The degree of credibility of the fuzzy assessment value demonstrates its significance and necessity in the fuzzy decision making problem. The fuzzy assessment values should be closely related to their credibility measures in order to increase the credibility levels and degrees of fuzzy assessment values. This will increase the abundance and the credibility of the assessment information. As a new extension of the intuitionistic fuzzy concept, this study suggests the idea of an intuitionistic fuzzy credibility number (IFCN). So, based on Dombi norms, we proposed some new operational laws for intuitionistic fuzzy credibility numbers. Different intuitionistic fuzzy credibility aggregation operators are defined using Dombi t-norm and t-conorm operations. i.e., intuitionistic fuzzy credibility Dombi weighted averaging (IFCDWA), intuitionistic fuzzy credibility Dombi ordered weighted averaging (IFCDOWA), intuitionistic fuzzy credibility Dombi hybrid weighted averaging (IFCDHWA) operators. Next, we defined multiple criteria group decisions (MCGDM) approach. To ensure that their results are reliable and applicable, we also gave an example of railway train selection and discussed comparative result analysis.
Citation: Muhammad Qiyas, Neelam Khan, Muhammad Naeem, Saleem Abdullah. Intuitionistic fuzzy credibility Dombi aggregation operators and their application of railway train selection in Pakistan[J]. AIMS Mathematics, 2023, 8(3): 6520-6542. doi: 10.3934/math.2023329
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The degree of credibility of the fuzzy assessment value demonstrates its significance and necessity in the fuzzy decision making problem. The fuzzy assessment values should be closely related to their credibility measures in order to increase the credibility levels and degrees of fuzzy assessment values. This will increase the abundance and the credibility of the assessment information. As a new extension of the intuitionistic fuzzy concept, this study suggests the idea of an intuitionistic fuzzy credibility number (IFCN). So, based on Dombi norms, we proposed some new operational laws for intuitionistic fuzzy credibility numbers. Different intuitionistic fuzzy credibility aggregation operators are defined using Dombi t-norm and t-conorm operations. i.e., intuitionistic fuzzy credibility Dombi weighted averaging (IFCDWA), intuitionistic fuzzy credibility Dombi ordered weighted averaging (IFCDOWA), intuitionistic fuzzy credibility Dombi hybrid weighted averaging (IFCDHWA) operators. Next, we defined multiple criteria group decisions (MCGDM) approach. To ensure that their results are reliable and applicable, we also gave an example of railway train selection and discussed comparative result analysis.
We begin with the following definitions of notations:
N={1,2,3,⋯} and N0:=N∪{0}. |
Also, as usual, R denotes the set of real numbers and C denotes the set of complex numbers.
The two variable Laguerre polynomials Ln(u,v) [1] are defined by the Taylor expansion about τ=0 (also popularly known as generating function) as follows:
∞∑p=0Lp(u,v)τpp!=evτC0(uτ), |
where is the 0-th order Tricomi function [19] given by
C0(u)=∞∑p=0(−1)pup(p!)2 |
and has the series representation
Lp(u,v)=p∑s=0p!(−1)svp−sus(p−s)!(s!)2. |
The classical Euler polynomials Ep(u), Genocchi polynomials Gp(u) and the Bernoulli polynomials Bp(u) are usually defined by the generating functions (see, for details and further work, [1,2,4,5,6,7,9,11,12,20]):
∞∑p=0Ep(u)τpp!=2eτ+1euτ(|τ|<π), |
∞∑p=0Gp(u)τpp!=2τeτ+1euτ(|τ|<π) |
and
∞∑p=0Bp(u)τpp!=τeτ−1euτ(|τ|<2π). |
The Daehee polynomials, recently originally defined by Kim et al. [9], are defined as follows
∞∑p=0Dp(u)τpp!=log(1+τ)τ(1+τ)u, | (1.1) |
where, for u=0, Dp(0)=Dp stands for Daehee numbers given by
∞∑p=0Dpτpp!=log(1+τ)τ. | (1.2) |
Due to Kim et al.'s idea [9], Jang et al. [3] gave the partially degenarate Genocchi polynomials as follows:
2log(1+τλ)1λeτ+1euτ=∞∑p=0Gp,λ(u)τpp!, | (1.3) |
which, for the case u=0, yields the partially degenerate Genocchi numbers Gn,λ:=Gn,λ(0).
Pathan et al. [17] considered the generalization of Hermite-Bernoulli polynomials of two variables HB(α)p(u,v) as follows
(τeτ−1)αeuτ+vτ2=∞∑p=0HB(α)p(u,v)τpp!. | (1.4) |
On taking α=1 in (1.4) yields a well known result of [2,p. 386 (1.6)] given by
(τeτ−1)euτ+vτ2=∞∑p=0HBp(u,v)τpp!. | (1.5) |
The two variable Laguerre-Euler polynomials (see [7,8]) are defined as
∞∑p=0LEp(u,v)τpp!=2eτ+1evτC0(uτ). | (1.6) |
The alternating sum Tk(p), where k∈N0, (see [14]) is given as
Tk(p)=p∑j=0(−1)jjk |
and possess the generating function
∞∑r=0Tk(p)τrr!=1−(−eτ)(p+1)eτ+1. | (1.7) |
The idea of degenerate numbers and polynomials found existence with the study related to Bernoulli and Euler numbers and polynomials. Lately, many researchers have begun to study the degenerate versions of the classical and special polynomials (see [3,10,11,12,13,14,15,16,18], for a systematic work). Influenced by their works, we introduce partially degenerate Laguerre-Genocchi polynomials and also a new generalization of partially degenerate Laguerre-Genocchi polynomials and then give some of their applications. We also derive some implicit summation formula and general symmetry identities.
Let λ,τ∈C with |τλ|≤1 and τλ≠−1. We introduce and investigate the partially degenerate Laguerre-Genocchi polynomials as follows:
∞∑p=0LGp,λ(u,v)τpp!=2log(1+λτ)1λeτ+1evτC0(uτ). | (2.1) |
In particular, when λ→0, LGp,λ(u,v)→LGp(u,v) and they have the closed form given as
LGp,λ(u,v)=p∑q=0(pq)Gq,λLp−q(u,v). |
Clearly, u=0 in (2.1) gives LGp,λ(0,0):=Gp,λ that stands for the partially degenerate Genocchi polynomials [3].
Theorem 1. For p∈No, the undermentioned relation holds:
LGp,λ(u,v)=p∑q=0(pq+1)q!(−λ)qLGp−q−1(u,v). | (2.2) |
Proof. With the help of (2.1), one can write
∞∑p=0LGp,λ(u,v)τpp!=2log(1+λτ)1λeτ+1evτC0(uτ)=τ{∞∑q=0(−1)qq+1(λτ)q}{∞∑p=0LGp(u,v)τpp!}=∞∑p=0{p∑q=0(pq)(−λ)qq+1q!LGp−q(u,v)}τp+1p!, |
where, LGp−q(u,v) are the Laguerre-Genocchi polynomials (see [8]). Finally, the assertion easily follows by equating the coefficients τpp!.
Theorem 2. For p∈No, the undermentioned relation holds:
LGp+1,λ(u,v)=p∑q=0(pq)λq(p+1)LGp−q+1(u,v)Dq. | (2.3) |
Proof. We first consider
I1=1τ2log(1+λτ)1λeτ+1evτC0(uτ)={∞∑q=0Dq(λτ)qq!}{∞∑p=0LGp(u,v)τpp!}=∞∑p=1{p∑q=0(pq)(λ)qDqLGp−q(u,v)}τpp!. |
Next we have,
I2=1τ2log(1+λτ)1λeτ+1evτCo(uτ)=1τ∞∑p=0LGp,λ(u,v)τpp!=∞∑p=0LGp+1,λ(u,v)p+1τpp!. |
Since I1=I2, we conclude the assertion (2.3) of Theorem 2.
Theorem 3. For p∈N0, the undermentioned relation holds:
LGp,λ(u,v)=pp−1∑q=0(p−1q)(λ)qLEp−q−1(u,v)Dq. | (2.4) |
Proof. With the help of (2.1), one can write
∞∑p=0LGp,λ(x,y)τpp!={τlog(1+λτ)λτ}{2eτ+1evτC0(uτ)}=τ{∞∑q=0Dq(λτ)qq!}{∞∑p=0LEp(u,v)τpp!}=∞∑p=0{p∑q=0(pq)(λ)qDqLEp−q(u,v)}τp+1p!. |
Finally, the assertion (2.4) straightforwardly follows by equating the coefficients of same powers of τ above.
Theorem 4. For p∈No, the following relation holds:
LGp,λ(u,v+1)=p∑q=0(pq)LGp−q,λ(u,v). | (2.5) |
Proof. Using (2.1), we find
∞∑p=0{LGp,λ(u,v+1)−LGp,λ(u,v)}τpp!=2log(1+λτ)1λeτ+1×e(v+1)τC0(uτ)−2log(1+λτ)1λeτ+1evτC0(uτ)=∞∑p=0LGp,λ(u,v)τpp!∞∑q=0τqq!−∞∑p=0LGp,λ(u,v)τpp!=∞∑p=0{p∑q=0(pq)LGp−q,λ(u,v)−LGp,λ(u,v)}τpp!. |
Hence, the assertion (2.5) straightforwardly follows by equating the coefficients of τp above.
Theorem 5. For p∈No, the undermentioned relation holds:
LGp,λ(u,v)=p∑q=0q∑l=0(pq)(ql)Gp−qDq−lλq−lLl(u,v). | (2.6) |
Proof. Since
∞∑p=0LGp,λ(u,v)τpp!=2log(1+λτ)1λeτ+1evτC0(uτ)={2τeτ+1}{2log(1+λτ)λτ}evτC0(uτ)={∞∑p=0Gpτpp!}{∞∑q=0Dq(λτ)qq!}{∞∑l=0Ll(u,v)τll!}, |
we have
∞∑p=0LGp,λ(u,v)τpp!=∞∑p=0{p∑q=0q∑l=0(pq)(ql)Gp−qDq−lλq−lLl(u,v)}τpp!. |
We thus complete the proof of Theorem 5.
Theorem 6. (Multiplication formula). For p∈No, the undermentioned relation holds:
LGp,λ(u,v)=fp−1f−1∑a=0LGp,λf(u,v+af). | (2.7) |
Proof. With the help of (2.1), we obtain
∞∑p=0LGp,λ(u,v)τpp!=2log(1+λτ)1λeτ+1evτC0(uτ)=2log(1+λτ)1λeτ+1C0(uτ)f−1∑a=0e(a+v)τ=∞∑p=0{fp−1f−1∑a=0LGp,λf(u,v+af)}τpp!. |
Thus, the result in (2.7) straightforwardly follows by comparing the coefficients of τp above.
Consider a Dirichlet character χ and let d(d∈N) be the conductor connected with it such that d≡1(mod2) (see [22]). Now we present a generalization of partially degenerate Laguerre-Genocchi polynomials attached to χ as follows:
∞∑p=0LGp,χ,λ(u,v)τpp!=2log(1+λτ)1λefτ+1f−1∑a=0(−1)aχ(a)e(v+a)τC0(uτ). | (3.1) |
Here, Gp,χ,λ=LGp,χ,λ(0,0) are in fact, the generalized partially degenerate Genocchi numbers attached to the Drichlet character χ. We also notice that
limλ→0v=0 LGp,χ,λ(u,v)=Gp,χ(u), |
is the familiar looking generalized Genocchi polynomial (see [20]).
Theorem 7. For p∈N0, the following relation holds:
LGp,χ,λ(u,v)=p∑q=0(pq)λqDqLGp−q,χ(u,v). | (3.2) |
Proof. In view of (3.1), we can write
∞∑p=0LGp,χ,λ(u,v)τpp!=2log(1+λτ)1λefτ+1f−1∑a=0(−1)aχ(a)e(v+a)τC0(uτ) |
={log(1+λτ)λτ}{2τefτ+1f−1∑a=0(−1)aχ(a)e(v+a)τC0(uτ)} |
={∞∑q=0Dqλqτqq!}{∞∑p=0LGp,χ(u,v)τpp!}. |
Finally, the assertion (3.2) of Theorem 7 can be achieved by equating the coefficients of same powers of τ.
Theorem 8. The undermentioned formula holds true:
LGp,χ,λ(u,v)=fp−1f−1∑a=0(−1)aχ(a)LGp,λf(u,a+vf). | (3.3) |
Proof. We first evaluate
∞∑p=0LGp,χ,λ(u,v)τpp!=2log(1+λτ)1λefτ+1f−1∑a=0(−1)aχ(a)e(v+a)τC0(uτ)=1ff−1∑a=0(−1)aχ(a)2log(1+λτ)fλefτ+1e(a+vf)fτC0(uτ)=∞∑p=0{fp−1f−1∑a=0(−1)aχ(a)LGp,λf(u,a+vf)}τpp!. |
Now, the Theorem 8 can easily be concluded by equating the coefficients τpp! above.
Using the result in (3.1) and with a similar approach used just as in above theorems, we provide some more theorems given below. The proofs are being omitted.
Theorem 9. The undermentioned formula holds true:
LGp,χ,λ(u,v)=p∑q=0Gp−q,χ,λ(v)(−u)qp!(q!)2(p−q)!. | (3.4) |
Theorem 10. The undermentioned formula holds true:
LGp,χ,λ(u,v)=p,l∑q=0Gp−q−l,χ,λ(v)q(−u)lp!(p−q−l)!(q)!(l!)2. | (3.5) |
Theorem 11. The undermentioned formula holds true:
LGl+h,λ(u,ν)=l,h∑p,n=0(lp)(hn)(u−v)p+nLGl+h−n−p,λ(u,v). | (4.1) |
Proof. On changing τ by τ+μ and rewriting (2.1), we evaluate
e−v(τ+μ)∞∑l,h=0LGl+h,λ(u,v)τlμhl!h!=2log(1+λ(τ+μ))1λeτ+μ+1Co(u(τ+μ)), |
which, upon replacing v by u and solving further, gives
e(u−v)(τ+μ)∞∑l,h=0LGl+h,λ(u,v)τlμhl!h!=∞∑l,h=0LGl+h,λ(u,ν)τlμhl!h!, |
and also
∞∑P=0(u−v)P(τ+u)PP!∞∑l,h=0LGl+h,λ(u,v)τlμhl!h!=∞∑l,h=0LGl+h,λ(u,ν)τlμhl!h!. | (4.2) |
Now applying the formula [21,p.52(2)]
∞∑P=0f(P)(u+v)PP!=∞∑p,q=0f(p+q)upp!vqq!, |
in conjunction with (4.2), it becomes
∞∑p,n=0(u−v)p+nτpμnp!n!∞∑l,h=0LGl+h,λ(u,v)τlμhl!h!=∞∑l,h=0LGl+h,λ(u,ν)τlμhl!h!. | (4.3) |
Further, upon replacing l by l−p, h by h−n, and using the result in [21,p.100 (1)], in the left of (4.3), we obtain
∞∑p,n=0∞∑l,h=0(u−v)p+np!n!LGl+h−p−n,λ(u,v)τlμh(l−p)!(h−n)!=∞∑l,h=0LGl+h,λ(u,ν)τlμhl!h!. |
Finally, the required result can be concluded by equating the coefficients of the identical powers of τl and μh above.
Corollary 4.1. For h=0 in (4.1), we get
LGl,λ(u,ν)=l∑ρ=0(lρ)(u−v)pLGl−ρ,λ(u,v). |
Some identities of Genocchi polynomials for special values of the parameters u and ν in Theorem 11 can also be obtained. Now, using the result in (2.1) and with a similar approach, we provide some more theorems given below. The proofs are being omitted.
Theorem 12. The undermentioned formula holds good:
LGp,λ(u,v+μ)=p∑q=0(pq)μqLGp−q,λ(u,v) |
Theorem 13. The undermentioned implicit holds true:
∞∑p=0LGp,λ(u,v)τpp!=2log(1+λτ)1λeτ+1evτCo(uτ)=p∑q=0(pq)Gp−q,λLp(u,v) |
and
LGp,λ(u,v)=p∑q=0(pq)Gp−q,λ(u,v)Lp(u,v). |
Theorem 14. The undermentioned implicit summation formula holds:
LGp,λ(u,v+1)+LGp,λ(u,v)=2pp−1∑q=0(p−1q)(−λ)qq!q+1Lp−q−1(u,v). |
Theorem 15. The undermentioned formula holds true:
LGp,λ(u,v+1)=p∑q=0LGp−q,λ(u,v). |
Symmetry identities involving various polynomials have been discussed (e.g., [7,9,10,11,17]). As in above-cited work, here, in view of the generating functions (1.3) and (2.1), we obtain symmetry identities for the partially degenerate Laguerre-Genocchi polynomials LGn,λ(u,v).
Theorem 16. Let α,β∈Z and p∈N0, we have
p∑q=0(pq)βqαp−qLGp−q,λ(uβ,vβ)LGq,λ(uα,vα) |
=p∑q=0(pq)αqβp−qLGp−q,λ(uα,vα)LGq,λ(uβ,vβ). |
Proof. We first consider
g(τ)={2log(1+λ)βλ}(eατ+1){2log(1+λ)αλ}(eβτ+1)e(α+β)vτC0(uατ)C0(uβτ). |
Now we can have two series expansion of g(τ) in the following ways:
On one hand, we have
g(τ)=(∞∑p=0LGp,λ(uβ,vβ)(ατ)pp!)(∞∑q=0LGq,λ(uα,vα)(βτ)qq!)=∞∑p=0(p∑q=0(pq)βqαp−qLGp−q,λ(uβ,vβ)LGq,λ(uα,vα))τpp!. | (5.1) |
and on the other, we can write
g(τ)=(∞∑p=0LGp,λ(uα,vα)(βτ)pp!)(∞∑q=0LGq,λ(uβ,vβ)(ατ)qq!)=∞∑p=0(p∑q=0(pq)αqβp−qLGp−q,λ(uα,vα)LGq,λ(uβ,vβ))τpp!. | (5.2) |
Finally, the result easily follows by equating the coefficients of τp on the right-hand side of Eqs (5.1) and (5.2).
Theorem 17. Let α,β∈Z with p∈N0, Then,
p∑q=0(pq)βqαp−qα−1∑σ=0β−1∑ρ=0(−1)σ+ρLGp−q,λ(u,vβ+βασ+ρ)Gq,λ(zα) |
=p∑q=0(pq)αpβp−qβ−1∑σ=0α−1∑ρ=0(−1)σ+ρLGp−q,λ(u,vα+βασ+ρ)Gq,λ(zβ). |
Proof. Let
g(τ)={2log(1+λ)αλ}(eατ+1)2{2log(1+λ)βλ}(eβτ+1)2e(αβτ+1)2e(αβ)(v+z)τ[Cs0(uτ)]. |
Considering g(τ) in two forms. Firstly,
g(τ)={2log(1+λ)αλ}eατ+1eαβvτCo(uτ)(eαβτ+1eβτ+1)×{2log(1+λ)βλ}eβτ+1eαβzτ(eαβτ+1eατ+1) |
={2log(1+λ)αλ}eατ+1eαβvτC0(uτ)(α−1∑σ=0(−1)σeβτσ)×{2log(1+λ)βλ}eβτ+1eαβτzC0(uτ)(β−1∑ρ=0(−1)ρeατρ), | (5.3) |
Secondly,
g(τ)=∞∑p=0{p∑q=0(pq)βqαp−qα−1∑σ=0β−1∑ρ=0(−1)σ+ρLGp−q,λ(uα,vβ+βασ+ρ)Gq,λ(αz)}τpp!=∞∑p=0{p∑q=0(pq)αqβp−qα−1∑σ=0β−1∑ρ=0(−1)σ+ρLGσ−ρ,λ(u,vα+αβσ+ρ)Gq,λ(zβ)}τpp!. | (5.4) |
Finally, the result straightforwardly follows by equating the coefficients of τp in Eqs (5.3) and (5.4).
We now give the following two Theorems. We omit their proofs since they follow the same technique as in the Theorems 16 and 17.
Theorem 18. Let α,β∈Z and p∈N0, Then,
p∑q=0(pq)βqαp−qα−1∑σ=0β−1∑ρ=0(−1)σ+ρLGp−q,λ(u,vβ+βασ)Gq,λ(zα+αβρ)=p∑q=0(pq)αqβp−qβ−1∑σ=0α−1∑ρ=0(−1)σ+ρLGp−q,λ(u,vα+αβσ+ρ)LGq,λ(zβ+βαρ). |
Theorem 19. Let α,β∈Z and p∈N0, Then,
p∑q=0(pq)βqαp−qLGp−q,λ(uβ,vβ)q∑σ=0(qσ)Tσ(α−1)Gq−σ,λ(uα)=p∑q=0(pq)βp−qαqLGp−q,λ(uα,vα)q∑σ=0(qσ)Tσ(β−1)Gq−σ,λ(uβ). |
Motivated by importance and potential for applications in certain problems in number theory, combinatorics, classical and numerical analysis and other fields of applied mathematics, various special numbers and polynomials, and their variants and generalizations have been extensively investigated (for example, see the references here and those cited therein). The results presented here, being very general, can be specialized to yield a large number of identities involving known or new simpler numbers and polynomials. For example, the case u=0 of the results presented here give the corresponding ones for the generalized partially degenerate Genocchi polynomials [3].
The authors express their thanks to the anonymous reviewers for their valuable comments and suggestions, which help to improve the paper in the current form.
We declare that we have no conflict of interests.
[1] |
K. T. Atanassov, More on intuitionistic fuzzy sets, Fuzzy Set. Syst., 33 (1989), 37–45. https://doi.org/10.1016/0165-0114(89)90215-7 doi: 10.1016/0165-0114(89)90215-7
![]() |
[2] |
S. Ayouni, L. J. Menzli, F. Hajjej, M. Maddeh, S. Al-Otaibi, Fuzzy Vikor application for learning management systems evaluation in higher education, IJICTE, 17 (2021), 17–![]() |
[3] |
F. E. Boran, S. Genç, M. Kurt, D. Akay, A multi-criteria intuitionistic fuzzy group decision making for supplier selection with TOPSIS method, Expert Syst. Appl., 36 (2009), 11363–11368. https://doi.org/10.1016/j.eswa.2009.03.039 doi: 10.1016/j.eswa.2009.03.039
![]() |
[4] |
I. Beg, T. Rashid, Multi-criteria trapezoidal valued intuitionistic fuzzy decision making with Choquet integral based TOPSIS, Opsearch, 51 (2014), 98–129. https://doi.org/10.1007/s12597-013-0134-5 doi: 10.1007/s12597-013-0134-5
![]() |
[5] |
J. Dombi, A general class of fuzzy operators, the DeMorgan class of fuzzy operators and fuzziness measures induced by fuzzy operators, Fuzzy Set. Syst., 8 (1982), 149–163. https://doi.org/10.1016/0165-0114(82)90005-7 doi: 10.1016/0165-0114(82)90005-7
![]() |
[6] |
S. K. De, R. Biswas, A. R. Roy, An application of intuitionistic fuzzy sets in medical diagnosis, Fuzzy Set. Syst., 117 (2001), 209–213. https://doi.org/10.1016/S0165-0114(98)00235-8 doi: 10.1016/S0165-0114(98)00235-8
![]() |
[7] |
K. Guo, Q. Song, On the entropy for Atanassov's intuitionistic fuzzy sets: An interpretation from the perspective of amount of knowledge, Appl. Soft Comput., 24 (2014), 328–![]() |
[8] |
H. Garg, A new generalized Pythagorean fuzzy information aggregation using Einstein operations and its application to decision making, Int. J. Intell. Syst., 31 (2016), 886–920. https://doi.org/10.1002/int.21809 doi: 10.1002/int.21809
![]() |
[9] | C. C. Hung, L. H. Chen, A fuzzy TOPSIS decision making model with entropy weight under intuitionistic fuzzy environment, Proceedings of the international multiconference of engineers and computer scientists, 1 (2009). |
[10] |
G. Q. Huang, L. M. Xiao, G. B. Zhang, Assessment and prioritization method of key engineering characteristics for complex products based on cloud rough numbers, Adv. Eng. Inform., 49 (2021), 101309. https://doi.org/10.1016/j.aei.2021.101309 doi: 10.1016/j.aei.2021.101309
![]() |
[11] |
A. Hussain, A. Alsanad, Novel Dombi aggregation operators in spherical cubic fuzzy information with applications in multiple attribute decision-making, Math. Probl. Eng., 2021 (2021), 9921553. https://doi.org/10.1155/2021/9921553 doi: 10.1155/2021/9921553
![]() |
[12] |
G. Q. Huang, L. M. Xiao, W. Pedrycz, D. Pamucar, G. B. Zhang, L. Martínez, Design alternative assessment and selection: A novel Z-cloud rough number-based BWM-MABAC model, Inform. Sci., 603 (2022), 149–189. https://doi.org/10.1016/j.ins.2022.04.040 doi: 10.1016/j.ins.2022.04.040
![]() |
[13] | G. Q. Huang, L. M. Xiao, W. Pedrycz, G. B. Zhang, L. Martinez, Failure mode and effect analysis using T-spherical fuzzy maximizing deviation and combined comparison solution methods, IEEE Trans. Reliab., 2022, 1–22. https://doi.org/10.1109/TR.2022.3194057 |
[14] |
D. Kumar, Analysis of issues of generic medicine supply chain using fuzzy AHP: A Pilot study of Indian public drug distribution scheme, Int. J. Pharm. Healthcare Mark., 15 (2021), 18–42. https://doi.org/10.1108/IJPHM-12-2019-0078 doi: 10.1108/IJPHM-12-2019-0078
![]() |
[15] |
D. F. Li, Multiattribute decision making models and methods using intuitionistic fuzzy sets, J. Comput. Syst. Sci., 70 (2005), 73–85. https://doi.org/10.1016/j.jcss.2004.06.002 doi: 10.1016/j.jcss.2004.06.002
![]() |
[16] |
P. D. Liu, J. L. Liu, S.M. Chen, Some intuitionistic fuzzy Dombi Bonferroni mean operators and their application to multi-attribute group decision making, J. Oper. Res. Soc., 69 (2018), 1–24. https://doi.org/10.1057/s41274-017-0190-y doi: 10.1057/s41274-017-0190-y
![]() |
[17] |
J. H. Park, Intuitionistic fuzzy metric spaces, Chaos, Soliton. Fract., 22 (2004), 1039–1046. https://doi.org/10.1016/j.chaos.2004.02.051 doi: 10.1016/j.chaos.2004.02.051
![]() |
[18] |
M. Qiyas, T. Madrar, S. Khan, S. Abdullah, T. Botmart, A. Jirawattanapaint, Decision support system based on fuzzy credibility Dombi aggregation operators and modified TOPSIS method, AIMS Mathematics, 7 (2022), 19057–19082. https://doi.org/10.3934/math.20221047 doi: 10.3934/math.20221047
![]() |
[19] | M. Qiyas, M. Yahya, S. Abdullah, N. Khan, M. Naeem, Extended GRA method for multi-criteria group decision making problem based on fuzzy credibility geometric aggregation operator, 2022. Available from: https://doi.org/10.21203/rs.3.rs-1419758/v1. |
[20] |
E. Szmidt, J. Kacprzyk, Entropy for intuitionistic fuzzy sets, Fuzzy Set. Syst., 118 (2001), 467–477. https://doi.org/10.1016/S0165-0114(98)00402-3 doi: 10.1016/S0165-0114(98)00402-3
![]() |
[21] |
Y. Sun, J. S. Mi, J. K. Chen, W. Liu, A new fuzzy multi-attribute group decision-making method with generalized maximal consistent block and its application in emergency management, Knowl.-Based Syst., 215 (2021), 106594. https://doi.org/10.1016/j.knosys.2020.106594 doi: 10.1016/j.knosys.2020.106594
![]() |
[22] |
Y. M. Wang, H. Y. Yang, K. Y. Qin, The consistency between cross-entropy and distance measures in fuzzy sets, Symmetry, 11 (2019), 386. https://doi.org/10.3390/sym11030386 doi: 10.3390/sym11030386
![]() |
[23] |
Z. S. Xu, An integrated model-based interactive approach to FMAGDM with incomplete preference information, Fuzzy Optim. Decis. Making, 9 (2010), 333–![]() |
[24] |
L. M. Xiao, G. Q. Huang, W. Pedrycz, D. Pamucar, L. Martínez, G. B. Zhang, A q-rung orthopair fuzzy decision-making model with new score function and best-worst method for manufacturer selection, Inform. Sci., 608 (2022), 153–177. https://doi.org/10.1016/j.ins.2022.06.061 doi: 10.1016/j.ins.2022.06.061
![]() |
[25] |
Z. L. Yue, An extended TOPSIS for determining weights of decision makers with interval numbers, Knowl.-Based Syst., 24 (2011), 146–153. https://doi.org/10.1016/j.knosys.2010.07.014 doi: 10.1016/j.knosys.2010.07.014
![]() |
[26] |
L. M. Xiao, G. Q. Huang, G. B. Zhang, An integrated risk assessment method using Z-fuzzy clouds and generalized TODIM, Qual. Reliab. Eng. Int., 38 (2022), 1909–1943. https://doi.org/10.1002/qre.3062 doi: 10.1002/qre.3062
![]() |
[27] |
E. Yadegaridehkordi, M. Hourmand, M. Nilashi, E. Alsolami, S. Samad, M. Mahmoud, et al., Assessment of sustainability indicators for green building manufacturing using fuzzy multi-criteria decision making approach, J. Cleaner Prod., 277 (2020), 122905. https://doi.org/10.1016/j.jclepro.2020.122905 doi: 10.1016/j.jclepro.2020.122905
![]() |
[28] | M. Yahya, S. Abdullah, M. Qiyas, Analysis of medical diagnosis based on fuzzy credibility Dombi Bonferroni mean operator, J. Ambient Intell. Human. Comput., 2022. https://doi.org/10.1007/s12652-022-04203-2 |
[29] |
M. Yahya, S. Abdullah, A. O. Almagrabi, T. Botmart, Analysis of S-box based on image encryption application using complex fuzzy credibility Frank aggregation operators, IEEE Access, 10 (2022), 88858–88871. https://doi.org/10.1109/ACCESS.2022.3197882 doi: 10.1109/ACCESS.2022.3197882
![]() |
[30] |
J. Ye, J. M. Song, S. G. Du, R. Yong, Weighted aggregation operators of fuzzy credibility numbers and their decision-making approach for slope design schemes, Comp. Appl. Math., 40 (2021), 155. https://doi.org/10.1007/s40314-021-01539-x doi: 10.1007/s40314-021-01539-x
![]() |
[31] |
L. A. Zadeh, Fuzzy sets, Information and control, J. Symbolic Logic, 8 (1965), 338– |
[32] |
H. J. Zimmermann, Fuzzy set theory, WIREs Comp. Stats., 2 (2010), 317– |
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