655 | 0.6567 | A3>A1>A2>A4>A5 |
© 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Share and Cite
Wang, J.; Wei, G.; Gao, H. Approaches to Multiple Attribute Decision Making with Interval-Valued 2-Tuple Linguistic Pythagorean Fuzzy Information. Mathematics 2018, 6, 201. https://doi.org/10.3390/math6100201
Wang J, Wei G, Gao H. Approaches to Multiple Attribute Decision Making with Interval-Valued 2-Tuple Linguistic Pythagorean Fuzzy Information. Mathematics. 2018; 6(10):201. https://doi.org/10.3390/math6100201
Chicago/Turabian StyleWang, Jie, Guiwu Wei, and Hui Gao. 2018. "Approaches to Multiple Attribute Decision Making with Interval-Valued 2-Tuple Linguistic Pythagorean Fuzzy Information" Mathematics 6, no. 10: 201. https://doi.org/10.3390/math6100201
APA StyleWang, J., Wei, G., & Gao, H. (2018). Approaches to Multiple Attribute Decision Making with Interval-Valued 2-Tuple Linguistic Pythagorean Fuzzy Information. Mathematics, 6(10), 201. https://doi.org/10.3390/math6100201