Abstract
In this paper, a novel multiple-attribute decision-making method based on a set of Archimedean power Maclaurin symmetric mean operators of picture fuzzy numbers is proposed. The Maclaurin symmetric mean operator, power average operator, and operational rules based on Archimedean T-norm and T-conorm are introduced into picture fuzzy environment to construct the aggregation operators. The formal definitions of the aggregation operators are presented. Their general and specific expressions are established. The properties and special cases of the aggregation operators are, respectively, explored and discussed. Using the presented aggregation operators, a method for solving the multiple-attribute decision-making problems based on picture fuzzy numbers is designed. The method is illustrated through example and experiments and validated by comparisons. The results of the comparisons show that the proposed method is feasible and effective that can provide the generality and flexibility in aggregation of values of attributes and consideration of interactions among attributes and the capability to lower the negative effect of biased attribute values on the result of aggregation.
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Data availability
The Java implementation code of all quantitative comparison methods and related data used to support the findings of this study have been deposited in the GitHub repository (https://github.com/YuchuChingQin/MADMAOsOfPFNs).
References
Ai Z, Xu Z (2018) Multiple Definite Integrals of Intuitionistic Fuzzy Calculus and Isomorphic Mappings. IEEE Trans Fuzzy Syst 26(2):670–680
Atanassov KT (1986) Intuitionistic fuzzy sets. Fuzzy Sets Syst 20(1):87–96
Bustince H, Barrenechea E, Pagola M, Fernandez J, Xu Z, Bedregal B, Montero J, Hagras H, Herrera F, De Baets B (2016) A historical account of types of fuzzy sets and their relationships. IEEE Trans Fuzzy Syst 24(1):179–194
Castillo O, Cervantes L, Melin P, Pedrycz W (2019) A new approach to control of multivariable systems through a hierarchical aggregation of fuzzy controllers. Granular Comput 4(1):1–13
Chen SM, Adam SI (2017) Adaptive fuzzy interpolation based on general representative values of polygonal fuzzy sets and the shift and modification techniques. Inf Sci 414:147–157
Chen SM, Chang CH (2016) Fuzzy multiattribute decision making based on transformation techniques of intuitionistic fuzzy values and intuitionistic fuzzy geometric averaging operators. Inf Sci 352:133–149
Chen SM, Chen SW (2014) Fuzzy forecasting based on two-factors second-order fuzzy-trend logical relationship groups and the probabilities of trends of fuzzy logical relationships. IEEE Trans Cybern 45(3):391–403
Chen SM, Niou SJ (2011) Fuzzy multiple attributes group decision-making based on fuzzy preference relations. Expert Syst Appl 38(4):3865–3872
Chen SM, Ko YK, Chang YC, Pan JS (2009) Weighted fuzzy interpolative reasoning based on weighted increment transformation and weighted ratio transformation techniques. IEEE Trans Fuzzy Syst 17(6):1412–1427
Chen SM, Chu HP, Sheu TW (2012) TAIEX forecasting using fuzzy time series and automatically generated weights of multiple factors. IEEE Trans Syst Man Cybern Part A Syst Hum 42(6):1485–1495
Chen SM, Cheng SH, Lan TC (2016a) Multicriteria decision making based on the TOPSIS method and similarity measures between intuitionistic fuzzy values. Inf Sci 367:279–295
Chen SM, Cheng SH, Chiou CH (2016b) Fuzzy multiattribute group decision making based on intuitionistic fuzzy sets and evidential reasoning methodology. Inf Fusion 27:215–227
Cuong BC (2014) Picture fuzzy sets. J Comput Sci Cybern 30(4):409–420
Dutta P (2019) Multi-criteria decision making under uncertainty via the operations of generalized intuitionistic fuzzy numbers. Granular Comput. https://doi.org/10.1007/s41066-019-00189-z
Dutta P, Saikia B (2019) Arithmetic operations on normal semi elliptic intuitionistic fuzzy numbers and their application in decision-making. Granular Comput. https://doi.org/10.1007/s41066-019-00175-5
Garg H (2017a) Novel intuitionistic fuzzy decision making method based on an improved operation laws and its application. Eng Appl Artif Intell 60:164–174
Garg H (2017b) Some picture fuzzy aggregation operators and their applications to multicriteria decision-making. Arab J Sci Eng 42(12):5275–5290
Garg H, Kumar K (2018) An advanced study on the similarity measures of intuitionistic fuzzy sets based on the set pair analysis theory and their application in decision making. Soft Comput 22(15):4959–4970
Garg H, Kumar K (2019) Improved possibility degree method for ranking intuitionistic fuzzy numbers and their application in multiattribute decision-making. Granul Comput 4(2):237–247
Hinde CJ, Patching RS, McCoy SA (2007) Inconsistent Intuitionistic Fuzzy Sets and Mass Assignment. In: Atanassov KT, Baczyński M, Drewniak J, Kacprzyk J, Krawczak M, Szmidt E, Wygralak M, Zadrożny S (Eds.) Developments in Fuzzy Sets, Intuitionistic Fuzzy Sets, Generalized Nets and Related Topics, vol. I: Foundations, Warsaw: SRI PAS/IBS PAN, pp 133 − 153
Jamkhaneh EB, Garg H (2018) Some new operations over the generalized intuitionistic fuzzy sets and their application to decision-making process. Granul Comput 3(2):111–122
Jana C, Senapati T, Pal M, Yager RR (2019) Picture fuzzy Dombi aggregation operators: Application to MADM process. Applied Soft Computing 74:99–109
Ju Y, Ju D, Gonzalez EDS, Giannakis M, Wang A (2019) Study of site selection of electric vehicle charging station based on extended GRP method under picture fuzzy environment. Comput Ind Eng 135:1271–1285
Khalil AM, Li SG, Garg H, Li H, Ma S (2019) New operations on interval-valued picture fuzzy set, interval-valued picture fuzzy soft set and their applications. IEEE Access 7:51236–51253
Klement EP, Mesiar R, Pap E (2000) Triangular Norms. Springer, Dordrecht
Kumar K, Garg H (2018) Connection number of set pair analysis based TOPSIS method on intuitionistic fuzzy sets and their application to decision making. Appl Intell 48(8):2112–2119
Lei Q, Xu Z (2016) Chain and substitution rules of intuitionistic fuzzy calculus. IEEE Trans Fuzzy Syst 24(3):519–529
Lei Q, Xu Z (2017) A unification of intuitionistic fuzzy calculus theories based on subtraction derivatives and division derivatives. IEEE Trans Fuzzy Syst 25(5):1023–1040
Liang W, Zhao G, Luo S (2018) An integrated EDAS-ELECTRE method with picture fuzzy information for cleaner production evaluation in gold mines. IEEE Access 6:65747–65759
Liao H, Xu Z (2014) Priorities of intuitionistic fuzzy preference relation based on multiplicative consistency. IEEE Trans Fuzzy Syst 22(6):1669–1681
Liao H, Xu Z, Zeng XJ, Merigó JM (2015) Framework of group decision making with intuitionistic fuzzy preference information. IEEE Trans Fuzzy Syst 23(4):1211–1227
Liu P, Chen SM (2017) Group decision making based on Heronian aggregation operators of intuitionistic fuzzy numbers. IEEE Trans Cybern 47(9):2514–2530
Liu P, Chen SM, Wang P (2018) Multiple-attribute group decision-making based on q-rung orthopair fuzzy power maclaurin symmetric mean operators. IEEE Trans Syst Man Cybern Syst. https://doi.org/10.1109/tsmc.2018.2852948
Liu P, Chen SM, Wang Y (2020) Multiattribute group decision making based on intuitionistic fuzzy partitioned Maclaurin symmetric mean operators. Inf Sci 512:830–854
Liu P, Tang G (2018) Some intuitionistic fuzzy prioritized interactive einstein choquet operators and their application in decision making. IEEE Access 6:72357–72371
Liu P, Liu X (2017) Multiattribute group decision making methods based on linguistic intuitionistic fuzzy power Bonferroni mean operators. Complexity 2017:3571459
Liu P, Liu J (2018) Some q-rung orthopai fuzzy Bonferroni mean operators and their application to multi-attribute group decision making. Int J Intell Syst 33(2):315–347
Liu P, Wang P (2018) Some q-rung orthopair fuzzy aggregation operators and their applications to multiple-attribute decision making. Int J Intell Syst 33(2):259–280
Liu P, Wang P (2019) Multiple-attribute decision making based on Archimedean Bonferroni operators of q-rung orthopair fuzzy numbers. IEEE Trans Fuzzy Syst 27(5):834–848
Maclaurin C (1729) A second letter to Martin Folkes, Esq.; Concerning the roots of equations, with the demonstration of other rules in algebra. Philos Trans R Soc Lond 36(1):59–96
Mahmood T, Ullah K, Khan Q, Jan N (2019) An approach toward decision-making and medical diagnosis problems using the concept of spherical fuzzy sets. Neural Comput Appl 31(11):7041–7053
Qin Y, Qi Q, Scott PJ, Jiang X (2019a) Multi-criteria group decision making based on Archimedean power partitioned Muirhead mean operators of q-rung orthopair fuzzy numbers. PLoS One 14(9):e0221759
Qin Y, Cui X, Huang M, Zhong Y, Tang Z, Shi P (2019b) Archimedean muirhead aggregation operators of q-rung orthopair fuzzy numbers for multicriteria group decision making. Complexity 2019:3103741
Qin Y, Cui X, Huang M, Zhong Y, Tang Z, Shi P (2020a) Linguistic interval-valued intuitionistic fuzzy archimedean power muirhead mean operators for multiattribute group decision-making. Complexity 2020:2373762
Qin Y, Qi Q, Shi P, Scott PJ, Jiang X (2020b) Linguistic interval-valued intuitionistic fuzzy Archimedean prioritised aggregation operators for multi-criteria decision making. J Intell Fuzzy Syst 38(4):4643–4666
Qin Y, Qi Q, Scott PJ, Jiang X (2020c) Multiple criteria decision making based on weighted Archimedean power partitioned Bonferroni aggregation operators of generalised orthopair membership grades. Soft Comput 24(16):12329–12355
Rani P, Jain D, Hooda DS (2019) Extension of intuitionistic fuzzy TODIM technique for multi-criteria decision making method based on shapley weighted divergence measure. Granul Comput 4(3):407–420
Seikh MR, Mandal U (2019) Intuitionistic fuzzy Dombi aggregation operators and their application to multiple attribute decision-making. Granul Comput. https://doi.org/10.1007/s41066-019-00209-y
Singh P (2015) Correlation coefficients for picture fuzzy sets. J Intell Fuzzy Syst 28(2):591–604
Son LH (2016) Generalized picture distance measure and applications to picture fuzzy clustering. Appl Soft Comput 46:284–295
Song Y, Fu Q, Wang YF, Wang X (2019) Divergence-based cross entropy and uncertainty measures of Atanassov’s intuitionistic fuzzy sets with their application in decision making. Appl Soft Comput 84:105703
Tan A, Shi S, Wu WZ, Li J, Pedrycz W (2020) Granularity and entropy of intuitionistic fuzzy information and their applications. IEEE Trans Cybern. https://doi.org/10.1109/tcyb.2020.2973379
Teng F, Liu Z, Liu P (2018) Some power Maclaurin symmetric mean aggregation operators based on Pythagorean fuzzy linguistic numbers and their application to group decision making. Int J Intell Syst 33(9):1949–1985
Thong PH (2016) A novel automatic picture fuzzy clustering method based on particle swarm optimization and picture composite cardinality. Knowl-Based Syst 109:48–60
Wang JQ, Zhang HY (2013) Multicriteria decision-making approach based on Atanassov’s intuitionistic fuzzy sets with incomplete certain information on weights. IEEE Trans Fuzzy Syst 21(3):510–515
Wang L, Zhang H, Wang J, Li L (2018a) Picture fuzzy normalized projection-based VIKOR method for the risk evaluation of construction project. Appl Soft Comput 64:216–226
Wang L, Peng J, Wang J (2018b) A multi-criteria decision-making framework for risk ranking of energy performance contracting project under picture fuzzy environment. J Clean Prod 191:105–118
Wei G (2017) Picture fuzzy aggregation operators and their application to multiple attribute decision making. J Intell Fuzzy Syst 33(2):713–724
Wei G (2018) Picture fuzzy Hamacher aggregation operators and their application to multiple attribute decision making. Fundamenta Informaticae 157(3):271–320
Wei G, Lu M, Gao H (2018a) Picture fuzzy Heronian mean aggregation operators in multiple attribute decision making. Int J Knowl-Based Intell Eng Syst 22(3):167–175
Wei G, Alsaadi FE, Hayat T, Alsaedi A (2018b) Picture 2-tuple linguistic aggregation operators in multiple attribute decision making. Soft Comput 22(3):989–1002
Xia M, Xu Z, Zhu B (2012) Some issues on intuitionistic fuzzy aggregation operators based on Archimedean t-conorm and t-norm. Knowl-Based Syst 31:78–88
Xu Y, Shang X, Wang J, Zhang R, Li W, Xing Y (2019) A method to multi-attribute decision making with picture fuzzy information based on Muirhead mean. J Intell Fuzzy Syst 36(4):3833–3849
Xu Z, Yager RR (2011) Intuitionistic fuzzy Bonferroni means. IEEE Trans Syst Man Cybern-Part B Cybern 41(2):568–578
Yager RR (2001) The power average operator. IEEE Trans Syst Man Cybern-Part A Syst Hum 31(6):724–731
Zadeh LA (1965) Fuzzy sets. Inf Control 8(3):338–353
Zeng S, Chen SM, Kuo LW (2019) Multiattribute decision making based on novel score function of intuitionistic fuzzy values and modified VIKOR method. Inf Sci 488:76–92
Zhang FW, Huang WW, Sun J, Liu ZD, Zhu YH, Li KT, Xu SH, Li Q (2019) Generalized fuzzy additive operators on intuitionistic fuzzy sets and interval-valued intuitionistic fuzzy sets and their application. IEEE Access 7:45734–45743
Zhang H, Zhang R, Huang H, Wang J (2018) Some picture fuzzy Dombi Heronian mean operators with their application to multi-attribute decision-making. Symmetry 10(11):593
Zhang Z, Pedrycz W (2017a) Models of mathematical programming for intuitionistic multiplicative preference relations. IEEE Trans Fuzzy Syst 25(4):945–957
Zhang Z, Pedrycz W (2017b) Intuitionistic multiplicative group analytic hierarchy process and its use in multicriteria group decision-making. IEEE Trans Cybern 48(7):1950–1962
Zhang Z, Pedrycz W (2018) Goal programming approaches to managing consistency and consensus for intuitionistic multiplicative preference relations in group decision making. IEEE Trans Fuzzy Syst 26(6):3261–3275
Zhang Z, Chen SM, Wang C (2020) Group decision making with incomplete intuitionistic multiplicative preference relations. Inf Sci 516:560–571
Zhong Y, Guo X, Gao H, Qin Y, Huang M, Luo X (2019a) A new multi-criteria decision-making method based on Pythagorean hesitant fuzzy Archimedean Muirhead mean operators. J Intell Fuzzy Syst 37(4):5551–5571
Zhong Y, Gao H, Guo X, Qin Y, Huang M, Luo X (2019b) Dombi power partitioned Heronian mean operators of q-rung orthopair fuzzy numbers for multiple attribute group decision making. PLoS One 14(10):e0222007
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This study was funded by the National Natural Science Foundation of PR China (No. 51765012 and No. 61562016) and the Key Laboratory Project of Guangxi (No. GIIP1805).
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Yuchu Qin declares that he has no conflict of interest. Xiaolan Cui declares that she has no conflict of interest. Meifa Huang declares that he has no conflict of interest. Yanru Zhong declares that she has no conflict of interest. Zhemin Tang declares that he has no conflict of interest. Peizhi Shi declares that he has no conflict of interest.
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Appendixes
Appendixes
1.1 A. Proof of Theorem 1
Proof
-
1
The following equations are successively derived from the operational rules in Eqs. (1), (2), (3), and (4)
$$\begin{aligned}(n\omega_{{i_{h} }} )\alpha_{{i_{h} }} & = \left\langle {\psi^{ - 1} \left( {(n\omega_{{i_{h} }} )\psi (\mu_{{i_{h} }} )} \right), \, \varphi^{ - 1} \left( {(n\omega_{{i_{h} }} )\varphi (\eta_{{i_{h} }} )} \right), \, \varphi^{ - 1} \left( {(n\omega_{{i_{h} }} )\varphi (\nu_{{i_{h} }} )} \right)} \right\rangle , \\ \mathop \otimes \limits_{h = 1}^{k} \left( {(n\omega_{{i_{h} }} )\alpha_{{i_{h} }} } \right) & = \left\langle {\varphi^{ - 1} \left( {\sum\limits_{h = 1}^{k} {\varphi \left( {\psi^{ - 1} \left( {(n\omega_{{i_{h} }} )\psi (\mu_{{i_{h} }} )} \right)} \right)} } \right), \, \psi^{ - 1} \left( {\sum\limits_{h = 1}^{k} {\psi \left( {\varphi^{ - 1} \left( {(n\omega_{{i_{h} }} )\varphi (\eta_{{i_{h} }} )} \right)} \right)} } \right), \, \psi^{ - 1} \left( {\sum\limits_{h = 1}^{k} {\psi \left( {\varphi^{ - 1} \left( {(n\omega_{{i_{h} }} )\varphi (\nu_{{i_{h} }} )} \right)} \right)} } \right)} \right\rangle , \\ \mathop \oplus \limits_{{1 \le i_{1} < \ldots < i_{k} \le n}} \mathop \otimes \limits_{h = 1}^{k} \left( {(n\omega_{{i_{h} }} )\alpha_{{i_{h} }} } \right) & = \left\langle {\psi^{ - 1} \left( {\sum\limits_{{1 \le i_{1} < \ldots < i_{k} \le n}} {\psi \left( {\varphi^{ - 1} \left( {\sum\limits_{h = 1}^{k} {\varphi \left( {\psi^{ - 1} \left( {(n\omega_{{i_{h} }} )\psi (\mu_{{i_{h} }} )} \right)} \right)} } \right)} \right)} } \right),} \right. \\ & \quad \varphi^{ - 1} \left( {\sum\limits_{{1 \le i_{1} < \ldots < i_{k} \le n}} {\varphi \left( {\psi^{ - 1} \left( {\sum\limits_{h = 1}^{k} {\psi \left( {\varphi^{ - 1} \left( {(n\omega_{{i_{h} }} )\varphi (\eta_{{i_{h} }} )} \right)} \right)} } \right)} \right)} } \right), \\ & \left. { \quad \varphi^{ - 1} \left( {\sum\limits_{{1 \le i_{1} < \ldots < i_{k} \le n}} {\varphi \left( {\psi^{ - 1} \left( {\sum\limits_{h = 1}^{k} {\psi \left( {\varphi^{ - 1} \left( {(n\omega_{{i_{h} }} )\varphi (\nu_{{i_{h} }} )} \right)} \right)} } \right)} \right)} } \right)} \right\rangle , \\ \frac{1}{{C_{n}^{k} }}\mathop \oplus \limits_{{1 \le i_{1} < \ldots < i_{k} \le n}} \mathop \otimes \limits_{h = 1}^{k} \left( {(n\omega_{{i_{h} }} )\alpha_{{i_{h} }} } \right) & = \left\langle {\psi^{ - 1} \left( {\frac{1}{{C_{n}^{k} }}\sum\limits_{{1 \le i_{1} < \ldots < i_{k} \le n}} {\psi \left( {\varphi^{ - 1} \left( {\sum\limits_{h = 1}^{k} {\varphi \left( {\psi^{ - 1} \left( {(n\omega_{{i_{h} }} )\psi (\mu_{{i_{h} }} )} \right)} \right)} } \right)} \right)} } \right)} \right., \\ & \quad \varphi^{ - 1} \left( {\frac{1}{{C_{n}^{k} }}\sum\limits_{{1 \le i_{1} < \ldots < i_{k} \le n}} {\varphi \left( {\psi^{ - 1} \left( {\sum\limits_{h = 1}^{k} {\psi \left( {\varphi^{ - 1} \left( {(n\omega_{{i_{h} }} )\varphi (\eta_{{i_{h} }} )} \right)} \right)} } \right)} \right)} } \right), \\ & \left. { \quad \varphi^{ - 1} \left( {\frac{1}{{C_{n}^{k} }}\sum\limits_{{1 \le i_{1} < \ldots < i_{k} \le n}} {\varphi \left( {\psi^{ - 1} \left( {\sum\limits_{h = 1}^{k} {\psi \left( {\varphi^{ - 1} \left( {(n\omega_{{i_{h} }} )\varphi (\nu_{{i_{h} }} )} \right)} \right)} } \right)} \right)} } \right)} \right\rangle , \\ \left( {\frac{1}{{C_{n}^{k} }}\mathop \oplus \limits_{{1 \le i_{1} < \ldots < i_{k} \le n}} \mathop \otimes \limits_{h = 1}^{k} \left( {(n\omega_{{i_{h} }} )\alpha_{{i_{h} }} } \right)} \right)^{1/k} & = \left\langle {\varphi^{ - 1} \left( {\frac{1}{k}\varphi \left( {\psi^{ - 1} \left( {\frac{1}{{C_{n}^{k} }}\sum\limits_{{1 \le i_{1} < \ldots < i_{k} \le n}} {\psi \left( {\varphi^{ - 1} \left( {\sum\limits_{h = 1}^{k} {\varphi \left( {\psi^{ - 1} \left( {(n\omega_{{i_{h} }} )\psi (\mu_{{i_{h} }} )} \right)} \right)} } \right)} \right)} } \right)} \right)} \right),} \right. \\ & \quad \psi^{ - 1} \left( {\frac{1}{k}\psi \left( {\varphi^{ - 1} \left( {\frac{1}{{C_{n}^{k} }}\sum\limits_{{1 \le i_{1} < \ldots < i_{k} \le n}} {\varphi \left( {\psi^{ - 1} \left( {\sum\limits_{h = 1}^{k} {\psi \left( {\varphi^{ - 1} \left( {(n\omega_{{i_{h} }} )\varphi (\eta_{{i_{h} }} )} \right)} \right)} } \right)} \right)} } \right)} \right)} \right), \\ & \quad \left. {\psi^{ - 1} \left( {\frac{1}{k}\psi \left( {\varphi^{ - 1} \left( {\frac{1}{{C_{n}^{k} }}\sum\limits_{{1 \le i_{1} < \ldots < i_{k} \le n}} {\varphi \left( {\psi^{ - 1} \left( {\sum\limits_{h = 1}^{k} {\psi \left( {\varphi^{ - 1} \left( {(n\omega_{{i_{h} }} )\varphi (\nu_{{i_{h} }} )} \right)} \right)} } \right)} \right)} } \right)} \right)} \right)} \right\rangle . \\ \end{aligned}$$ -
2
The proof of “PFAPMSM(k)(α1, α2, ..., αn) is a PFN” is equivalent to the proof of “0 ≤ μ ≤ 1, 0 ≤ η ≤ 1, 0 ≤ ν ≤ 1, and 0 ≤ μ + η + ν ≤ 1”. The following is the proof of “0 ≤ μ ≤ 1”:
-
(i)
According to the conditions 0 ≤ μih ≤ 1, φ(t) and φ−1(t) are monotonically decreasing, and ψ(t) and ψ−1(t) are monotonically increasing, the following inequalities are successively derived
$$\begin{aligned} (n\omega_{{i_{h} }} )\psi (0) & \le (n\omega_{{i_{h} }} )\psi (\mu_{{i_{h} }} ) \le (n\omega_{{i_{h} }} )\psi (1), \\ \psi^{ - 1} \left( {(n\omega_{{i_{h} }} )\psi (0)} \right) & \le \psi^{ - 1} \left( {(n\omega_{{i_{h} }} )\psi (\mu_{{i_{h} }} )} \right) \le \psi^{ - 1} \left( {(n\omega_{{i_{h} }} )\psi (1)} \right), \\ \sum\limits_{h = 1}^{k} {\varphi \left( {\psi^{ - 1} \left( {(n\omega_{{i_{h} }} )\psi (0)} \right)} \right)} & \ge \sum\limits_{h = 1}^{k} {\varphi \left( {\psi^{ - 1} \left( {(n\omega_{{i_{h} }} )\psi (\mu_{{i_{h} }} )} \right)} \right)} \ge \sum\limits_{h = 1}^{k} {\varphi \left( {\psi^{ - 1} \left( {(n\omega_{{i_{h} }} )\psi (1)} \right)} \right)} , \\ \varphi^{ - 1} \left( {\sum\limits_{h = 1}^{k} {\varphi \left( {\psi^{ - 1} \left( {(n\omega_{{i_{h} }} )\psi (0)} \right)} \right)} } \right) & \le \varphi^{ - 1} \left( {\sum\limits_{h = 1}^{k} {\varphi \left( {\psi^{ - 1} \left( {(n\omega_{{i_{h} }} )\psi (\mu_{{i_{h} }} )} \right)} \right)} } \right) \le \varphi^{ - 1} \left( {\sum\limits_{h = 1}^{k} {\varphi \left( {\psi^{ - 1} \left( {(n\omega_{{i_{h} }} )\psi (1)} \right)} \right)} } \right), \\ \frac{1}{{C_{n}^{k} }}\sum\limits_{{1 \le i_{1} < \ldots < i_{k} \le n}} {\psi \left( {\varphi^{ - 1} \left( {\sum\limits_{h = 1}^{k} {\varphi \left( {\psi^{ - 1} \left( {(n\omega_{{i_{h} }} )\psi (0)} \right)} \right)} } \right)} \right)} & \le \frac{1}{{C_{n}^{k} }}\sum\limits_{{1 \le i_{1} < \ldots < i_{k} \le n}} {\psi \left( {\varphi^{ - 1} \left( {\sum\limits_{h = 1}^{k} {\varphi \left( {\psi^{ - 1} \left( {(n\omega_{{i_{h} }} )\psi (\mu_{{i_{h} }} )} \right)} \right)} } \right)} \right)} \\ & \quad \le\,\frac{1}{{C_{n}^{k} }}\sum\limits_{{1 \le i_{1} < \ldots < i_{k} \le n}} {\psi \left( {\varphi^{ - 1} \left( {\sum\limits_{h = 1}^{k} {\varphi \left( {\psi^{ - 1} \left( {(n\omega_{{i_{h} }} )\psi (1)} \right)} \right)} } \right)} \right)} . \\ \end{aligned}$$Since
$$\sum\limits_{{1 \le i_{1} < \ldots < i_{k} \le n}} {\sum\limits_{h = 1}^{k} {(n\omega_{{i_{h} }} ) = n\sum\limits_{{1 \le i_{1} < \ldots < i_{k} \le n}} {\left( {\omega_{{i_{1} }} + \omega_{{i_{2} }} + \ldots + \omega_{{i_{k} }} } \right)} } } = n\frac{1}{n} = 1.$$The following inequalities are successively obtained
$$\begin{aligned} \psi \left( {\varphi^{ - 1} \left( {k\varphi (0)} \right)} \right) \le \frac{1}{{C_{n}^{k} }}\sum\limits_{{1 \le i_{1} < \ldots < i_{k} \le n}} {\psi \left( {\varphi^{ - 1} \left( {\sum\limits_{h = 1}^{k} {\varphi \left( {\psi^{ - 1} \left( {(n\omega_{{i_{h} }} )\psi (\mu_{{i_{h} }} )} \right)} \right)} } \right)} \right)} \le \psi \left( {\varphi^{ - 1} \left( {k\varphi (1)} \right)} \right), \hfill \\ \varphi^{ - 1} \left( {k\varphi (0)} \right) \le \psi^{ - 1} \left( {\frac{1}{{C_{n}^{k} }}\sum\limits_{{1 \le i_{1} < \ldots < i_{k} \le n}} {\psi \left( {\varphi^{ - 1} \left( {\sum\limits_{h = 1}^{k} {\varphi \left( {\psi^{ - 1} \left( {(n\omega_{{i_{h} }} )\psi (\mu_{{i_{h} }} )} \right)} \right)} } \right)} \right)} } \right) \le \varphi^{ - 1} \left( {k\varphi (1)} \right), \hfill \\ \varphi (0) \ge \frac{1}{k}\varphi \left( {\psi^{ - 1} \left( {\frac{1}{{C_{n}^{k} }}\sum\limits_{{1 \le i_{1} < \ldots < i_{k} \le n}} {\psi \left( {\varphi^{ - 1} \left( {\sum\limits_{h = 1}^{k} {\varphi \left( {\psi^{ - 1} \left( {(n\omega_{{i_{h} }} )\psi (\mu_{{i_{h} }} )} \right)} \right)} } \right)} \right)} } \right)} \right) \ge \varphi (1), \hfill \\ 0 \le \varphi^{ - 1} \left( {\frac{1}{k}\varphi \left( {\psi^{ - 1} \left( {\frac{1}{{C_{n}^{k} }}\sum\limits_{{1 \le i_{1} < \ldots < i_{k} \le n}} {\psi \left( {\varphi^{ - 1} \left( {\sum\limits_{h = 1}^{k} {\varphi \left( {\psi^{ - 1} \left( {(n\omega_{{i_{h} }} )\psi (\mu_{{i_{h} }} )} \right)} \right)} } \right)} \right)} } \right)} \right)} \right) \le 1. \hfill \\ \end{aligned}$$That is 0 ≤ μ ≤ 1. “0 ≤ η ≤ 1” and “0 ≤ ν ≤ 1” can be proved in a similar way.
-
(ii)
The following is the proof of “0 ≤ μ + η + ν ≤ 1”:
Since 0 ≤ μ ≤ 1, 0 ≤ η ≤ 1, and 0 ≤ ν ≤ 1, it is obtained that 0 ≤ μ + η + ν ≤ 3. According to the definition of a PFN in Def. 1, it is further obtained that μih + ηih + νih ≤ 1 and μih ≤ 1 – (ηih + νih).
According to the conditions φ(t) and φ−1(t) are monotonically decreasing, ψ(t) and ψ−1(t) are monotonically increasing, ψ(1 − t) = φ(t), ψ−1(t) = 1 − φ−1(t), φ(1 − t) = ψ(t), and φ−1(t) = 1 − ψ−1(t), the following inequalities are successively derived
$$\begin{aligned} (n\omega_{{i_{h} }} )\psi (\mu_{{i_{h} }} ) \le (n\omega_{{i_{h} }} )\psi \left( {1 - (\eta_{{i_{h} }} + \nu_{{i_{h} }} )} \right), \hfill \\ (n\omega_{{i_{h} }} )\psi (\mu_{{i_{h} }} ) \le (n\omega_{{i_{h} }} )\varphi (\eta_{{i_{h} }} + \nu_{{i_{h} }} ), \hfill \\ \varphi (\eta_{{i_{h} }} + \nu_{{i_{h} }} ) \le 2\varphi (\eta_{{i_{h} }} + \nu_{{i_{h} }} ) \le \varphi (\eta_{{i_{h} }} ) + \varphi (\nu_{{i_{h} }} ), \hfill \\ (n\omega_{{i_{h} }} )\psi (\mu_{{i_{h} }} ) \le (n\omega_{{i_{h} }} )\varphi (\eta_{{i_{h} }} + \nu_{{i_{h} }} ) \le (n\omega_{{i_{h} }} )\left( {\varphi (\eta_{{i_{h} }} ) + \varphi (\nu_{{i_{h} }} )} \right), \hfill \\ \psi^{ - 1} \left( {(n\omega_{{i_{h} }} )\psi (\mu_{{i_{h} }} )} \right) \le \psi^{ - 1} \left( {(n\omega_{{i_{h} }} )\left( {\varphi (\eta_{{i_{h} }} ) + \varphi (\nu_{{i_{h} }} )} \right)} \right), \hfill \\ \psi^{ - 1} \left( {(n\omega_{{i_{h} }} )\psi (\mu_{{i_{h} }} )} \right) \le 1 - \varphi^{ - 1} \left( {(n\omega_{{i_{h} }} )\left( {\varphi (\eta_{{i_{h} }} ) + \varphi (\nu_{{i_{h} }} )} \right)} \right), \hfill \\ \sum\limits_{h = 1}^{k} {\varphi \left( {\psi^{ - 1} \left( {(n\omega_{{i_{h} }} )\psi (\mu_{{i_{h} }} )} \right)} \right)} \ge \sum\limits_{h = 1}^{k} {\varphi \left( {1 - \varphi^{ - 1} \left( {(n\omega_{{i_{h} }} )\left( {\varphi (\eta_{{i_{h} }} ) + \varphi (\nu_{{i_{h} }} )} \right)} \right)} \right)} , \hfill \\ \sum\limits_{h = 1}^{k} {\varphi \left( {\psi^{ - 1} \left( {(n\omega_{{i_{h} }} )\psi (\mu_{{i_{h} }} )} \right)} \right)} \ge \sum\limits_{h = 1}^{k} {\psi \left( {\varphi^{ - 1} \left( {(n\omega_{{i_{h} }} )\left( {\varphi (\eta_{{i_{h} }} ) + \varphi (\nu_{{i_{h} }} )} \right)} \right)} \right)} , \hfill \\ \varphi^{ - 1} \left( {\sum\limits_{h = 1}^{k} {\varphi \left( {\psi^{ - 1} \left( {(n\omega_{{i_{h} }} )\psi (\mu_{{i_{h} }} )} \right)} \right)} } \right) \le \varphi^{ - 1} \left( {\sum\limits_{h = 1}^{k} {\psi \left( {\varphi^{ - 1} \left( {(n\omega_{{i_{h} }} )\left( {\varphi (\eta_{{i_{h} }} ) + \varphi (\nu_{{i_{h} }} )} \right)} \right)} \right)} } \right), \hfill \\ \varphi^{ - 1} \left( {\sum\limits_{h = 1}^{k} {\varphi \left( {\psi^{ - 1} \left( {(n\omega_{{i_{h} }} )\psi (\mu_{{i_{h} }} )} \right)} \right)} } \right) \le 1 - \psi^{ - 1} \left( {\sum\limits_{h = 1}^{k} {\psi \left( {\varphi^{ - 1} \left( {(n\omega_{{i_{h} }} )\left( {\varphi (\eta_{{i_{h} }} ) + \varphi (\nu_{{i_{h} }} )} \right)} \right)} \right)} } \right), \hfill \\ \frac{1}{{C_{n}^{k} }}\sum\limits_{{1 \le i_{1} < \ldots < i_{k} \le n}} {\psi \left( {\varphi^{ - 1} \left( {\sum\limits_{h = 1}^{k} {\varphi \left( {\psi^{ - 1} \left( {(n\omega_{{i_{h} }} )\psi (\mu_{{i_{h} }} )} \right)} \right)} } \right)} \right)} \le \frac{1}{{C_{n}^{k} }}\sum\limits_{{1 \le i_{1} < \ldots < i_{k} \le n}} {\psi \left( {1 - \psi^{ - 1} \left( {\sum\limits_{h = 1}^{k} {\psi \left( {\varphi^{ - 1} \left( {(n\omega_{{i_{h} }} )\left( {\varphi (\eta_{{i_{h} }} ) + \varphi (\nu_{{i_{h} }} )} \right)} \right)} \right)} } \right)} \right)} , \hfill \\ \frac{1}{{C_{n}^{k} }}\sum\limits_{{1 \le i_{1} < \ldots < i_{k} \le n}} {\psi \left( {\varphi^{ - 1} \left( {\sum\limits_{h = 1}^{k} {\varphi \left( {\psi^{ - 1} \left( {(n\omega_{{i_{h} }} )\psi (\mu_{{i_{h} }} )} \right)} \right)} } \right)} \right)} \le \frac{1}{{C_{n}^{k} }}\sum\limits_{{1 \le i_{1} < \ldots < i_{k} \le n}} {\varphi \left( {\psi^{ - 1} \left( {\sum\limits_{h = 1}^{k} {\psi \left( {\varphi^{ - 1} \left( {(n\omega_{{i_{h} }} )\left( {\varphi (\eta_{{i_{h} }} ) + \varphi (\nu_{{i_{h} }} )} \right)} \right)} \right)} } \right)} \right)} , \hfill \\ \psi^{ - 1} \left( {\frac{1}{{C_{n}^{k} }}\sum\limits_{{1 \le i_{1} < \ldots < i_{k} \le n}} {\psi \left( {\varphi^{ - 1} \left( {\sum\limits_{h = 1}^{k} {\varphi \left( {\psi^{ - 1} \left( {(n\omega_{{i_{h} }} )\psi (\mu_{{i_{h} }} )} \right)} \right)} } \right)} \right)} } \right) \le \psi^{ - 1} \left( {\frac{1}{{C_{n}^{k} }}\sum\limits_{{1 \le i_{1} < \ldots < i_{k} \le n}} {\varphi \left( {\psi^{ - 1} \left( {\sum\limits_{h = 1}^{k} {\psi \left( {\varphi^{ - 1} \left( {(n\omega_{{i_{h} }} )\left( {\varphi (\eta_{{i_{h} }} ) + \varphi (\nu_{{i_{h} }} )} \right)} \right)} \right)} } \right)} \right)} } \right), \hfill \\ \psi^{ - 1} \left( {\frac{1}{{C_{n}^{k} }}\sum\limits_{{1 \le i_{1} < \ldots < i_{k} \le n}} {\psi \left( {\varphi^{ - 1} \left( {\sum\limits_{h = 1}^{k} {\varphi \left( {\psi^{ - 1} \left( {(n\omega_{{i_{h} }} )\psi (\mu_{{i_{h} }} )} \right)} \right)} } \right)} \right)} } \right) \hfill \\ \le 1 - \varphi^{ - 1} \left( {\frac{1}{{C_{n}^{k} }}\sum\limits_{{1 \le i_{1} < \ldots < i_{k} \le n}} {\varphi \left( {\psi^{ - 1} \left( {\sum\limits_{h = 1}^{k} {\psi \left( {\varphi^{ - 1} \left( {(n\omega_{{i_{h} }} )\left( {\varphi (\eta_{{i_{h} }} ) + \varphi (\nu_{{i_{h} }} )} \right)} \right)} \right)} } \right)} \right)} } \right), \hfill \\ \frac{1}{k}\varphi \left( {\psi^{ - 1} \left( {\frac{1}{{C_{n}^{k} }}\sum\limits_{{1 \le i_{1} < \ldots < i_{k} \le n}} {\psi \left( {\varphi^{ - 1} \left( {\sum\limits_{h = 1}^{k} {\varphi \left( {\psi^{ - 1} \left( {(n\omega_{{i_{h} }} )\psi (\mu_{{i_{h} }} )} \right)} \right)} } \right)} \right)} } \right)} \right) \hfill \\ \ge \frac{1}{k}\varphi \left( {1 - \varphi^{ - 1} \left( {\frac{1}{{C_{n}^{k} }}\sum\limits_{{1 \le i_{1} < \ldots < i_{k} \le n}} {\varphi \left( {\psi^{ - 1} \left( {\sum\limits_{h = 1}^{k} {\psi \left( {\varphi^{ - 1} \left( {(n\omega_{{i_{h} }} )\left( {\varphi (\eta_{{i_{h} }} ) + \varphi (\nu_{{i_{h} }} )} \right)} \right)} \right)} } \right)} \right)} } \right)} \right), \hfill \\ \frac{1}{k}\varphi \left( {\psi^{ - 1} \left( {\frac{1}{{C_{n}^{k} }}\sum\limits_{{1 \le i_{1} < \ldots < i_{k} \le n}} {\psi \left( {\varphi^{ - 1} \left( {\sum\limits_{h = 1}^{k} {\varphi \left( {\psi^{ - 1} \left( {(n\omega_{{i_{h} }} )\psi (\mu_{{i_{h} }} )} \right)} \right)} } \right)} \right)} } \right)} \right) \hfill \\ \ge \frac{1}{k}\psi \left( {\varphi^{ - 1} \left( {\frac{1}{{C_{n}^{k} }}\sum\limits_{{1 \le i_{1} < \ldots < i_{k} \le n}} {\varphi \left( {\psi^{ - 1} \left( {\sum\limits_{h = 1}^{k} {\psi \left( {\varphi^{ - 1} \left( {(n\omega_{{i_{h} }} )\left( {\varphi (\eta_{{i_{h} }} ) + \varphi (\nu_{{i_{h} }} )} \right)} \right)} \right)} } \right)} \right)} } \right)} \right), \hfill \\ \varphi^{ - 1} \left( {\frac{1}{k}\varphi \left( {\psi^{ - 1} \left( {\frac{1}{{C_{n}^{k} }}\sum\limits_{{1 \le i_{1} < \ldots < i_{k} \le n}} {\psi \left( {\varphi^{ - 1} \left( {\sum\limits_{h = 1}^{k} {\varphi \left( {\psi^{ - 1} \left( {(n\omega_{{i_{h} }} )\psi (\mu_{{i_{h} }} )} \right)} \right)} } \right)} \right)} } \right)} \right)} \right) \hfill \\ \le \varphi^{ - 1} \left( {\frac{1}{k}\psi \left( {\varphi^{ - 1} \left( {\frac{1}{{C_{n}^{k} }}\sum\limits_{{1 \le i_{1} < \ldots < i_{k} \le n}} {\varphi \left( {\psi^{ - 1} \left( {\sum\limits_{h = 1}^{k} {\psi \left( {\varphi^{ - 1} \left( {(n\omega_{{i_{h} }} )\left( {\varphi (\eta_{{i_{h} }} ) + \varphi (\nu_{{i_{h} }} )} \right)} \right)} \right)} } \right)} \right)} } \right)} \right)} \right), \hfill \\ \varphi^{ - 1} \left( {\frac{1}{k}\varphi \left( {\psi^{ - 1} \left( {\frac{1}{{C_{n}^{k} }}\sum\limits_{{1 \le i_{1} < \ldots < i_{k} \le n}} {\psi \left( {\varphi^{ - 1} \left( {\sum\limits_{h = 1}^{k} {\varphi \left( {\psi^{ - 1} \left( {(n\omega_{{i_{h} }} )\psi (\mu_{{i_{h} }} )} \right)} \right)} } \right)} \right)} } \right)} \right)} \right) \hfill \\ \le 1 - \psi^{ - 1} \left( {\frac{1}{k}\psi \left( {\varphi^{ - 1} \left( {\frac{1}{{C_{n}^{k} }}\sum\limits_{{1 \le i_{1} < \ldots < i_{k} \le n}} {\varphi \left( {\psi^{ - 1} \left( {\sum\limits_{h = 1}^{k} {\psi \left( {\varphi^{ - 1} \left( {(n\omega_{{i_{h} }} )\left( {\varphi (\eta_{{i_{h} }} ) + \varphi (\nu_{{i_{h} }} )} \right)} \right)} \right)} } \right)} \right)} } \right)} \right)} \right) \hfill \\ \le 1 - \left( \begin{aligned} \psi^{ - 1} \left( {\frac{1}{k}\psi \left( {\varphi^{ - 1} \left( {\frac{1}{{C_{n}^{k} }}\sum\limits_{{1 \le i_{1} < \ldots < i_{k} \le n}} {\varphi \left( {\psi^{ - 1} \left( {\sum\limits_{h = 1}^{k} {\psi \left( {\varphi^{ - 1} \left( {(n\omega_{{i_{h} }} )\left( {\varphi (\eta_{{i_{h} }} )} \right)} \right)} \right)} } \right)} \right)} } \right)} \right)} \right) + \hfill \\ \psi^{ - 1} \left( {\frac{1}{k}\psi \left( {\varphi^{ - 1} \left( {\frac{1}{{C_{n}^{k} }}\sum\limits_{{1 \le i_{1} < \ldots < i_{k} \le n}} {\varphi \left( {\psi^{ - 1} \left( {\sum\limits_{h = 1}^{k} {\psi \left( {\varphi^{ - 1} \left( {(n\omega_{{i_{h} }} )\left( {\varphi (\nu_{{i_{h} }} )} \right)} \right)} \right)} } \right)} \right)} } \right)} \right)} \right) \hfill \\ \end{aligned} \right). \hfill \\ \end{aligned}$$That is, μ + η + ν ≤ 1.
Since 0 ≤ μ + η + ν ≤ 3 and μ + η + ν ≤ 1 have been proved, 0 ≤ μ + η + ν ≤ 1 can be obtained.
-
(i)
1.2 B. Proof of Theorem 2
Proof
Since αi = α = < μα, ηα, να > for all i = 1, 2, ..., n, d(αi, αj) = 0 for all j = 1, 2, ..., n and j ≠ i. Based on the expression of T(αp) in Def. 9, it is obtained that
Based on this and Theorem 1, it can be obtained that
Since μi = μα, then
The following equations are successively obtained
This is μ = μα. Similarly, it can be proved that η = ηα and ν = να. Thus, PFAPMSM(k)(α1, α2, ..., αn) = < μα, ηα, να > .
1.3 C. Proof of Theorem 3
Proof
It can be derived from the definition of the PFAPMSM operator that
According to Def. 9, it is obtained that PFAPMSM(k)(β1, β2, ..., βn) = PFAPMSM(k)(α1, α2, ..., αn).
1.4 D. Proof of Theorem 4
Proof
Based on Theorem 2, it can be obtained that PFAPMSM(k)(α−, α−, ..., α−) = αα−, PFAPMSM(k)(α+, α+, ..., α+) = α+, and nξih = 1 for both PFAPMSM(k)(α−, α−, ..., α−) and PFAPMSM(k)(α+, α+, ..., α+). According to the conditions μ− ≤ μih ≤ μ+, φ(t) and φ−1(t) are monotonically decreasing, and ψ(t) and ψ−1(t) are monotonically increasing, the following inequalities are successively derived
That is μ− ≤ μ ≤ μ+. Similarly, it can be proved that η− ≥ η ≥ η+ and ν− ≥ ν ≥ ν+.
According to Def. 2, it is obtained that
PFAPMSM(k)(α−, α−, ..., α−) ≤ PFAPMSM(k)(α1, α2, ..., αn) ≤ PFAPMSM(k)(α+, α+, ..., α+)
Therefore, α− ≤ PFAPMSM(k)(α1, α2, ..., αn) ≤ α+.
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Qin, Y., Cui, X., Huang, M. et al. Multiple-attribute decision-making based on picture fuzzy Archimedean power Maclaurin symmetric mean operators. Granul. Comput. 6, 737–761 (2021). https://doi.org/10.1007/s41066-020-00228-0
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DOI: https://doi.org/10.1007/s41066-020-00228-0