Research article Special Issues

Pythagorean fuzzy N-Soft PROMETHEE approach: A new framework for group decision making

  • The use of Pythagorean fuzzy N-soft sets (PFNSs) enables the examination of belongingness and non-belongingness of membership degrees, as well as their combinations with N-grading, in the unpredictable nature of individuals. This research aims to enhance our understanding of a popular multi-criteria group decision making (MCGDM) technique, Preference Ranking Organization Method for Enrichment of Evaluations, under the PFNS environment, aiding in making effective decisions for real-life problems, as fuzzy set theory is directly relevant to real-life applications. The PROMETHEE technique's main principle is to calculate the inflow and outflow streams of alternatives based on the deviation of their score degrees, ultimately providing partial and complete rankings of the given options. To capture the uncertainty of human nature, which demands both the association and disassociation of the considered criteria and provision of N-grading, the PFNS PROMETHEE technique is introduced in this research article. First, an Analytic Hierarchy Process AHP is used to check the feasibility of the standard weights of the criteria. The article then explains the detailed method of the fuzzy N-soft PROMETHEE technique to rank alternatives, with all the steps presented in an extensive flowchart for better understanding of the methodology. Furthermore, the practicality and viability of the proposed technique are demonstrated through an example of selecting the best chemical element in cloud seeding, where the most suitable choice is identified using an outranking directed graph. The credibility of the PFNS PROMETHEE technique is assessed by comparison with an existing method. Finally, the proposed technique's strengths and weaknesses are discussed to demonstrate its efficiency and drawbacks.

    Citation: Muhammad Akram, Maheen Sultan, Arooj Adeel, Mohammed M. Ali Al-Shamiri. Pythagorean fuzzy N-Soft PROMETHEE approach: A new framework for group decision making[J]. AIMS Mathematics, 2023, 8(8): 17354-17380. doi: 10.3934/math.2023887

    Related Papers:

    [1] Yasmina Khiar, Esmeralda Mainar, Eduardo Royo-Amondarain, Beatriz Rubio . High relative accuracy for a Newton form of bivariate interpolation problems. AIMS Mathematics, 2025, 10(2): 3836-3847. doi: 10.3934/math.2025178
    [2] Chih-Hung Chang, Ya-Chu Yang, Ferhat Şah . Reversibility of linear cellular automata with intermediate boundary condition. AIMS Mathematics, 2024, 9(3): 7645-7661. doi: 10.3934/math.2024371
    [3] Yongge Tian . Miscellaneous reverse order laws and their equivalent facts for generalized inverses of a triple matrix product. AIMS Mathematics, 2021, 6(12): 13845-13886. doi: 10.3934/math.2021803
    [4] Yang Chen, Kezheng Zuo, Zhimei Fu . New characterizations of the generalized Moore-Penrose inverse of matrices. AIMS Mathematics, 2022, 7(3): 4359-4375. doi: 10.3934/math.2022242
    [5] Pattrawut Chansangiam, Arnon Ploymukda . Riccati equation and metric geometric means of positive semidefinite matrices involving semi-tensor products. AIMS Mathematics, 2023, 8(10): 23519-23533. doi: 10.3934/math.20231195
    [6] Zongcheng Li, Jin Li . Linear barycentric rational collocation method for solving a class of generalized Boussinesq equations. AIMS Mathematics, 2023, 8(8): 18141-18162. doi: 10.3934/math.2023921
    [7] Maolin Cheng, Bin Liu . A novel method for calculating the contribution rates of economic growth factors. AIMS Mathematics, 2023, 8(8): 18339-18353. doi: 10.3934/math.2023932
    [8] Wenyue Feng, Hailong Zhu . The orthogonal reflection method for the numerical solution of linear systems. AIMS Mathematics, 2025, 10(6): 12888-12899. doi: 10.3934/math.2025579
    [9] Junsheng Zhang, Lihua Hao, Tengyun Jiao, Lusong Que, Mingquan Wang . Mathematical morphology approach to internal defect analysis of A356 aluminum alloy wheel hubs. AIMS Mathematics, 2020, 5(4): 3256-3273. doi: 10.3934/math.2020209
    [10] Sizhong Zhou, Quanru Pan . The existence of subdigraphs with orthogonal factorizations in digraphs. AIMS Mathematics, 2021, 6(2): 1223-1233. doi: 10.3934/math.2021075
  • The use of Pythagorean fuzzy N-soft sets (PFNSs) enables the examination of belongingness and non-belongingness of membership degrees, as well as their combinations with N-grading, in the unpredictable nature of individuals. This research aims to enhance our understanding of a popular multi-criteria group decision making (MCGDM) technique, Preference Ranking Organization Method for Enrichment of Evaluations, under the PFNS environment, aiding in making effective decisions for real-life problems, as fuzzy set theory is directly relevant to real-life applications. The PROMETHEE technique's main principle is to calculate the inflow and outflow streams of alternatives based on the deviation of their score degrees, ultimately providing partial and complete rankings of the given options. To capture the uncertainty of human nature, which demands both the association and disassociation of the considered criteria and provision of N-grading, the PFNS PROMETHEE technique is introduced in this research article. First, an Analytic Hierarchy Process AHP is used to check the feasibility of the standard weights of the criteria. The article then explains the detailed method of the fuzzy N-soft PROMETHEE technique to rank alternatives, with all the steps presented in an extensive flowchart for better understanding of the methodology. Furthermore, the practicality and viability of the proposed technique are demonstrated through an example of selecting the best chemical element in cloud seeding, where the most suitable choice is identified using an outranking directed graph. The credibility of the PFNS PROMETHEE technique is assessed by comparison with an existing method. Finally, the proposed technique's strengths and weaknesses are discussed to demonstrate its efficiency and drawbacks.



    Throughout this article, Cm×n denotes the collection of all m×n matrices over the field of complex numbers, A denotes the conjugate transpose of ACm×n, r(A) denotes the rank of ACm×n, R(A) denotes the range of ACm×n, Im denotes the identity matrix of order m, and [A,B] denotes a row block matrix consisting of ACm×n and BCm×p. The Moore-Penrose generalized inverse of ACm×n, denoted by A, is the unique matrix XCn×m satisfying the four Penrose equations

    (1) AXA=A,  (2) XAX=X,  (3) (AX)=AX,  (4) (XA)=XA.

    Further, we denote by

    PA=AA,  EA=ImAA (1.1)

    the two orthogonal projectors induced from ACm×n. For more detailed information regarding generalized inverses of matrices, we refer the reader to [2,3,4].

    Recall that the well-known Kronecker product of any two matrices A=(aij)Cm×n and B=(bij)Cp×q is defined to be

    AB=(aijB)=[a11Ba12Ba1nBa21Ba22Ba2nBam1Bam2BamnB]Cmp×nq.

    The Kronecker product, named after German mathematician Leopold Kronecker, was classified to be a special kind of matrix operation, which has been regarded as an important matrix operation and mathematical technique. This product has wide applications in system theory, matrix calculus, matrix equations, system identification and more (cf. [1,5,6,7,8,9,10,11,12,13,14,16,18,19,20,21,23,24,25,27,28,33,34]). It has been known that the matrices operations based on Kronecker products have a series of rich and good structures and properties, and thus they have many significant applications in the research areas of both theoretical and applied mathematics. In fact, mathematicians established a variety of useful formulas and facts related to the products and used them to deal with various concrete scientific computing problems. Specifically, the basic facts on Kronecker products of matrices in the following lemma were highly appraised and recognized (cf. [15,17,21,32,34]).

    Fact 1.1. Let ACm×n, BCp×q, CCn×s, and DCq×t. Then, the following equalities hold:

          (AB)(CD)=(AC)(BD), (1.2)
    (AB)=AB,   (AB)=AB, (1.3)
    PAB=PAPB,      r(AB)=r(A)r(B). (1.4)

    In addition, the Kronecker product of matrices has a rich variety of algebraic operation properties. For example, one of the most important features is that the product A1A2 can be factorized as certain ordinary products of matrices:

    A1A2=(A1Im2)(In1A2)=(Im1A2)(A1In2) (1.5)

    for any A1Cm1×n1 and A2Cm2×n2, and the triple Kronecker product A1A2A3 can be written as

    A1A2A3=(A1Im2Im3)(In1A2Im3)(In1In2A3), (1.6)
    A1A2A3=(In1A2Im3)(In1(In1In2A3)(A1Im2Im3), (1.7)
    A1A2A3=(Im1Im2A3)(A1In2In3)(Im1A2In3) (1.8)

    for any A1Cm1×n1, A2Cm2×n2 and A3Cm3×n3, where the five matrices in the parentheses on the right hand sides of (1.5)–(1.8) are usually called the dilation expressions of the given three matrices A1, A2 and A3, and the four equalities in (1.5)–(1.8) are called the dilation factorizations of the Kronecker products A1A2 and A1A2A3, respectively. A common feature of the four matrix equalities in (1.5)–(1.8) is that they factorize Kronecker products of any two or three matrices into certain ordinary products of the dilation expressions of A1, A2 and A3. Particularly, a noticeable fact we have to point out is that the nine dilation expressions of matrices in (1.5)–(1.8) commute each other by the well-known mixed-product property in (1.2) when A1, A2 and A3 are all square matrices. It can further be imagined that there exists proper extension of the dilation factorizations to Kronecker products of multiple matrices. Although the dilation factorizations in (1.5)–(1.8) seem to be technically trivial in form, they can help deal with theoretical and computational issues regarding Kronecker products of two or three matrices through the ordinary addition and multiplication operations of matrices.

    In this article, we provide a new analysis of performances and properties of Kronecker products of matrices, as well as present a wide range of novel and explicit facts and results through the dilation factorizations described in (1.5)–(1.8) for the purpose of obtaining a deeper understanding and grasping of Kronecker products of matrices, including a number of analytical formulas for calculating ranks, dimensions, orthogonal projectors, and ranges of the dilation expressions of matrices and their algebraic operations.

    The remainder of article is organized as follows. In section two, we introduce some preliminary facts and results concerning ranks, ranges, and generalized inverses of matrices. In section three, we propose and prove a collection of useful equalities, inequalities, and formulas for calculating the ranks, dimensions, orthogonal projectors, and ranges associated with the Kronecker products A1A2 and A1A2A3 through the dilation expressions of A1, A2 and A3 and their operations. Conclusions and remarks are given in section four.

    One of the remarkable applications of generalized inverses of matrices is to establish various exact and analytical expansion formulas for calculating the ranks of partitioned matrices. As convenient and skillful tools, these matrix rank formulas can be used to deal with a wide variety of theoretical and computational issues in matrix theory and its applications (cf. [22]). In this section, we present a mixture of commonly used formulas and facts in relation to ranks of matrices and their consequences about the commutativity of two orthogonal projectors, which we shall use as analytical tools to approach miscellaneous formulas related to Kronecker products of matrices.

    Lemma 2.1. [22,29] Let ACm×n and BCm×k. Then, the following rank equalities

    r[A,B]=r(A)+r(EAB)=r(B)+r(EBA), (2.1)
    r[A,B]=r(A)+r(B)2r(AB)+r[PAPB,PBPA], (2.2)
    r[A,B]=r(A)+r(B)r(AB)+21r(PAPBPBPA), (2.3)
    r[A,B]=r(A)+r(B)r(AB)+r(P[A,B]PAPB+PAPB) (2.4)

    hold. Therefore,

    PAPB=PBPAP[A,B]=PA+PBPAPBr(EAB)=r(B)r(AB)r[A,B]=r(A)+r(B)r(AB)R(PAPB)=R(PBPA). (2.5)

    If PAPB=PBPA, PAPC=PCPA and PBPC=PCPB, then

    P[A,B,C]=PA+PB+PCPAPBPAPCPBPC+PAPBPC. (2.6)

    Lemma 2.2. [30] Let A,B and CCm×m be three idempotent matrices. Then, the following rank equality

    r[A,B,C]=r(A)+r(B)+r(C)r[AB,AC]r[BA,BC]r[CA,CB]   +r[AB,AC,BA,BC,CA,CB] (2.7)

    holds. As a special instance, if AB=BA, AC=CA and BC=CB, then

    r[A,B,C]=r(A)+r(B)+r(C)r[AB,AC]r[BA,BC]r[CA,CB]+r[AB,AC,BC]. (2.8)

    The formulas and facts in the above two lemmas belong to mathematical competencies and conceptions in ordinary linear algebra. Thus they can easily be understood and technically be utilized to establish and simplify matrix expressions and equalities consisting of matrices and their generalized inverses.

    We first establish a group of formulas and facts associated with the orthogonal projectors, ranks, dimensions, and ranges of the matrix product in (1.5).

    Theorem 3.1. Let A1Cm1×n1 and A2Cm2×n2, and denote by

    M1=A1Im2,  M2=Im1A2

    the two dilation expressions of A1 and A2, respectively. Then, we have the following results.

    (a) The following orthogonal projector equalities hold:

    PA1A2=PM1PM2=PM2PM1=PA1PA2. (3.1)

    (b) The following four rank equalities hold:

    r[A1Im2,Im1A2]=m1m2(m1r(A1))(m2r(A2)), (3.2)
    r[A1Im2,Im1EA2]=m1m2(m1r(A1))r(A2), (3.3)
    r[EA1Im2,Im1A2]=m1m2r(A1)(m2r(A2)), (3.4)
    r[EA1Im2,Im1EA2]=m1m2r(A1)r(A2), (3.5)

    and the following five dimension equalities hold:

    dim(R(M1)R(M2))=r(M1M2)=r(A1)r(A2), (3.6)
    dim(R(M1)R(M2))=r(M1EM2)=r(A1)(m2r(A2)), (3.7)
    dim(R(M1)R(M2))=r(EM1M2)=(m1r(A1))r(A2), (3.8)
    dim(R(M1)R(M2))=r(EM1EM2)=(m1r(A1))(m2r(A2)), (3.9)
    dim(R(M1)R(M2))+dim(R(M1)R(M2))+dim(R(M1)R(M2)) +dim(R(M1)R(M2))=m1m2. (3.10)

    (c) The following range equalities hold:

    R(M1)R(M2)=R(M1M2)=R(M2M1)=R(A1A2), (3.11)
    R(M1)R(M2)=R(M1EM2)=R(EM2M1)=R(A1EA2), (3.12)
    R(M1)R(M2)=R(EM1M2)=R(M2EM1)=R(EA1A2), (3.13)
    R(M1)R(M2)=R(EM1EM2)=R(EM2EM1)=R(EA1EA2), (3.14)
    (R(M1)R(M2))(R(M1)R(M2))(R(M1)R(M2))(R(M1)R(M2))=Cm1m2. (3.15)

    (d) The following orthogonal projector equalities hold:

    PR(M1)R(M2)=PM1PM2=PA1PA2, (3.16)
    PR(M1)R(M2)=PM1EM2=PA1EA2, (3.17)
    PR(M1)R(M2)=EM1PM2=EA1PA2, (3.18)
    PR(M1)R(M2)=EM1EM2=EA1EA2, (3.19)
    PR(M1)R(M2)+PR(M1)R(M2)+PR(M1)R(M2)+PR(M1)R(M2)=Im1m2. (3.20)

    (e) The following orthogonal projector equalities hold:

    P[A1Im2,Im1A2]=PA1Im2+Im1PA2PA1PA2=Im1m2EA1EA2, (3.21)
    P[A1Im2,Im1EA2]=PA1Im2+Im1EA2PA1EA2=Im1m2EA1PA2, (3.22)
    P[EA1Im2,Im1A2]=EA1Im2+Im1PA2EA1PA2=Im1m2PA1EA2, (3.23)
    P[EA1Im2,Im1EA2]=EA1Im2+Im1EA2EA1EA2=Im1m2PA1PA2. (3.24)

    Proof. It can be seen from (1.2) and (1.4) that

    PM1PM2=(A1Im2)(A1Im2)(Im1A2)(Im1A2)=(A1Im2)(A1Im2)(Im1A2)(Im1A2)=(PA1Im2)(Im1PA2)=PA1PA2,PM2PM1=(Im1A2)(Im1A2)(A1Im2)(A1Im2)=(Im1A2)(Im1A2)(A1Im2)(A1Im2)=(Im1PA2)(PA1Im2)=PA1PA2,

    thus establishing (3.1).

    Applying (2.1) to [A1Im2,Im1A2] and then simplifying by (1.2)–(1.4) yields

    r[A1Im2,Im1A2]=r(A1Im2)+r((Im1m2(A1Im2)(A1Im2))(Im1A2))=r(A1Im2)+r((Im1m2(A1Im2)(A1Im2))(Im1A2))=r(A1Im2)+r((Im1m2(A1A1)Im2)(Im1A2))=m2r(A1)+r((Im1A1A1)Im2)(Im1A2))=m2r(A1)+r((Im1A1A1)A2))=m2r(A1)+r(Im1A1A1)r(A2)=m2r(A1)+(m1r(A1))r(A2)=m1m2(m1r(A1))(m2r(A2)),

    as required for (3.2). In addition, (3.2) can be directly established by applying (2.5) to the left hand side of (3.2). Equations (3.3)–(3.5) can be obtained by a similar approach. Subsequently by (3.2),

    dim(R(M1)R(M2))=r(M1)+r(M2)r[M1,M2]=r(A1)r(A2),

    as required for (3.6). Equations (3.7)–(3.9) can be established by a similar approach. Adding (3.7)–(3.9) leads to (3.10).

    The first two equalities in (3.11) follow from (3.6), and the last two range equalities follow from (3.1).

    Equations (3.12)–(3.14) can be established by a similar approach. Adding (3.11)–(3.14) and combining with (3.10) leads to (3.15).

    Equations (3.16)–(3.19) follow from (3.11)–(3.14). Adding (3.16)–(3.19) leads to (3.20).

    Under (3.1), we find from (2.5) that

    P[M1,M2]=PM1+PM2PM1PM2=PA1Im2+Im1PA2PA1PA2=Im1m2EA1EA2,

    as required for (3.21). Equations (3.22)–(3.24) can be established by a similar approach.

    Equation (3.2) was first shown in [7]; see also [27] for some extended forms of (3.2). Obviously, Theorem 3.1 reveals many performances and properties of Kronecker products of matrices, and it is no doubt that they can be used as analysis tools to deal with various matrix equalities composed of algebraic operations of Kronecker products of matrices. For example, applying the preceding results to the Kronecker sum and difference A1Im2±Im1A2 for two idempotent matrices A1 and A2, we obtain the following interesting consequences.

    Theorem 3.2. Let A1Cm1×m1 and A2Cm2×m2. Then, the following rank inequality

    r(A1Im2+Im1A2)m1r(A2)+m2r(A1)2r(A1)r(A2) (3.25)

    holds. If A1=A21 and A2=A22, then the following two rank equalities hold:

    r(A1Im2+Im1A2)=m1r(A2)+m2r(A1)r(A1)r(A2), (3.26)
    r(A1Im2Im1A2)=m1r(A2)+m2r(A1)2r(A1)r(A2). (3.27)

    Proof. Equation (3.25) follows from applying the following well-known rank inequality (cf. [22])

    r(A+B)r[AB]+r[A,B]r(A)r(B)

    and (2.1) to A1Im2+Im1A2. Specifically, if A1=A21 and A2=A22, then it is easy to verify that (A1Im2)2=A21Im2=A1Im2 and (Im1A2)2=Im1A22=Im1A2 under A21=A1 and A22=A2. In this case, applying the following two known rank formulas

    r(A+B)=r[ABB0]r(B)=r[BAA0]r(A),r(AB)=r[AB]+r[A,B]r(A)r(B),

    where A and B are two idempotent matrices of the same size (cf. [29,31]), to A1Im2±Im1A2 and then simplifying by (2.1) and (3.2) yields (3.26) and (3.27), respectively.

    Undoubtedly, the above two theorems reveal some essential relations among the dilation forms of two matrices by Kronecker products, which demonstrate that there still exist various concrete research topics on the Kronecker product of two matrices with analytical solutions that can be proposed and obtained. As a natural and useful generalization of the preceding formulas, we next give a diverse range of results related to the three-term Kronecker products of matrices in (1.6).

    Theorem 3.3. Let A1Cm1×n1,A2Cm2×n2 and A3Cm3×n3, and let

    X1=A1Im2Im3,  X2=Im1A2Im3,  X3=Im1Im2A3 (3.28)

    denote the three dilation expressions of A1, A2 and A3, respectively. Then, we have the following results.

    (a) The following three orthogonal projector equalities hold:

    PX1=PA1Im2Im3,  PX2=Im1PA2Im3,  PX3=Im1Im2PA3, (3.29)

    the following equalities hold:

    PX1PX2=PX2PX1=PA1PA2Im3, (3.30)
    PX1PX3=PX3PX1=PA1Im2PA3, (3.31)
    PX2PX3=PX3PX2=Im1PA2PA3, (3.32)

    and the equalities hold:

    PA1A2A3=PX1PX2PX3=PA1PA2PA3. (3.33)

    (b) The following eight rank equalities hold:

    r[A1Im2Im3,Im1A2Im3,Im1Im2A3]  =m1m2m3(m1r(A1))(m2r(A2))(m3r(A3)), (3.34)
    r[A1Im2Im3,Im1A2Im3,Im1Im2EA3]  =m1m2m3(m1r(A1))(m2r(A2))r(A3), (3.35)
    r[A1Im2Im3,Im1EA2Im3,Im1Im2A3]  =m1m2m3(m1r(A1))r(A2)(m3r(A3)), (3.36)
    r[EA1Im2Im3,Im1A2Im3,Im1Im2A3]  =m1m2m3r(A1)(m2r(A2))(m3r(A3)), (3.37)
    r[A1Im2Im3,Im1EA2Im3,Im1Im2EA3]  =m1m2m3(m1r(A1))r(A2)r(A3), (3.38)
    r[EA1Im2Im3,Im1A2Im3,Im1Im2EA3]  =m1m2m3r(A1)(m2r(A2))r(A3), (3.39)
    r[EA1Im2Im3,Im1EA2Im3,Im1Im2A3]  =m1m2m3r(A1)r(A2)(m3r(A3)), (3.40)
    r[EA1Im2Im3,Im1EA2Im3,Im1Im2EA3]=m1m2m3r(A1)r(A2)r(A3), (3.41)

    the following eight dimension equalities hold:

    dim(R(X1)R(X2)R(X3))=r(A1)r(A2)r(A3), (3.42)
    dim(R(X1)R(X2)R(X3))=r(A1)r(A2)(m3r(A3)), (3.43)
    dim(R(X1)R(X2)R(X3))=r(A1)(m2r(A2))r(A3), (3.44)
    dim(R(X1)R(X2)R(X3))=(m1r(A1))r(A2)r(A3), (3.45)
    dim(R(X1)R(X2)R(X3))=r(A1)(m2r(A2))(m3r(A3)), (3.46)
    dim(R(X1)R(X2)R(X3))=(m1r(A1))r(A2)(m3r(A3)), (3.47)
    dim(R(X1)R(X2)R(X3))=(m1r(A1))(m2r(A2))r(A3), (3.48)
    dim(R(X1)R(X2)R(X3))=(m1r(A1))(m2r(A2))(m3r(A3)), (3.49)

    and the following dimension equality holds:

    dim(R(X1)R(X2)R(X3))+dim(R(X1)R(X2)R(X3))  +dim(R(X1)R(X2)R(X3))+dim(R(X1)R(X2)R(X3))  +dim(R(X1)R(X2)R(X3))+dim(R(X1)R(X2)R(X3))  +dim(R(X1)R(X2)R(X3))+dim(R(X1)R(X2)R(X3)=m1m2m3. (3.50)

    (c) The following eight groups of range equalities hold:

    R(X1)R(X2)R(X3)=R(X1X2X3)=R(A1A2A3), (3.51)
    R(X1)R(X2)R(X3)=R(X1X2EX3)=R(A1A2EA3), (3.52)
    R(X1)R(X2)R(X3)=R(X1EX2X3)=R(A1EA2A3), (3.53)
    R(X1)R(X2)R(X3)=R(EX1X2X3)=R(EA1A2A3), (3.54)
    R(X1)R(X2)R(X3)=R(X1EX2EX3)=R(A1EA2EA3), (3.55)
    R(X1)R(X2)R(X3)=R(EX1X2EX3)=R(EA1A2EA3), (3.56)
    R(X1)R(X2)R(X3)=R(X1EX2X3)=R(EA1EA2A3), (3.57)
    R(X1)R(X2)R(X3)=R(EX1EX2EX3)=R(EA1EA2EA3), (3.58)

    and the following direct sum equality holds:

    (R(X1)R(X2)R(X3))(R(X1)R(X2)R(X3))(R(X1)R(X2)R(X3))(R(X1)R(X2)R(X3))(R(X1)R(X2)R(X3))(R(X1)R(X2)R(X3))(R(X1)R(X2)R(X3))(R(X1)R(X2)R(X3))=Cm1m2m3. (3.59)

    (d) The following eight orthogonal projector equalities hold:

    PR(X1)R(X2)R(X3)=PA1PA2PA3, (3.60)
    PR(X1)R(X2)R(X3)=PA1PA2EA3, (3.61)
    PR(X1)R(X2)R(X3)=PA1EA2PA3, (3.62)
    PR(X1)R(X2)R(X3)=EA1PA2PA3, (3.63)
    PR(X1)R(X2)R(X3)=PA1EA2EA3, (3.64)
    PR(X1)R(X2)R(X3)=EA1PA2EA3, (3.65)
    PR(X1)R(X2)R(X3)=EA1EA2PA3, (3.66)
    PR(X1)R(X2)R(X3)=EA1EA2EA3, (3.67)

    and the following orthogonal projector equality holds:

    PR(X1)R(X2)R(X3)+PR(X1)R(X2)R(X3)  +PR(X1)R(X2)R(X3)+PR(X1)R(X2)R(X3)  +PR(X1)R(X2)R(X3)+PR(X1)R(X2)R(X3)  +PR(X1)R(X2)R(X3)+PR(X1)R(X2)R(X3)=Im1m2m3. (3.68)

    (e) The following eight orthogonal projector equalities hold:

    P[A1Im2Im3,Im1A2Im3,Im1Im2A3]=Im1m2m3EA1EA2EA3, (3.69)
    P[A1Im2Im3,Im1A2Im3,Im1Im2EA3]=Im1m2m3EA1EA2PA3, (3.70)
    P[A1Im2Im3,Im1EA2Im3,Im1Im2A3]=Im1m2m3EA1PA2EA3, (3.71)
    P[EA1Im2Im3,Im1A2Im3,Im1Im2A3]=Im1m2m3PA1EA2EA3, (3.72)
    P[A1Im2Im3,Im1EA2Im3,Im1Im2EA3]=Im1m2m3EA1PA2PA3, (3.73)
    P[EA1Im2Im3,Im1A2Im3,Im1Im2EA3]=Im1m2m3PA1EA2PA3, (3.74)
    P[EA1Im2Im3,Im1EA2Im3,Im1Im2A3]=Im1m2m3PA1PA2EA3, (3.75)
    P[EA1Im2Im3,Im1EA2Im3,Im1Im2EA3]=Im1m2m3PA1PA2PA3. (3.76)

    Proof. By (1.1)–(1.3),

    PX1=(A1Im2Im3)(A1Im2Im3)=(A1Im2Im3)(A1Im2Im3)=(A1A1)Im2Im3=PA1Im2Im3,

    thus establishing the first equality in (3.29). The second and third equalities in (3.29) can be shown in a similar way. Also by (1.1)–(1.3),

    PA1A2A3=(A1A2A3)(A1A2A3)=(A1A2A3)(A1A2A3)=(A1A1)(A2A2)(A3A3)=PA1PA2PA3, (3.77)

    and by (1.2) and (3.29),

    PX1PX2PX3=(PA1Im2Im3)(Im1PA2Im3)(Im1Im2PA3)=PA1PA2PA3. (3.78)

    Combining (3.77) and (3.78) leads to (3.33).

    By (2.1), (1.2)–(1.4) and (3.2),

    r[A1Im2Im3,Im1A2Im3,Im1Im2A3]=r(A1Im2Im3)+r((Im1A1A1)[A2Im3,Im2A3])=m2m3r(A1)+r(Im1A1A1)r[A2Im3,Im2A3]=m2m3r(A1)+(m1r(A1))(m2m3(m2r(A2))(m3r(A3)))=m1m2m3(m1r(A1))(m2r(A2))(m3r(A3)),

    thus establishing (3.34). Equations (3.35)–(3.41) can be established in a similar way.

    By (3.11), we are able to obtain

    R(X1)R(X2)=R(X1X2)=R(X2X1)=R(A1A2Im3).

    Consequently,

    R(X1)R(X2)R(X3)=R(X1X2)R(X3)=R(X1X2X3)=R(A1A2A3),

    as required for (3.51). Equations (3.52)–(3.58) can be established in a similar way. Adding (3.51)–(3.58) leads to (3.59).

    Taking the dimensions of both sides of (3.51)–(3.58) and applying (1.4), we obtain (3.42)–(3.50).

    Equations (3.60)–(3.68) follow from (3.51)–(3.59).

    Equations (3.69)–(3.77) follow from (2.6) and (3.30)–(3.32).

    In addition to (3.28), we can construct the following three dilation expressions

    Y1=Im1A2A3,  Y2=A1Im2A3  and  Y3=A1A2Im3 (3.79)

    from any three matrices A1Cm1×n1,A2Cm2×n2 and A3Cm3×n3. Some concrete topics on rank equalities for the dilation expressions under vector situations were considered in [26]. Below, we give a sequence of results related to the three dilation expressions.

    Theorem 3.4. Let Y1, Y2 and Y3 be the same as given in (3.79). Then, we have the following results.

    (a) The following three projector equalities hold:

    PY1=Im1PA2PA3,  PY2=PA1Im2PA3  and  PY3=PA1PA2Im3. (3.80)

    (b) The following twelve matrix equalities hold:

    PY1PY2=PY2PY1=PY1PY3=PY3PY1=PY2PY3=PY3PY2=PY1PY2PY3=PY1PY3PY2=PY2PY1PY3=PY2PY3PY1=PY3PY1PY2=PY3PY2PY1=PA1PA2PA3. (3.81)

    (c) The following rank equality holds:

    r[Y1,Y2,Y3]=m1r(A2)r(A3)+m2r(A1)r(A3)+m3r(A1)r(A2)2r(A1)r(A2)r(A3). (3.82)

    (d) The following range equality holds:

    R(Y1)R(Y2)R(Y3)=R(A1A2A3). (3.83)

    (e) The following dimension equality holds:

    dim(R(Y1)R(Y2)R(Y3))=r(A1)r(A2)r(A3). (3.84)

    (f) The following projector equality holds:

    PR(Y1)R(Y2)R(Y3)=PA1PA2PA3. (3.85)

    (g) The following projector equality holds:

    P[Y1,Y2,Y3]=Im1PA2PA3+PA1Im2PA3+PA1PA2Im32(PA1PA2PA3). (3.86)

    Proof. Equation (3.80) follows directly from (3.79), and (3.81) follows from (3.80). Since PY1, PY2 and PY3 are idempotent matrices, we find from (2.8) and (3.80) that

    r[Y1,Y2,Y3]=r[PY1,PY2,PY3]=r(PY1)+r(PY2)+r(PY3)   r[PY1PY2,PY1PY3]r[PY2PY1,PY2PY3]r[PY3PY1,PY3PY1]   +r[PY1PY2,PY1PY3,PY2PY2]=r(PY1)+r(PY2)+r(PY3)2r(PA1PA2PA3)=m1r(A2)r(A3)+m2r(A1)r(A3)+m3r(A1)r(A2)2r(A1)r(A2)r(A3),

    thus establishing (3.82). Equations (3.83)–(3.86) are left as exercises for the reader.

    There are some interesting consequences to Theorems 3.3 and 3.4. For example, applying the following well-known rank inequality (cf. [22]):

    r(A+B+C)r[ABC]+r[A,B,C]r(A)r(B)r(C)

    to the sums of matrices in (3.28) and (3.80) yields the two rank inequalities

    r(A1Im2Im3+Im1A2Im3+Im1Im2A3)m1m2r(A3)+m1m3r(A2)+m2m3r(A1)2m1r(A2)r(A3)2m2r(A1)r(A3)   2m3r(A1)r(A2)+2r(A1)r(A2)r(A3)

    and

    r(Im1A2A3+A1Im2A3+A1A2Im3)m1r(A2)r(A3)+m2r(A1)r(A3)+m3r(A1)r(A2)4r(A1)r(A2)r(A3),

    respectively, where A1Cm1×m1,A2Cm2×m2 and A3Cm3×m3.

    We presented a new analysis of the dilation factorizations of the Kronecker products of two or three matrices, and obtained a rich variety of exact formulas and facts related to ranks, dimensions, orthogonal projectors, and ranges of Kronecker products of matrices. Admittedly, it is easy to understand and utilize these resulting formulas and facts in dealing with Kronecker products of matrices under various concrete situations. Given the formulas and facts in the previous theorems, there is no doubt to say that this study clearly demonstrates significance and usefulness of the dilation factorizations of Kronecker products of matrices. Therefore, we believe that this study can bring deeper insights into performances of Kronecker products of matrices, and thereby can lead to certain advances of enabling methodology in the domain of Kronecker products. We also hope that the findings in this resultful study can be taken as fundamental facts and useful supplementary materials in matrix theory when identifying and approaching various theoretical and computational issues associated with Kronecker products of matrices.

    Moreover, the numerous formulas and facts in this article can be extended to the situations for dilation factorizations of multiple Kronecker products of matrices, which can help us a great deal in producing more impressive and useful contributions of researches related to Kronecker products of matrices and developing other relevant mathematical techniques applicable to solving practical topics. Thus, they can be taken as a reference and a source of inspiration for deep understanding and exploration of numerous performances and properties of Kronecker products of matrices.

    The authors declare they have not used Artificial Intelligence (AI) tools in the creation of this article.

    The authors would like to express their sincere thanks to anonymous reviewers for their helpful comments and suggestions.

    The authors declare that they have no conflict of interest.



    [1] L. A. Zadeh, Fuzzy sets, Inf. Control., 8 (1965), 338–353. https://doi.org/10.1016/S0019-9958(65)90241-X
    [2] K. T. Atanassov, Intuitionistic fuzzy sets, Fuzzy Sets Syst., 20 (1986), 87–96. https://doi.org/10.1016/S0165-0114(86)80034-3
    [3] K. T. Atanassov, On the concept of intuitionistic fuzzy sets, In: On intuitionistic fuzzy sets theory, Berlin, Heidelberg: Springer, 2012. https://doi.org/10.1007/978-3-642-29127-2_1
    [4] R. R. Yager, A. M. Abbasov, Pythagorean membership grades, complex numbers, and decision making, Int. J. Intell. Syst., 28 (2013), 436–452. https://doi.org/10.1002/int.21584 doi: 10.1002/int.21584
    [5] S. Zeng, J. Chen, X. Li, A hybrid method for Pythagorean fuzzy multiple-criteria decision making, Int. J. Inf. Technol. Decis., 15 (2016), 403–422. https://doi.org/10.1142/S0219622016500012 doi: 10.1142/S0219622016500012
    [6] X. Zhang, Multicriteria Pythagorean fuzzy decision analysis: A hierarchical QUALIFLEX approach with the closeness index-based ranking methods, Inf. Sci., 330 (2016), 104–124. https://doi.org/10.1016/j.ins.2015.10.012 doi: 10.1016/j.ins.2015.10.012
    [7] M. Akram, K. Zahid, J. C. R. Alcantud, A new outranking method for multicriteria decision making with complex Pythagorean fuzzy information, Neural Comput. Appl., 34 (2022), 8069–8102. https://doi.org/10.1007/s00521-021-06847-1 doi: 10.1007/s00521-021-06847-1
    [8] M. Kirişci, N. Şimşek, Decision making method related to Pythagorean fuzzy soft sets with infectious diseases application, J. King Saud Univ. Comput. Inf. Sci., 34 (2022), 5968–5978. https://doi.org/10.1016/j.jksuci.2021.08.010 doi: 10.1016/j.jksuci.2021.08.010
    [9] M. Deveci, L. Eriskin, M. Karatas, A survey on recent applications of pythagorean fuzzy sets: A state-of-the-art between 2013 and 2020, In: Pythagorean fuzzy sets: Theory and applications, Singapore: Springer, 2021. https://doi.org/10.1007/978-981-16-1989-2_1
    [10] D. A. Molodtsov, Soft set theory - First results, Comput. Math. Appl., 37 (1999), 19–31. https://doi.org/10.1016/S0898-1221(99)00056-5 doi: 10.1016/S0898-1221(99)00056-5
    [11] F. Fatimah, D. Rosadi, R. B. F. Hakim, J. C. R. Alcantud, N-soft sets and their decision making algorithms, Soft Comput., 22 (2018), 3829–3842. https://doi.org/10.1007/s00500-017-2838-6 doi: 10.1007/s00500-017-2838-6
    [12] J. C. R. Alcantud, The semantics of N-soft sets, their applications, and a coda about three-way decision, Inf. Sci., 606 (2022), 837–852. https://doi.org/10.1016/j.ins.2022.05.084 doi: 10.1016/j.ins.2022.05.084
    [13] J. C. R. Alcantud, F. Feng, R. R. Yager, An N-soft set approach to rough sets, IEEE T. Fuzzy Syst., 28 (2020), 2996–3007. https://doi.org/10.1109/TFUZZ.2019.2946526 doi: 10.1109/TFUZZ.2019.2946526
    [14] F. Fatimah, Analysis of tourism facilities using N-soft set decision making procedures, J. RESTI, 4 (2020), 135–141. https://doi.org/10.29207/resti.v4i1.1536 doi: 10.29207/resti.v4i1.1536
    [15] J. C. R. Alcantud, G. Santos-García, M. Akram, OWA aggregation operators and multi-agent decisions with N-soft sets, Expert Syst. Appl., 203 (2022), 117430. https://doi.org/10.1016/j.eswa.2022.117430 doi: 10.1016/j.eswa.2022.117430
    [16] P. K. Maji, A. R. Roy, R. Biswas, Fuzzy soft sets, J. Fuzzy Math., 9 (2001), 589–602.
    [17] P. K. Maji, R. Biswas, A. R. Roy, An application of soft sets in a decision making problem, Comput. Math. Appl., 44 (2002), 1077–1083. https://doi.org/10.1016/S0898-1221(02)00216-X doi: 10.1016/S0898-1221(02)00216-X
    [18] J. C. R. Alcantud, S. C. Rambaud, M. J. M. Torrecillas, Valuation fuzzy soft sets: A flexible fuzzy soft set based decision making procedure for the valuation of assets, Symmetry, 9 (2017), 253. https://doi.org/10.3390/sym9110253 doi: 10.3390/sym9110253
    [19] M. Akram, A. Adeel, J. C. R. Alcantud, Fuzzy N-soft sets: A novel model with applications, J. Intell. Fuzzy Syst., 35 (2018), 4757–4771. https://doi.org/10.3233/JIFS-18244 doi: 10.3233/JIFS-18244
    [20] A. Adeel, M. Akram, N. Yaqoob, W. Chammam, Detection and severity of tumor cells by graded decision-making methods under fuzzy N-soft model, J. Intell. Fuzzy Syst., 39 (2020), 1303–1318. https://doi.org/10.3233/JIFS-192203 doi: 10.3233/JIFS-192203
    [21] D. Zhang, P. Y. Li, S. An, N-soft rough sets and its applications, J. Intell. Fuzzy Syst., 40 (2021), 565–573. https://doi.org/10.3233/JIFS-200338 doi: 10.3233/JIFS-200338
    [22] F. Fatimah, J. C. R. Alcantud, The multi-fuzzy N-soft set and its applications to decision-making, Neural. Comput. Appl., 33 (2021), 11437–11446. https://doi.org/10.1007/s00521-020-05647-3 doi: 10.1007/s00521-020-05647-3
    [23] T. Mahmood, U. Rehman, Z. Ali, A novel complex fuzzy N-soft sets and their decision-making algorithm, Complex Intell. Syst., 7 (2021), 2255–2280. https://doi.org/10.1007/s40747-021-00373-2 doi: 10.1007/s40747-021-00373-2
    [24] U. Rehman, T. Mahmood, Picture fuzzy N-soft sets and their applications in decision-making problems, Fuzzy Inf. Eng., 13 (2021), 335–367. https://doi.org/10.1080/16168658.2021.1943187 doi: 10.1080/16168658.2021.1943187
    [25] M. Akram, M. Sultan, J. C. R. Alcantud, M. M. A. Al-Shamiri, Extended fuzzy N-Soft PROMETHEE method and its application in robot butler selection, Math. Biosci. Eng., 20 (2023), 1774–1800. https://doi.org/10.3934/mbe.2023081 doi: 10.3934/mbe.2023081
    [26] M. Akram, G. Ali, J. C. R. Alcantud, New decision-making hybrid model: Intuitionistic fuzzy N-soft rough sets, Soft Comput., 23 (2019), 9853–9868. https://doi.org/10.1007/s00500-019-03903-w doi: 10.1007/s00500-019-03903-w
    [27] Q. Dong, Q. Sheng, L. Martnez, Z. Zhang, An adaptive group decision making framework: Individual and local world opinion based opinion dynamics, Inf. Fusion, 78 (2022), 218–231. https://doi.org/10.1016/j.inffus.2021.09.013 doi: 10.1016/j.inffus.2021.09.013
    [28] Z. Li, Z. Zhang, Threshold-based value-driven method to support consensus reaching in multicriteria group sorting problems: A minimum adjustment perspective, IEEE T. Comput. Soc. Syst., 2023. https://doi.org/10.1109/TCSS.2023.3251351
    [29] Z. Li, Z. Zhang, W. Yu, Consensus reaching for ordinal classification-based group decision making with heterogeneous preference information, JORS, 2023. https://doi.org/10.1080/01605682.2023.2186806
    [30] R. E. Bellman, L. A. Zadeh, L. A. Decision-making in a fuzzy environment, Manage. Sci., 17 (1970), 141–164. https://doi.org/10.1287/mnsc.17.4.B141 doi: 10.1287/mnsc.17.4.B141
    [31] T. L. Saaty, Axiomatic foundation of the analytic hierarchy process, Manage. Sci., 32 (1986), 841–855. https://doi.org/10.1287/mnsc.32.7.841 doi: 10.1287/mnsc.32.7.841
    [32] C. L. Hwang, K. Yoon, Methods for multiple attribute decision making, In: Multiple attribute decision making, Berlin, Heidelberg: Springer, 1981. https://doi.org/10.1007/978-3-642-48318-9_3
    [33] B. Roy, The outranking approach and the foundations of ELECTRE methods, Theor. Decis., 31 (1991), 49–73. https://doi.org/10.1007/BF00134132 doi: 10.1007/BF00134132
    [34] M. Akram, M. Sultan, J. C. R. Alcantud, An integrated ELECTRE method for selection of rehabilitation center with m-polar fuzzy N-soft information, Artif. Intell. Med., 135 (2023), 102449. https://doi.org/10.1016/j.artmed.2022.102449 doi: 10.1016/j.artmed.2022.102449
    [35] S. Opricovic, G. H. Tzeng, Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS, Eur. J. Oper. Res., 156(2004), 445–455. https://doi.org/10.1016/S0377-2217(03)00020-1 doi: 10.1016/S0377-2217(03)00020-1
    [36] W. K. M. Brauers, E. K. Zavadskas, Project management by MULTIMOORA as an instrument for transition economies, Technol. Econ. Dev. Eco., 16 (2010), 5–24. https://doi.org/10.3846/tede.2010.01 doi: 10.3846/tede.2010.01
    [37] G. Ali, M. Akram, Decision-making method based on fuzzy N-soft expert sets, Arab. J. Sci. Eng., 45 (2020), 10381–10400. https://doi.org/10.1007/s13369-020-04733-x doi: 10.1007/s13369-020-04733-x
    [38] H. Zhang, D. Jia-Hua, C. Yan, Multi-attribute group decision-making methods based on Pythagorean fuzzy N-soft sets, IEEE Access, 8 (2020), 62298–62309. https://doi.org/10.1109/ACCESS.2020.2984583 doi: 10.1109/ACCESS.2020.2984583
    [39] C. Jana, Multiple attribute group decision-making method based on extended bipolar fuzzy MABAC approach, J. Comput. Appl. Math., 40 (2021), 227. https://doi.org/10.1007/s40314-021-01606-3 doi: 10.1007/s40314-021-01606-3
    [40] C. Jana, M. Pal, J. Wang, A robust aggregation operator for multi-criteria decision-making method with bipolar fuzzy soft environment, Iran. J. Fuzzy Syst., 16 (2019), 1–16. https://doi.org/10.22111/IJFS.2019.5014 doi: 10.22111/IJFS.2019.5014
    [41] J. P. Brans, P. H. Vincke, A preference ranking organisation method (The PROMETHEE method for multiple criteria decision making), Manage. Sci., 31 (1985), 647–656. https://doi.org/10.1287/mnsc.31.6.647 doi: 10.1287/mnsc.31.6.647
    [42] M. Goumas, V. Lygerou, An extension of the PROMETHEE method for decision making in fuzzy environment: Ranking of alternative energy exploitation projects, Eur. J. Oper. Res., 123 (2000), 606–613. https://doi.org/10.1016/S0377-2217(99)00093-4 doi: 10.1016/S0377-2217(99)00093-4
    [43] M. Gul, E. Celik, A. T. Gumus, A. F. Guneri, A fuzzy logic based PROMETHEE method for material selection problems, Beni-Suef Univ. J. Basic Appl. Sci., 7 (2018), 68–79. https://doi.org/10.1016/j.bjbas.2017.07.002 doi: 10.1016/j.bjbas.2017.07.002
    [44] F. Feng, Z. Xu, H. Fujita, M. Liang, Enhancing PROMETHEE method with intuitionistic fuzzy soft sets, Int. J. Intell. Syst., 35 (2020), 1071–1104. https://doi.org/10.1002/int.22235 doi: 10.1002/int.22235
    [45] R. Krishankumar, K. S. Ravichandran, A. B. Saeid, A new extension to PROMETHEE under intuitionistic fuzzy environment for solving supplier selection problem with linguistic preferences, Appl. Soft Comput., 60 (2017), 564–576. https://doi.org/10.1016/j.asoc.2017.07.028 doi: 10.1016/j.asoc.2017.07.028
    [46] W. Zhang, Y. Zhu, D. Wang, S. Zhao, D. Dong, A multi-attribute decision making method based on interval Pythagorean fuzzy language and the PROMETHEE method, In: Advances in Natural Computation, Fuzzy Systems and Knowledge Discovery, Cham: Springer, 2019. https://doi.org/10.1007/978-3-030-32456-8_88
    [47] F. Feng, H. Fujita, M. I. Ali, R. R. Yager, X. Liu, Another view on generalized intuitionistic fuzzy soft sets and related multiattribute decision making methods, IEEE T. Fuzzy Syst., 27 (2019), 474–488. https://doi.org/10.1109/TFUZZ.2018.2860967 doi: 10.1109/TFUZZ.2018.2860967
    [48] F. Feng, M. Liang, H. Fujita, R. R. Yager, X. Liu, Lexicographic orders of intuitionistic fuzzy values and their relationships, Mathematics, 7 (2019), 166. https://doi.org/10.3390/math7020166 doi: 10.3390/math7020166
    [49] H. Liao, Z. Xu, Multi-criteria decision making with intuitionistic fuzzy PROMETHEE, J. Intell. Fuzzy Syst., 27(2014), 1703–1717. https://doi.org/10.3233/IFS-141137 doi: 10.3233/IFS-141137
    [50] R. R. Yager, Pythagorean membership grades in multicriteria decision making, IEEE T. Fuzzy Syst., 22 (2013), 958–965. https://doi.org/10.1109/TFUZZ.2013.2278989 doi: 10.1109/TFUZZ.2013.2278989
    [51] T. Y. Chen, A novel PROMETHEE-based outranking approach for multiple criteria decision analysis with Pythagorean fuzzy information, IEEE Access, 6 (2018), 54495–54506. https://doi.org/10.1109/ACCESS.2018.2869137 doi: 10.1109/ACCESS.2018.2869137
    [52] A. Mardani, A. Jusoh, E. K. Zavadskas, Fuzzy multiple criteria decision-making techniques and applications-Two decades review from 1994 to 2014, Expert Syst. Appl., 42 (2015), 4126–4148. https://doi.org/10.1016/j.eswa.2015.01.003 doi: 10.1016/j.eswa.2015.01.003
    [53] M. J. Manton, L. Warren, A Confirmatory Snowfall Enhancement Project in the Snowy Mountains of Australia. Part II: Primary and Associated Analyses, J. Appl. Meteorol. Climtol., 50 (2011), 1448–1458. https://doi.org/10.1175/2011JAMC2660.1 doi: 10.1175/2011JAMC2660.1
    [54] D. Pamucar, M. Deveci, F. Canitez, D. Bozanic, A fuzzy full consistency method-Dombi-Bonferroni model for prioritizing transportation demand management measures, Appl. Soft Comput., 87 (2020), 105952. https://doi.org/10.1016/j.asoc.2019.105952 doi: 10.1016/j.asoc.2019.105952
    [55] H. M. Ridha, H. Hizam, S. Mirjalili, M. L. Othman, M. E. Ya'acob, M. Ahmadipour, Innovative hybridization of the two-archive and PROMETHEE-II triple-objective and multi-criterion decision making for optimum configuration of the hybrid renewable energy system, Appl. Energy, 341 (2023), 121117. https://doi.org/10.1016/j.apenergy.2023.121117 doi: 10.1016/j.apenergy.2023.121117
    [56] A. B. Super, J. A. Heimbach, Evaluation of the bridger range winter cloud seeding experiment using control gages, J. Climatol. Appl. Meteorol., 22 (1983), 1989–2011.
    [57] Y. Yang, T. Gai, M. Cao, Z. Zhang, H. Zhang, J. Wu, Application of Group Decision Making in Shipping Industry 4.0: Bibliometric Analysis, Trends, and Future Directions, Systems, 11 (2023), 69. https://doi.org/10.3390/systems11020069 doi: 10.3390/systems11020069
    [58] J. P. Brans, Ph. Vincke, B. Mareschal, How to select and how to rank projects: The PROMETHEE method, Eur. J. Oper. Res., 24 (1986), 228–238. https://doi.org/10.1016/0377-2217(86)90044-5 doi: 10.1016/0377-2217(86)90044-5
    [59] J. Ye, T. Y. Chen, Pythagorean fuzzy sets combined with the PROMETHEE method for the selection of cotton woven fabric, J. Nat. Fibers, 19 (2022), 12447–12461. https://doi.org/10.1080/15440478.2022.2072993 doi: 10.1080/15440478.2022.2072993
    [60] M. Kirisci, I. Demir, N. Simsek, N. Topa, M. Bardak, The novel VIKOR methods for generalized Pythagorean fuzzy soft sets and its application to children of early childhood in COVID-19 quarantine, Neural Comput. Appl., 34 (2022), 1877–1903. https://doi.org/10.1007/s00521-021-06427-3 doi: 10.1007/s00521-021-06427-3
    [61] Z. Hua, X. Jing, A generalized shapley index-based interval-valued Pythagorean fuzzy PROMETHEE method for group decision-making, Soft Comput., 27 (2023), 6629–6652. https://doi.org/10.1007/s00500-023-07842-5 doi: 10.1007/s00500-023-07842-5
    [62] M. U. Molla, B. C. Giri, P. Biswas, Extended PROMETHEE method with Pythagorean fuzzy sets for medical diagnosis problems, Soft Comput., 25 (2021), 4503–4512. https://doi.org/10.1007/s00500-020-05458-7 doi: 10.1007/s00500-020-05458-7
    [63] C. Jana, M. Pal, A robust single-valued neutrosophic soft aggregation operators in multi-criteria decision making, Symmetry, 11 (2019), 110. https://doi.org/10.3390/sym11010110 doi: 10.3390/sym11010110
    [64] M. Alipour, R. Hafezi, P. Rani, M. Hafezi, A. Mardani, A new Pythagorean fuzzy-based decision-making method through entropy measure for fuel cell and hydrogen components supplier selection, Energy, 234 (2021), 121208. https://doi.org/10.1016/j.energy.2021.121208 doi: 10.1016/j.energy.2021.121208
  • Reader Comments
  • © 2023 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

Metrics

Article views(2155) PDF downloads(142) Cited by(6)

Figures and Tables

Figures(8)  /  Tables(23)

/

DownLoad:  Full-Size Img  PowerPoint
Return
Return

Catalog