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Aggregation of pragmatic operators to support probabilistic linguistic multi-criteria group decision-making problems

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Abstract

In this paper, a multi-attribute group decision-making method based on aggregation operators is presented to solve the decision-making problems which the evaluation values take the form of probabilistic linguistic terms sets (PLTSs). Firstly, some properties of the PLTS are defined, such as the concept and the linguistic terms transformation function, the existing comparison methods and the proposed score function and distance. Secondly, some novel operators are proposed by combining the Heronian mean operator with the centered OWA operator and the power average operator under probabilistic linguistic environment, such as the probabilistic linguistic weighted centered order weighted generalized Heronian mean operator and the probabilistic linguistic weighted power generalized Heronian mean operator. Thirdly, the model of deriving the criteria weight is put forward based on the ideology of deviation maximizing and customized individual attitudinal. Furthermore, based on the proposed aggregation operators and EDAS method, a scientific group decision-making procedure is put forward under probabilistic linguistic environment. Finally, an illustrative example is also given to demonstrate the feasibility and practicality of the proposed method.

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References

  • Abu AO, Al-Smadi M, Momani S et al (2016) Numerical solutions of fuzzy differential equations using reproducing kernel Hilbert space method. Soft Comput 20(8):3283–3302

    MATH  Google Scholar 

  • Ali SH (2012) A novel tool (FP-KC) for handle the three main dimensions reduction and association rule mining. In: 6th International conference on sciences of electronics, technologies of information and telecommunications (SETIT), Sousse. IEEE, pp 951–961

  • Al-Janabi S (2017) Pragmatic miner to risk analysis for intrusion detection (PMRA-ID). pragmatic miner to risk analysis for intrusion detection (PMRA-ID). In: International conference on soft computing in data science. Springer, Singapore, pp 263–277

  • Al-Janabi S, Alkaim AF (2019) A nifty collaborative analysis to predicting a novel tool (DRFLLS) for missing values estimation. Soft Comput. https://doi.org/10.1007/s00500-019-03972-x

    Article  Google Scholar 

  • Al-Janabi S, Alwan E (2017) Soft mathematical system to solve black box problem through development the FARB based on hyperbolic and polynomial functions. In: 10th International conference on developments in eSystems engineering (DeSE). IEEE, pp 37–42

  • Al-Janabi S, Mahdi MA (2019) Evaluation prediction techniques to achievement an optimal biomedical analysis. Int J Grid Util Comput 10(5):512–527

    Google Scholar 

  • Al-Janabi S, Rawat S, Patel A, Al-Shourbaji I (2015) Design and evaluation of a hybrid system for detection and prediction of faults in electrical transformers. Int J Electr Power Energy Syst 67:324–335

    Google Scholar 

  • Al-Janabi S, Yaqoob A, Mohammad M (2019) Pragmatic method based on intelligent big data analytics to prediction air pollution. In: International conference on big data and networks technologies, pp 84–109

  • Alkaim A F, Al-Janabi S (2019) Multi objectives optimization to gas flaring reduction from oil production. In: International conference on big data and networks technologies, pp 117–139

  • Arqub OA, Al-Smadi M, Momani S et al (2016) Application of reproducing kernel algorithm for solving second-order, two-point fuzzy boundary value problems. Soft Comput 21(23):1–16

    MATH  Google Scholar 

  • Bai CZ, Zhang R, Shen S et al (2018) Interval-valued probabilistic linguistic term sets in multi-criteria group decision making. Int J Intell Syst 33(6):1301–1321

    Google Scholar 

  • Beg I, Rashid T (2016) Hesitant 2-tuple linguistic information in multiple attributes group decision making. J Intell Fuzzy Syst 30(1):109–116

    MATH  Google Scholar 

  • Bordogna G, Fedrizzi M, Pasi G (1997) A linguistic modeling of consensus in group decision making based on owa operators. IEEE Trans Syst Man Cybern Part A Syst Hum 27(1):126–133

    Google Scholar 

  • Fan ZP, Liu Y (2010) A method for group decision-making based on multi-granularity uncertain linguistic information. Expert Syst Appl 37(5):4000–4008

    Google Scholar 

  • Feng XQ, Wei CP, Liu Q (2018) EDAS method for extended hesitant fuzzy linguistic multi-criteria decision making. Int J Fuzzy Syst 20(8):2470–2483

    MathSciNet  Google Scholar 

  • Finch G (2000) Linguistic terms and concepts. Macmillan Education, London

    Google Scholar 

  • Ghorabaee MK, Zavadskas EK, Amiri M, Turskis Z (2016) Extended edas method for fuzzy multi-criteria decision-making: an application to supplier selection. Int J Comput Commun Control 11(3):358–371

    Google Scholar 

  • Gou XJ, Xu ZS (2016) Novel basic operational laws for linguistic terms, hesitant fuzzy linguistic term sets and probabilistic linguistic term sets. Inf Sci 372:407–427

    Google Scholar 

  • Gou XJ, Xu ZS, Liao HC (2017) Multiple criteria decision making based on Bonferroni means with hesitant fuzzy linguistic information. Soft Comput 21(21):6515–6529

    MATH  Google Scholar 

  • Jin LS (2015) Some properties and representation methods for ordered weighted averaging operators. Fuzzy Sets Syst 261:60–86

    MathSciNet  MATH  Google Scholar 

  • Keshavarz Ghorabaee M, Zavadskas EK, Olfat L, Turskis Z (2015) Multi-criteria inventory classification using a new method of evaluation based on distance from average solution (EDAS). Informatica 26(3):435–451

    Google Scholar 

  • Köksalan M, Karasakal E (2006) An interactive approach for multiobjective decision making. J Oper Res Soc 57(5):532–540

    MATH  Google Scholar 

  • Lee LW, Chen SM (2014) A new group decision making method based on likelihood-based comparison relations of hesitant fuzzy linguistic term sets. In: IEEE international conference on systems. IEEE

  • Li J, Wang JQ, Hu JH (2018a) Multi-criteria decision-making method based on dominance degree and BWM with probabilistic hesitant fuzzy information. Int J Mach Learn Cybern. https://doi.org/10.1007/s13042-018-0845-2

    Article  Google Scholar 

  • Li YY, Wang JQ, Wang TL (2018b) A linguistic neutrosophic multi-criteria group decision-making approach with EDAS method. Arab J Sci Eng. https://doi.org/10.1007/s13369-018-3487-5

    Article  Google Scholar 

  • Liang DC, Kobina A, Quan W (2017) Grey relational analysis method for probabilistic linguistic multi-criteria group decision-making based on geometric Bonferroni mean. Int J Fuzzy Syst 20(7):2234–2244

    Google Scholar 

  • Lin MW, Xu ZS (2018) Probabilistic linguistic distance measures and their applications in multi-criteria group decision making, vol 357, pp 411–440

  • Liu PD, Teng F (2018) Some Muirhead mean operators for probabilistic linguistic term sets and their applications to multiple attribute decision-making. Appl Soft Comput 68:396–431

    Google Scholar 

  • Liu S, Chan FT, Ran W (2013) Multi-attribute group decision-making with multi-granularity linguistic assessment information: an improved approach based on deviation and TOPSIS. Appl Math Model 37(24):10129–10140

    MathSciNet  MATH  Google Scholar 

  • Merigó José M, Casanovas M, Palacios-Marqués D (2014) Linguistic group decision making with induced aggregation operators and probabilistic information. Appl Soft Comput 24:669–678

    Google Scholar 

  • Pang Q, Wang H, Xu ZS (2016) Probabilistic linguistic term sets in multi-attribute group decision making. Inf Sci 369:128–143

    Google Scholar 

  • Patel A, Al-Janabi S, AlShourbaji I, Pedersen J (2015) A novel methodology towards a trusted environment in mashup web applications. Comput Secur 49:107–122

    Google Scholar 

  • Rodriguez RM, Herrera F, Martinez L (2000) A fusion approach for managing multi-granularity linguistic term sets in decision making. Fuzzy Sets Syst 114(1):43–58

    MATH  Google Scholar 

  • Rodriguez RM, Martinez L, Herrera F (2012) Hesitant fuzzy linguistic term sets for decision making. IEEE Trans Fuzzy Syst 20(1):109–119

    Google Scholar 

  • Sykora S (2009) Mathematical means and averages: generalized Heronian means. Stan’s Library

  • Tang XY, Wei GW (2018) Multiple attribute decision-making with dual hesitant pythagorean fuzzy information. Cognit Comput 11(6):193–211

    Google Scholar 

  • Tang XY, Wei GW, Gao H (2019) Models for multiple attribute decision making with interval-valued pythagorean fuzzy muirhead mean operators and their application to green suppliers selection. Informatica 30(1):153–186

    Google Scholar 

  • Torfi F, Farahani RZ, Rezapour S (2010) Fuzzy AHP to determine the relative weights of evaluation criteria and fuzzy TOPSIS to rank the alternatives. Appl Soft Comput 10(2):520–528

    Google Scholar 

  • Torra V (2010) Hesitant fuzzy sets. Int J Intell Syst 25(6):529–539

    MATH  Google Scholar 

  • Wang YM (1997) Using the method of maximizing deviation to make decision for multiindices. J Syst Eng Electron 8(3):21–26

    Google Scholar 

  • Wang L, Peng JJ, Wang JQ (2018) A multi-criteria decision-making framework for risk ranking of energy performance contracting project under picture fuzzy environment. J Clean Prod 191:105–118

    Google Scholar 

  • Wang R, Wang J, Gao H, Wei G (2019) Methods for MADM with picture fuzzy muirhead mean operators and their application for evaluating the financial investment risk. Symmetry 11(1):6

    MATH  Google Scholar 

  • Wei CP, Ren ZL, Rodríguez RM (2015) A hesitant fuzzy linguistic TODIM method based on a score function. Int J Comput Intell Syst 8(4):701–712

    Google Scholar 

  • Xu ZS, Wang H (2016) Managing multi-granularity linguistic information in qualitative group decision making: an overview. Granul Comput 1(1):21–35

    Google Scholar 

  • Yager RR (1993) On ordered weighted averaging aggregation operators in multicriteria decisionmaking. Read Fuzzy Sets Intell Syst 18(1):80–87

    MathSciNet  Google Scholar 

  • Yager RR (2001) The power average operator. IEEE Trans Syst Man Cybern Part Syst Hum 31(6):724–731

    Google Scholar 

  • Yager RR (2007) Centered OWA operators. Soft Comput 11(7):631–639

    MATH  Google Scholar 

  • Zadeh LA (1965) Fuzzy sets. Inf Control 8:338–353

    MATH  Google Scholar 

  • Zhai Y, Xu ZS, Liao HC (2016) Probabilistic linguistic vector-term set and its application in group decision making with multi-granular linguistic information. Appl Soft Comput 49:801–816

    Google Scholar 

  • Zhang WK, Ju YB, Liu XY (2017) Multiple criteria decision analysis based on Shapley fuzzy measures and interval-valued hesitant fuzzy linguistic numbers. Comput Ind Eng 105:28–38

    Google Scholar 

  • Zhang YX, Xu ZS, Liao HC (2018) Water security evaluation based on the TODIM method with probabilistic linguistic term sets. Soft Comput. https://doi.org/10.1007/s00500-018-3276-9

    Article  Google Scholar 

  • Zhang S, Gao H, Wei G et al (2019) Evaluation based on distance from average solution method for multiple criteria group decision making under picture 2-Tuple linguistic environment. Mathematics 7(3):243

    Google Scholar 

  • Zhou SH, Yang JC, Ding YS, Xu XH (2017) A Markov chain approximation to multi-stage interactive group decision-making method based on interval fuzzy number. Soft Comput 21(10):2701–2708

    Google Scholar 

Download references

Funding

This study was funded by University Natural Sciences Project of Jiangsu Province (No. 16KJB110015) and University Social Sciences Project of Jiangsu Province (No. 2016SJD630014).

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Correspondence to Xiangqian Feng.

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Appendices

Appendix A

Definition A1

(Pang et al. 2016) Let \( S = \{ s_{ - \tau } , \ldots ,s_{0} , \ldots ,s_{\tau } \} \) be a LTS, a PLTS can be defined as:

$$ L(p) = \left\{ {L^{(k)} \left( {p^{(k)} } \right)|L^{(k)} \in S,\;p^{\left( k \right)} \ge 0,\;k = 1,2, \ldots ,\# L(p),\sum\nolimits_{k = 1}^{\# L(p)} {p^{(k)} } \le 1} \right\} , $$
(A1)

where \( L^{(k)} (p^{(k)} ) \) represents the LT \( L^{(k)} \) associated with the probability \( p^{(k)} \), and \( \# L(p) \) be the number of LTs in \( L(p) \).

Definition A2

(Gou et al. 2017) Let \( S = \{ s_{ - \tau } , \ldots ,s_{0} , \ldots ,s_{\tau } \} \) and \( S^{{\prime }} = \{ s_{{ - \tau^{{\prime }} }} , \ldots ,s_{0} , \ldots ,s_{{\tau^{{\prime }} }} \} \) be two LTS, \( L_{S} (p) \) be a PLTS based on \( S \), and \( r^{\left( k \right)} \) be the subscript of LT \( L^{(k)} \), then the transformation function \( g \) can be defined to realize the reciprocal transformation between PLTSs with multi-granular linguistic information, which is shown as follows:

$$ g:{\kern 1pt} \,[ - \tau ,\tau ] \to [0,1]\quad g\left( {L_{S} (p)} \right) = \left\{ {\left( {\frac{{r^{(k)} }}{2\tau } + \frac{1}{2}} \right)(p^{(k)} )} \right\} = \left\{ {\eta^{(k)} (p^{\left( k \right)} )|\eta^{(k)} \in [0,1]} \right\} , $$
(A2)
$$ g^{ - 1} :\,{\kern 1pt} \left[ {0,1} \right] \to \left[ { - \tau^{{\prime }} ,\tau^{{\prime }} } \right]\quad g^{ - 1}_{{S^{{\prime }} }} \left( {g\left( {L_{S} (p)} \right)} \right) = \left\{ {\left( {s_{{\left( {2\eta^{(k)} - 1} \right) \cdot \tau^{{\prime }} }} (p^{k} )} \right)|\eta^{(k)} \in \left[ {0,1} \right]} \right\}_{{S^{{\prime }} }} , $$
(A3)

where \( \eta \in [0,1] \) be a crisp value transformed from linguistic information. For the sake of the simplicity in calculation and application, we often normalize the PLTSs with multi-granularity linguistic information to the uniform maximal granularity, and the subscript \( r^{\left( k \right)} \) will also be rounded. Further, the transformation function \( g^{ - 1} \) is improved as:

$$ g^{ - 1} :\,{\kern 1pt} \left[ {0,1} \right] \to \left[ { - t,t} \right]\quad g^{ - 1}_{{\overline{S} }} \left( {g\left( {L_{S} (p)} \right)} \right) = \left\{ {\left( {s_{{[\left( {2\eta^{(k)} - 1} \right) \cdot t]}} (p^{k} )} \right)|\eta^{(k)} \in \left[ {0,1} \right]} \right\}_{{\overline{S} }} , $$
(A4)

where \( \overline{S} = \{ s_{ - t} , \ldots ,s_{0} , \ldots ,s_{t} \left| {t = \hbox{max} (\tau ,\tau^{{\prime }} )} \right.\} \), and \( [ \cdot ] \) represents the integration.

Example A1

Let \( S = \{ s_{ - 3} = {\text{very}}\,{\text{low}},s_{ - 2} = {\text{low}},s_{ - 1} = {\text{slightly}}\,{\text{low}},s_{0} = {\text{fair}},s_{1} = {\text{slightly}}\,{\text{high}},s_{2} = {\text{high}},s_{3} = {\text{very}}\,{\text{high}}\} \), \( S^{{\prime }} = \{ s_{ - 2} = {\text{very}}\,{\text{low}},s_{ - 1} = {\text{low}},s_{0} = {\text{fair}},s_{1} = {\text{high}},s_{2} = {\text{very}}\,{\text{high}}\} \) and \( L_{S} (p) = \{ s_{ - 1} (0.2),s_{0} (0.3),s_{2} (0.4)\} \), \( L{\prime }_{{S^{{\prime }} }} (p) = \{ s_{0} (0.6),s_{1} (0.4)\} \). After being transformed by Definition A2, we can obtain:

$$ \begin{aligned} & g\left( {L\prime_{S'} (p)} \right) = \{ 0.5(0.6),0.75(0.4)\} , \\ & g^{ - 1}_{{\overline{S} }} \left( {g\left( {L\prime_{{S^{\prime } }} (p)} \right)} \right) = \left\{ {s_{0} (0.6),s_{2} (0.4)} \right\}_{{\overline{S} }} . \\ \end{aligned} $$

Definition A3

(Gou and Xu 2016) Let \( S = \{ s_{ - \tau } , \ldots ,s_{0} , \ldots ,s_{\tau } \} \) and \( S^{\prime } = \{ s_{{ - \tau^{\prime } }} , \ldots ,s_{0} , \ldots ,s_{{\tau^{\prime } }} \} \) be two different LTSs, and \( \overline{S} = \{ s_{ - t} , \ldots ,s_{0} , \ldots ,s_{t} \left| {t = \hbox{max} (\tau ,\tau^{{\prime }} )} \right.\} \) be another LTS. \( L_{S} (p) \) be an arbitrary PLTS based on LT \( S \), and \( L{\prime }_{{S^{{\prime }} }} (p) \) be another based on \( S^{{\prime }} \). Suppose \( \nu \) be a positive real value, and \( \eta^{(i)} \in g(L_{S} ) \), \( \eta^{{{\prime }(j)}} \in g(L^{{\prime }}_{{S^{{\prime }} }} ) \) and \( i = 1,2, \ldots ,\# L_{S} (p) \), \( j = 1,2, \ldots ,\# L^{{\prime }}_{{S^{{\prime }} }} (p) \). Then:

  1. (1)

    \( L_{S} (p) \oplus L^{{\prime }}_{{S^{{\prime }} }} (p) = g^{ - 1}_{{\overline{S} }} \left( {\bigcup\limits_{{\eta^{(i)} \in g(L),\eta {\prime }^{(j)} \in g\left( {L^{{\prime }} } \right)}} {\left\{ {\left( {\eta^{(i)} + \eta^{{{\prime }(j)}} - \eta^{(i)} \eta^{{{\prime }(j)}} } \right)\left( {p^{(i)} p^{{{\prime }(j)}} } \right)} \right\}} } \right) \);

  2. (2)

    \( L_{S} (p) \otimes L^{{\prime }}_{{S^{{\prime }} }} (p) = g^{ - 1}_{{\overline{S} }} \left( {\bigcup\limits_{{\eta^{(i)} \in g(L),\eta^{{{\prime }(j)}} \in g\left( {L^{{\prime }} } \right)}} {\left\{ {\left( {\eta^{(i)} \eta^{{{\prime }(j)}} } \right)\left( {p^{(i)} p^{{{\prime }(j)}} } \right)} \right\}} } \right) \);

  3. (3)

    \( \nu L_{S} (p) = g^{ - 1}_{{\overline{S} }} \left( {\bigcup\limits_{{\eta^{(i)} \in g(L)}} {\left\{ {\left( {1 - \left( {1 - \eta^{(i)} } \right)^{\nu } } \right)\left( {p^{(i)} } \right)} \right\}} } \right) \);

  4. (4)

    \( L_{S}^{\nu } (p) = g^{ - 1}_{{\overline{S} }} \left( {\bigcup\limits_{{\eta^{(i)} \in g(L)}} {\left\{ {\left( {\eta^{(i)} } \right)^{\nu } \left( {p^{(i)} } \right)} \right\}} } \right) \);

  5. (5)

    \( {\text{neg}}(L_{S} (p)) = g^{ - 1}_{{\overline{S} }} \left( {\bigcup\limits_{{\eta^{(i)} \in g(L)}} {\left\{ {\left( {1 - \eta^{(i)} } \right)\left( {p^{(i)} } \right)} \right\}} } \right) \).

Example A2

By using Example A1, let \( \nu = 2 \), then:

  1. (1)

    \( \begin{aligned} & L_{S} (p) \oplus L^{{\prime }}_{{S^{{\prime }} }} (p) = g^{ - 1}_{{\overline{S} }} \left( {\bigcup\limits_{{\eta^{(i)} \in g(L),\eta {\prime }^{(j)} \in g\left( {L^{{\prime }} } \right)}} {\left\{ {\left( {\eta^{(i)} + \eta^{{{\prime }(j)}} - \eta^{(i)} \eta^{{{\prime }(j)}} } \right)\left( {p^{(i)} p^{{{\prime }(j)}} } \right)} \right\}} } \right) \\ & \quad = g^{ - 1}_{{\overline{S} }} \left\{ {\frac{2}{3}(0.13),\frac{7}{9}(0.09),\frac{3}{4}(0.2),\frac{5}{6}(0.13),\frac{11}{12}(0.27),\frac{17}{18}(0.18)} \right\} \\ & \quad = \{ s_{1} (0.13),s_{2} (0.42),s_{3} (0.45)\}_{{\overline{S} }} ; \\ \end{aligned} \)

  2. (2)

    \( \begin{aligned} & L_{S} (p) \otimes L^{{\prime }}_{{S^{{\prime }} }} (p) = g^{ - 1}_{{\overline{S} }} \left( {\bigcup\limits_{{\eta^{(i)} \in g(L),\eta {\prime }^{(j)} \in g\left( {L^{{\prime }} } \right)}} {\left\{ {\left( {\eta^{(i)} \eta^{{{\prime }(j)}} } \right)\left( {p^{(i)} p^{{{\prime }(j)}} } \right)} \right\}} } \right) \\ & \quad = g^{ - 1}_{{\overline{S} }} \left\{ {\frac{1}{6}(0.13),\frac{2}{9}(0.09),\frac{1}{4}(0.2),\frac{1}{3}(0.13),\frac{5}{12}(0.27),\frac{5}{9}(0.18)} \right\} \\ & \quad = \{ s_{ - 2} (0.42),s_{ - 1} (0.4),s_{0} (0.18)\}_{{\overline{S} }} ; \\ \end{aligned} \)

  3. (3)

    \( \begin{aligned} & 2L_{S} (p) = g^{ - 1}_{{\overline{S} }} \left( {\bigcup\limits_{{\eta^{(i)} \in g(L)}} {\left\{ {\left( {1 - \left( {1 - \eta^{(i)} } \right)^{2} } \right)\left( {p^{(i)} } \right)} \right\}} } \right) \\ & \quad = g^{ - 1}_{{\overline{S} }} \{ 0.56(0.22),0.75(0.33),0.97(0.44)\} \\ & \quad = \{ s_{0} (0.22),s_{2} (0.33),s_{3} (0.44)\}_{{\overline{S} }} ; \\ \end{aligned} \)

  4. (4)

    \( \begin{aligned} & {\text{neg}}(L_{S} (p)) = g^{ - 1}_{{\overline{S} }} \left( {\bigcup\limits_{{\eta^{(i)} \in g(L)}} {\left\{ {\left( {1 - \eta^{(i)} } \right)\left( {p^{(i)} } \right)} \right\}} } \right) \\ & \quad = g^{ - 1}_{{\overline{S} }} \{ 0.67(0.22),0.5(0.33),0.17(0.44)\} \\ & \quad = \{ s_{ - 2} (0.44),s_{0} (0.33),s_{1} (0.22)\}_{{\overline{S} }} . \\ \end{aligned} \)

Definition A4

(Bai et al. 2018) Let \( S = \{ s_{t} \left| {t = - \tau , \ldots , - 1,0,1, \ldots ,\tau } \right.\} \) be an LTS, \( L_{1} (p) \) and \( L_{2} (p) \) be two PLTSs. We add any LT in \( L_{i} (i = 1,2) \), so that the PLTSs have the same number of LTs. The transformed PLTSs are denoted as \( L_{i}^{{\prime }} (i = 1,2) \). Let \( P^{{\prime }}_{S(j,k)} \) be the probability degree of the common LTs in \( L_{j}^{{\prime }} \) and \( L_{k}^{{\prime }} \,(j = 1\,{\text{or}}\,{\kern 1pt} 2,k = 2\,{\text{or}}\,{\kern 1pt} 1) \), and \( P^{{\prime }}_{S(j)} \) be the probability degree of all LTs in \( L_{j}^{{\prime }} \) larger than the corresponding terms in \( L_{k}^{{\prime }} \). The ratio

$$ p_{1} (L_{1} \ge L_{2} ) = \frac{{P^{{\prime }}_{S(1)} + 0.5P^{{\prime }}_{S(1,2)} }}{{P^{{\prime }}_{S(1)} + P^{{\prime }}_{S(2)} + 0.5(P^{{\prime }}_{S(1,2)} + P^{{\prime }}_{S(2,1)} )}} $$
(A5)

is defined as the possibility degree of \( L_{1} \) being not less than \( L_{2} \).

Definition A5

(Li et al. 2018a) Let \( S = \{ s_{t} \left| {t = - \tau , \ldots , - 1,0,1, \ldots ,\tau } \right.\} \) be an LTS, \( L_{1} (p) \) and \( L_{2} (p) \) be two PLTSs, \( p_{1} (L_{1} ) \) and \( p_{2} (L_{2} ) \) be the probability distribution functions of \( L_{1} (p) \) and \( L_{2} (p) \), respectively, where \( \sum\nolimits_{i = 1}^{{\# L_{1} (p)}} {p_{1} (L_{1}^{(i)} ) = 1} \) and \( \sum\nolimits_{j = 1}^{{\# L_{2} (p)}} {p_{2} (L_{2}^{(j)} ) = 1} \). Then, the dominance degree of \( L_{1} (p) \) being not less than \( L_{2} (p) \) is determined as:

$$ p_{2} (L_{1} (p) \ge L_{2} (p)) = \sum\limits_{i = 1}^{{\# L_{1} (p)}} {\sum\limits_{{j = 1,{\kern 1pt} {\kern 1pt} r_{2}^{(j)} \le r_{1}^{(i)} }}^{{\# L_{2} (p)}} {p(L_{1}^{i} )p(L_{2}^{j} )} } - 0.5\sum\limits_{i = 1}^{{\# L_{1} (p)}} {\sum\limits_{{j = 1,{\kern 1pt} {\kern 1pt} r_{2}^{(j)} = r_{1}^{(i)} }}^{{\# L_{2} (p)}} {p(L_{1}^{i} )p(L_{2}^{j} )} } , $$
(A6)

where \( r_{1}^{(i)} \) be the subscript of LT \( L_{1}^{(i)} \), and \( r_{2}^{(j)} \) be the subscript of LT \( L_{2}^{(j)} \), \( i = 1,2, \ldots ,\# L_{1} (p) \), \( j = 1,2, \ldots ,\# L_{2} (p) \).

The comparison between \( L_{1} (p) \) and \( L_{2} (p) \) is as follows: if \( p(L_{1} (p) \ge L_{2} (p)) > 0.5 \), then \( L_{1} (p) \) is superior to \( L_{2} (p) \); if \( p(L_{1} (p) \ge L_{2} (p)) < 0.5 \), then \( L_{1} (p) \) is inferior to \( L_{2} (p) \); if \( p(L_{1} (p) \ge L_{2} (p)) = 0.5 \), then \( L_{1} (p) \) is indifferent to \( L_{2} (p) \).

Furthermore, the possibility degree or dominance degree formulae previously defined satisfy the following properties:

  1. (1)

    \( 0 \le p(L_{1} \ge L_{2} ) \le 1 \)

  2. (2)

    \( p(L_{1} \ge L_{2} ) + p(L_{2} \ge L_{1} ) = 1 \)

  3. (3)

    \( p(L_{1} \ge L_{2} ) = 1 \), only if \( \hbox{min} (r_{1}^{(i)} ) \ge \hbox{max} (r_{2}^{(j)} )\;\left( {i = 1,2, \ldots ,\# L_{1} ;j = 1,2, \ldots ,\# L_{2} } \right) \)

  4. (4)

    \( p(L_{1} \ge L_{2} ) = 0{\kern 1pt} \), only if \( \hbox{max} (r_{1}^{(i)} ) \le \hbox{min} (r_{2}^{(j)} )\;\left( {i = 1,2, \ldots ,\# L_{1} ;j = 1,2, \ldots ,\# L_{2} } \right) \)

Appendix B

Proof of Theorem 1

For convenience, let \( \chi_{i} = w_{i}^{{\prime }} K\int_{{\frac{i - 1}{n}}}^{{\frac{i}{n}}} {\varphi \left( y \right){\text{d}}y} \), then Theorem 1 can be proven via the arithmetical operations of PLTSs presented in Sect. 2.

  1. (1)

    When n = 2, we have

    $$ \begin{aligned} & {\text{PLCOWA}}(L_{1} (p),L_{2} (p)) = \chi_{1} L_{1}^{{\prime }} (p) \oplus \chi_{2} L_{2}^{{\prime }} (p) \\ & \quad = g^{ - 1} \left( {\bigcup\limits_{{\eta_{1}^{{{\prime }(k)}} \in g\left( {L_{1}^{{\prime }} (p)} \right)}} {\left\{ {\left( {1 - \left( {1 - \eta_{1}^{{{\prime }(k)}} } \right)^{{\chi_{1} }} } \right)\left( {p^{{{\prime }(k)}} } \right)} \right\}} } \right) \oplus g^{ - 1} \left( {\bigcup\limits_{{\eta_{2}^{{{\prime }(t)}} \in g\left( {L_{2}^{{\prime }} (p)} \right)}} {\left\{ {\left( {1 - \left( {1 - \eta_{2}^{{{\prime }(t)}} } \right)^{{\chi_{2} }} } \right)\left( {p^{{{\prime }(t)}} } \right)} \right\}} } \right) \\ & \quad = g^{ - 1} \left( {\bigcup\limits_{ \eta_{1}^{{{\prime }(k)}} \in g\left( {L_{1}^{{\prime }} (p)} \right), \eta_{2}^{{{\prime }(t)}} \in g\left( {L_{2}^{{\prime }} (p)} \right)} {\left\{ {\left( {1 - \left( {1 - \eta_{1}^{{{\prime }(k)}} } \right)^{{\chi_{1} }} + 1 - \left( {1 - \eta_{2}^{{{\prime }(t)}} } \right)^{{\chi_{2} }} - \left( {1 - \left( {1 - \eta_{1}^{{{\prime }(k)}} } \right)^{{\chi_{1} }} } \right) \cdot \left( {1 - \left( {1 - \eta_{2}^{{{\prime }(t)}} } \right)^{{\chi_{2} }} } \right)} \right) \cdot \left( {p_{1}^{{{\prime }(k)}} p_{2}^{{{\prime }(t)}} } \right)} \right\}} } \right) \\ & \quad = g^{ - 1} \left( {\bigcup\limits_{{\eta_{1}^{{{\prime }(k)}} \in g\left( {L_{1}^{{\prime }} (p)} \right),\eta_{2}^{{{\prime }(t)}} \in g\left( {L_{2}^{{\prime }} (p)} \right)}} {\left\{ {\left( {1 - \left( {1 - \eta_{1}^{{{\prime }(k)}} } \right)^{{\chi_{1} }} \cdot \left( {1 - \eta_{2}^{{{\prime }(k)}} } \right)^{{\chi_{2} }} } \right) \cdot \left( {p_{1}^{{{\prime }(k)}} p_{2}^{{{\prime }(t)}} } \right)} \right\}} } \right). \\ \end{aligned} $$

    Therefore, when n = 2, Theorem 1 is true.

  2. (2)

    Assume that when n = k, Theorem 1 is true. Thus,

    $$ {\text{PLCOWA}}(L_{1} (p),L_{2} (p), \ldots ,L_{k} (p)) = g^{ - 1} \left( {\bigcup\limits_{{\eta_{1}^{{\prime }} \in g(L_{1}^{{\prime }} (p)),\eta_{2}^{{\prime }} \in g(L_{2}^{{\prime }} (p)), \ldots ,\eta_{k}^{{\prime }} \in g(L_{k}^{{\prime }} (p))}} {\left\{ {\left( {1 - \prod\limits_{i = 1}^{k} {(1 - \eta_{i}^{{\prime }} )^{{\chi_{i} }} } } \right) \cdot \left( {p_{1}^{{\prime }} p_{2}^{{\prime }} \ldots p_{k}^{{\prime }} } \right)} \right\}} } \right) . $$

    Then, when n = k + 1, we have

    $$ \begin{aligned} & {\text{PLCOWA}}(L_{1} (p),L_{2} (p), \ldots ,L_{k} (p),L_{k + 1} (p)) \\ & \quad = {\text{PLPWA}}(L_{1} (p),L_{2} (p), \ldots ,L_{k} (p)) \oplus \chi_{i + 1} L_{k + 1} (p) \\ {\kern 1pt} & \quad = g^{ - 1} \left( {\bigcup\limits_{{\eta_{1}^{{\prime }} \in g(L_{1}^{{\prime }} (p)),\eta_{2}^{{\prime }} \in g(L_{2}^{{\prime }} (p)), \ldots ,\eta_{k}^{{\prime }} \in g(L_{k}^{{\prime }} (p))}} {\left\{ {\left( {1 - \prod\limits_{i = 1}^{k} (1 - \eta_{i}^{{\prime }} )^{{\chi_{i} }} } \right) \cdot \left( {p_{1}^{{\prime }} p_{2}^{{\prime }} \ldots p_{k}^{{\prime }} } \right)} \right\}} } \right) \oplus \\ & \quad \quad g^{ - 1} \left( {\bigcup\limits_{{\eta_{k + 1}^{{\prime }} \in g\left( {L_{k + 1}^{{\prime }} (p)} \right)}} {\left\{ {\left( {1 - \left( {1 - \eta_{k + 1}^{{\prime }} } \right)^{{\chi_{i + 1} }} } \right)\left( {p_{k + 1}^{{\prime }} } \right)} \right\}} } \right) \\ & \quad = g^{ - 1} \left( {\bigcup\limits_{{\eta_{1}^{{\prime }} \in g(L_{1}^{{\prime }} (p)),\eta_{2}^{{\prime }} \in g(L_{2}^{{\prime }} (p)), \ldots ,\eta_{k}^{{\prime }} \in g(L_{k}^{{\prime }} (p)),\eta_{k + 1}^{{\prime }} \in g\left( {L_{k + 1}^{{\prime }} (p)} \right)}} {\left\{ {\left( {1 - \prod\limits_{i = 1}^{k} (1 - \eta_{i}^{{\prime }} )^{{\chi_{i} }} \cdot \left( {1 - \eta_{k + 1}^{{\prime }} } \right)^{{\chi_{i + 1} }} } \right) \cdot \left( {p_{1}^{{\prime }} p_{2}^{{\prime }} \ldots p_{k}^{{\prime }} p_{k + 1}^{{\prime }} } \right)} \right\}} } \right) \\ & \quad = g^{ - 1} \left( {\bigcup\limits_{{\eta_{1}^{{\prime }} \in g(L_{1}^{{\prime }} (p)),\eta_{2}^{{\prime }} \in g(L_{2}^{{\prime }} (p)), \ldots ,\eta_{k}^{{\prime }} \in g(L_{k}^{{\prime }} (p)),\eta_{k + 1}^{{\prime }} \in g\left( {L_{k + 1}^{{\prime }} (p)} \right)}} {\left\{ {\left( {1 - \prod\limits_{i = 1}^{k + 1} (1 - \eta_{i}^{{\prime }} )^{{\chi_{i} }} } \right) \cdot \left( {p_{1}^{{\prime }} p_{2}^{{\prime }} \ldots p_{k}^{{\prime }} p_{k + 1}^{{\prime }} } \right)} \right\}} } \right). \\ \end{aligned} $$

    Thus, when n = k + 1, Theorem 1 is true.

Proof of Theorem 2

For convenience, let \( \varphi_{i} = \frac{{(1 + T(L_{i} (p)))w_{i} }}{{\sum\nolimits_{i = 1}^{n} {(1 + T(L_{i} (p)))w_{i} } }} \), then Theorem 2 can be proven via the arithmetical operations of PLTSs presented in Sect. 2.

  1. (1)

    When n = 2, we have

    $$ \begin{aligned} & {\text{PLPWA}}(L_{1} (p),L_{2} (p)) = \varphi_{1} L_{1} (p) \oplus \varphi_{2} L_{2} (p) \\ {\kern 1pt} & \quad = g^{ - 1} \left( {\bigcup\limits_{{\eta_{1}^{(k)} \in g\left( {L_{1} (p)} \right)}} {\left\{ {\left( {1 - \left( {1 - \eta_{1}^{\left( k \right)} } \right)^{{\varphi_{1} }} } \right)\left( {p^{\left( k \right)} } \right)} \right\}} } \right){\kern 1pt} {\kern 1pt} {\kern 1pt} \oplus g^{ - 1} \left( {\bigcup\limits_{{\eta_{2}^{\left( t \right)} \in g\left( {L_{2} (p)} \right)}} {\left\{ {\left( {1 - \left( {1 - \eta_{2}^{\left( t \right)} } \right)^{{\varphi_{2} }} } \right)\left( {p^{\left( t \right)} } \right)} \right\}} } \right){\kern 1pt} {\kern 1pt} \\ & \quad = g^{ - 1} \left( {\bigcup\limits_{ \eta_{1}^{\left( k \right)} \in g\left( {L_{1} (p)} \right), \eta_{2}^{\left( t \right)} \in g\left( {L_{2} (p)} \right) } {\left\{ {\left( {1 - \left( {1 - \eta_{1}^{\left( k \right)} } \right)^{{\varphi_{1} }} + 1 - \left( {1 - \eta_{2}^{\left( t \right)} } \right)^{{\varphi_{2} }} - \left( {1 - \left( {1 - \eta_{1}^{\left( k \right)} } \right)^{{\varphi_{1} }} } \right) \cdot \left( {1 - \left( {1 - \eta_{2}^{\left( t \right)} } \right)^{{\varphi_{2} }} } \right)} \right) \cdot \left( {p_{1}^{\left( k \right)} p_{2}^{\left( t \right)} } \right)} \right\}} } \right){\kern 1pt} \\ & \quad = g^{ - 1} \left( {\bigcup\limits_{{\eta_{1}^{\left( k \right)} \in g\left( {L_{1} (p)} \right),\eta_{2}^{\left( t \right)} \in g\left( {L_{2} (p)} \right)}} {\left\{ {\left( {1 - \left( {1 - \eta_{1}^{\left( k \right)} } \right)^{{\varphi_{1} }} \cdot \left( {1 - \eta_{2}^{\left( t \right)} } \right)^{{\varphi_{2} }} } \right) \cdot \left( {p_{1}^{\left( k \right)} p_{2}^{\left( t \right)} } \right)} \right\}} } \right). \\ \end{aligned} $$

    Therefore, when n = 2, Theorem 2 is true.

  2. (2)

    Assume that when n = k, Theorem 2 is true. Thus,

    $$ {\text{PLPWA}}(L_{1} (p),L_{2} (p), \ldots ,L_{k} (p)) = g^{ - 1} \left( {\bigcup\limits_{{\eta_{1} \in g(L_{1} (p)),\eta_{2} \in g(L_{2} (p)), \ldots ,\eta_{k} \in g(L_{k} (p))}} {\left\{ {\left( {1 - \prod\limits_{i = 1}^{k} (1 - \eta_{i} )^{{\varphi_{i} }} } \right) \cdot \left( {p_{1} p_{2} \ldots p_{k} } \right)} \right\}} } \right) . $$

    Then, when n = k + 1, we have

    $$ \begin{aligned} & {\text{PLPWA}}(L_{1} (p),L_{2} (p), \ldots ,L_{k} (p),L_{k + 1} (p)) = {\text{PLPWA}}(L_{1} (p),L_{2} (p), \ldots ,L_{k} (p)) \oplus \varphi_{i + 1} L_{k + 1} (p) \\ {\kern 1pt} & \quad = g^{ - 1} \left( {\bigcup\limits_{\eta_{1} \in g(L_{1} (p)),\eta_{2} \in g(L_{2} (p)), \ldots ,\eta_{k} \in g(L_{k} (p)) } {\left\{ {\left( {1 - \prod\limits_{i = 1}^{k} (1 - \eta_{i} )^{{\varphi_{i} }} } \right) \cdot \left( {p_{1} p_{2} \ldots p_{k} } \right)} \right\}} } \right) \oplus g^{ - 1} \left( {\bigcup\limits_{{\eta_{k + 1} \in g\left( {L_{k + 1} (p)} \right)}} {\left\{ {\left( {1 - \left( {1 - \eta_{k + 1} } \right)^{{\varphi_{i + 1} }} } \right)\left( {p_{k + 1} } \right)} \right\}} } \right) \\ & \quad = g^{ - 1} \left( {\bigcup\limits_{\eta_{1} \in g(L_{1} (p)),\eta_{2} \in g(L_{2} (p)), \ldots ,\eta_{k} \in g(L_{k} (p)),\eta_{k + 1} \in g\left( {L_{k + 1} (p)} \right) } {\left\{ {\left( {1 - \prod\limits_{i = 1}^{k} (1 - \eta_{i} )^{{\varphi_{i} }} \cdot \left( {1 - \eta_{k + 1} } \right)^{{\varphi_{i + 1} }} } \right) \cdot \left( {p_{1} p_{2} \ldots p_{k} p_{k + 1} } \right)} \right\}} } \right) \\ & \quad = g^{ - 1} \left( {\bigcup\limits_{\eta_{1} \in g(L_{1} (p)),\eta_{2} \in g(L_{2} (p)), \ldots ,\eta_{k} \in g(L_{k} (p)),\eta_{k + 1} \in g\left( {L_{k + 1} (p)} \right) } {\left\{ {\left( {1 - \prod\limits_{i = 1}^{k + 1} (1 - \eta_{i} )^{{\varphi_{i} }} } \right) \cdot \left( {p_{1} p_{2} \ldots p_{k} p_{k + 1} } \right)} \right\}} } \right). \\ \end{aligned} $$

    Thus, when n = k + 1, Theorem 2 is true.

Proof of Theorem 3

Theorem 3 can be proven based on the arithmetical operations of PLTSs presented in Sect. 2.

  1. (1)

    When n = 2, we have

    $$ \begin{aligned} & {\text{PLHWM}}^{p,q} (L_{1} (p),L_{2} (p)) = \left( {\frac{1}{3}\left( {\sum\limits_{i = 1}^{n} {\sum\limits_{j = i}^{n} {\left( {nw_{i} L_{i} (p)} \right)^{p} \left( {nw_{j} L_{j} (p)} \right)^{q} } } } \right)} \right)^{{\frac{1}{p + q}}} \\ & \quad = \left( {\frac{1}{3}\left( {\sum\limits_{i = 1}^{2} {\sum\limits_{j = i}^{2} {\left( {g^{ - 1} \left( {\bigcup\limits_{{\eta_{i} \in g(L_{i} (p))}} {\left\{ {\left( {1 - (1 - \eta_{i} )^{{2w_{i} }} } \right) \cdot \left( {p_{i} } \right)} \right\}} } \right)^{p} \otimes g^{ - 1} \left( {\bigcup\limits_{{\eta_{j} \in g(L_{j} (p))}} {\left\{ {\left( {1 - (1 - \eta_{j} )^{{2w_{j} }} } \right) \cdot \left( {p_{j} } \right)} \right\}} } \right)^{q} } \right)} } } \right)} \right)^{{\frac{1}{p + q}}} \\ & \quad = \left( {\frac{1}{3}\left( \begin{aligned} g^{ - 1} \left( {\bigcup\limits_{{\eta_{1} \in g(L_{1} (p)),\eta_{2} \in g(L_{2} (p))}} {\left\{ {\left( {\left( {1 - (1 - \eta_{1} )^{{2w_{1} }} } \right)^{p} \left( {1 - (1 - \eta_{2} )^{{2w_{2} }} } \right)^{q} } \right) \cdot \left( {p_{1} p_{2} } \right)} \right\}} } \right) \hfill \\ \oplus g^{ - 1} \left( {\bigcup\limits_{{\eta_{1} \in g(L_{1} (p))}} {\left\{ {\left( {\left( {1 - (1 - \eta_{1} )^{{2w_{1} }} } \right)^{p + q} } \right) \cdot \left( {p_{1} } \right)} \right\}} } \right) \oplus g^{ - 1} \left( {\mathop U\limits_{{\eta_{2} \in g(L_{2} (p))}} \left\{ {\left( {\left( {1 - (1 - \eta_{2} )^{{2w_{2} }} } \right)^{p + q} } \right) \cdot \left( {p_{2} } \right)} \right\}} \right) \hfill \\ \end{aligned} \right)} \right)^{{\frac{1}{p + q}}} \\ & \quad = \left( {\frac{1}{3}\left( \begin{aligned} g^{ - 1} \left( {\bigcup\limits_{{\eta_{1} \in g(L_{1} (p)),\eta_{2} \in g(L_{2} (p))}} {\left\{ {\left( {\left( {1 - (1 - \eta_{1} )^{{2w_{1} }} } \right)^{p} \left( {1 - (1 - \eta_{2} )^{{2w_{2} }} } \right)^{q} } \right) \cdot \left( {p_{1} p_{2} } \right)} \right\}} } \right) \oplus \hfill \\ g^{ - 1} \left( {\bigcup\limits_{{\eta_{1} \in g(L_{1} (p))}} {\left\{ {\left( {\left( {1 - (1 - \eta_{1} )^{{2w_{1} }} } \right)^{p + q} + \left( {1 - (1 - \eta_{2} )^{{2w_{2} }} } \right)^{p + q} - \left( {1 - (1 - \eta_{1} )^{{2w_{1} }} } \right)^{p + q} \left( {1 - (1 - \eta_{2} )^{{2w_{2} }} } \right)^{p + q} } \right) \cdot \left( {p_{1} p_{2} } \right)} \right\}} } \right) \hfill \\ \end{aligned} \right)} \right)^{{\frac{1}{p + q}}} \\ & \quad = \left( {\frac{1}{3}\left( {g^{ - 1} \left( {\bigcup\limits_{ \eta_{1} \in g(L_{1} (p)), \eta_{2} \in g(L_{2} (p))} {\left\{ {\left( \begin{aligned} \left( {1 - (1 - \eta_{1} )^{{2w_{1} }} } \right)^{p} \left( {1 - (1 - \eta_{2} )^{{2w_{2} }} } \right)^{q} + \left( {1 - (1 - \eta_{1} )^{{2w_{1} }} } \right)^{p + q} + \left( {1 - (1 - \eta_{2} )^{{2w_{2} }} } \right)^{p + q} \hfill \\ - \left( {1 - (1 - \eta_{1} )^{{2w_{1} }} } \right)^{p + q} \left( {1 - (1 - \eta_{2} )^{{2w_{2} }} } \right)^{p + q} - \left( {1 - (1 - \eta_{1} )^{{2w_{1} }} } \right)^{p} \left( {1 - (1 - \eta_{2} )^{{2w_{2} }} } \right)^{q} \hfill \\ \left( \begin{aligned} \left( {1 - (1 - \eta_{1} )^{{2w_{1} }} } \right)^{p + q} + \left( {1 - (1 - \eta_{2} )^{{2w_{2} }} } \right)^{p + q} \hfill \\ - \left( {1 - (1 - \eta_{1} )^{{2w_{1} }} } \right)^{p + q} \left( {1 - (1 - \eta_{2} )^{{2w_{2} }} } \right)^{p + q} \hfill \\ \end{aligned} \right) \hfill \\ \end{aligned} \right) \cdot \left( {p_{1} p_{2} } \right)} \right\}} } \right)} \right)} \right)^{{\frac{1}{p + q}}} \\ & \quad = g^{ - 1} \left( {\bigcup\limits_{ \eta_{1} \in g(L_{1} (p)), \eta_{2} \in g(L_{2} (p)) } {\left\{ {\left( {1 - \left( {\prod\limits_{i = 1}^{2} \prod\limits_{j = i}^{2} \left( {1 - \left( {1 - (1 - \eta_{i} )^{{2w_{i} }} } \right)^{p} \left( {1 - (1 - \eta_{j} )^{{2w_{j} }} } \right)^{q} } \right)} \right)^{{\frac{1}{3}}} } \right)^{{\frac{1}{p + q}}} \cdot \left( {p_{1} p_{2} } \right)} \right\}} } \right). \\ \end{aligned} $$

    Therefore, when n = 2, Theorem 3 is true.

  2. (2)

    Assume that when n = k, Theorem 3 is true. Thus,

    $$ \begin{aligned} & {\text{PLHWM}}^{p,q} (L_{1} (p),L_{2} (p), \ldots ,L_{k} (p)) \\ & \quad = g^{ - 1} \left( {\bigcup\limits_{\eta_{1} \in g(L_{1} (p)),\eta_{2} \in g(L_{2} (p)), \ldots ,\eta_{k} \in g(L_{k} (p))} {\left\{ {\left( {1 - \left( {\prod\limits_{i = 1}^{k} \prod\limits_{j = i}^{k} \left( {1 - \left( {1 - (1 - \eta_{i} )^{{nw_{i} }} } \right)^{p} \left( {1 - (1 - \eta_{j} )^{{nw_{j} }} } \right)^{q} } \right)} \right)^{{\frac{2}{k(k + 1)}}} } \right)^{{\frac{1}{p + q}}} \cdot \left( {p_{1} p_{2} \ldots p_{k} } \right)} \right\}} } \right) \\ \end{aligned} . $$

    Then, when n = k + 1, we have

    $$ \begin{aligned} & {\text{PLHWM}}^{p,q} (L_{1} (p),L_{2} (p), \ldots ,L_{k} (p),L_{k + 1} (p)) \\ & \quad = \left( {\frac{2}{(k + 1)(k + 2)}\left( {\sum\limits_{i = 1}^{k} {\sum\limits_{j = i}^{k} {\left( {nw_{i} L_{i} (p)} \right)^{p} \left( {nw_{j} L_{j} (p)} \right)^{q} } } \oplus \sum\limits_{t = 1}^{k + 1} {\left( {nw_{t} L_{t} (p)} \right)^{p} \left( {nw_{k + 1} L_{k + 1} (p)} \right)^{q} } } \right)} \right)^{{\frac{1}{p + q}}} \\ & \quad = \left( {\frac{2}{(k + 1)(k + 2)}\left( \begin{aligned} g^{ - 1} \left( {\bigcup\limits_{\eta_{1} \in g(L_{1} (p)),\eta_{2} \in g(L_{2} (p)), \ldots ,\eta_{k} \in g(L_{k} (p))} {\left\{ {\left( {1 - \prod\limits_{i = 1}^{k} \prod\limits_{j = i}^{k} \left( {1 - \left( {1 - (1 - \eta_{i} )^{{nw_{i} }} } \right)^{p} \left( {1 - (1 - \eta_{j} )^{{nw_{j} }} } \right)^{q} } \right)} \right) \cdot \left( {p_{1} p_{2} \ldots p_{k} } \right)} \right\}} } \right) \hfill \\ \oplus g^{ - 1} \left( {\bigcup\limits_{ \eta_{t} \in g(L_{t} (p)), \eta_{k + 1} \in g(L_{k + 1} (p)) } {\left\{ {\left( {1 - \prod\limits_{t = 1}^{k + 1} \left( {1 - \left( {1 - (1 - \eta_{t} )^{{nw_{t} }} } \right)^{p} \left( {1 - (1 - \eta_{k + 1} )^{{nw_{k + 1} }} } \right)^{q} } \right)} \right) \cdot \left( {p_{1} p_{2} \ldots p_{k} p_{k + 1} } \right)} \right\}} } \right) \hfill \\ \end{aligned} \right)} \right)^{{\frac{1}{p + q}}} \\ & \quad = \left( {\frac{2}{(k + 1)(k + 2)}g^{ - 1} \left( {\bigcup\limits_{ \eta_{1} \in g(L_{1} (p)),\eta_{2} \in g(L_{2} (p)), \ldots , \eta_{k} \in g(L_{k} (p)),\eta_{k + 1} \in g\left( {L_{k + 1} (p)} \right)} {\left\{ {\left( {1 - \prod\limits_{i = 1}^{k + 1} \prod\limits_{j = i}^{k + 1} \left( {1 - \left( {1 - (1 - \eta_{i} )^{{nw_{i} }} } \right)^{p} \left( {1 - (1 - \eta_{j} )^{{nw_{j} }} } \right)^{q} } \right)} \right) \cdot \left( {p_{1} p_{2} \ldots p_{k + 1} } \right)} \right\}} } \right)} \right)^{{\frac{1}{p + q}}} \\ & \quad = g^{ - 1} \left( {\bigcup\limits_{ \eta_{1} \in g(L_{1} (p)),\eta_{2} \in g(L_{2} (p)), \ldots , \eta_{k} \in g(L_{k} (p)),\eta_{k + 1} \in g\left( {L_{k + 1} (p)} \right) } {\left\{ {\left( {1 - \left( {1 - \left( {1 - \prod\limits_{i = 1}^{k + 1} \prod\limits_{j = i}^{k + 1} \left( {1 - \left( {1 - (1 - \eta_{i} )^{{nw_{i} }} } \right)^{p} \left( {1 - (1 - \eta_{j} )^{{nw_{j} }} } \right)^{q} } \right)} \right)} \right)^{{\frac{2}{(k + 1)(k + 2)}}} } \right)^{{\frac{1}{p + q}}} \cdot \left( {p_{1} p_{2} \ldots p_{k + 1} } \right)} \right\}} } \right) \\ & \quad = g^{ - 1} \left( {\bigcup\limits_{ \eta_{1} \in g(L_{1} (p)),\eta_{2} \in g(L_{2} (p)), \ldots , \eta_{k} \in g(L_{k} (p)),\eta_{k + 1} \in g\left( {L_{k + 1} (p)} \right)} {\left\{ {\left( {1 - \left( {\prod\limits_{i = 1}^{k + 1} \prod\limits_{j = i}^{k + 1} \left( {1 - \left( {1 - (1 - \eta_{i} )^{{nw_{i} }} } \right)^{p} \left( {1 - (1 - \eta_{j} )^{{nw_{j} }} } \right)^{q} } \right)} \right)^{{\frac{2}{(k + 1)(k + 2)}}} } \right)^{{\frac{1}{p + q}}} \cdot \left( {p_{1} p_{2} \ldots p_{k + 1} } \right)} \right\}} } \right) \\ \end{aligned} . $$

    Thus, when n = k + 1, Theorem 3 is true.

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Feng, X., Zhang, Q. & Jin, L. Aggregation of pragmatic operators to support probabilistic linguistic multi-criteria group decision-making problems. Soft Comput 24, 7735–7755 (2020). https://doi.org/10.1007/s00500-019-04393-6

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