Skip to main content
Springer logoLink to Springer
. 2018 Oct 25;2018(1):291. doi: 10.1186/s13660-018-1869-6

AE solutions to two-sided interval linear systems over max-plus algebra

Lihua Wang 1, Wei Li 1, Haohao Li 2,
PMCID: PMC6208628  PMID: 30839792

Abstract

This paper introduces a concept of AE solutions to two-sided interval max-plus linear systems, a rather general concept which includes many known concepts of solutions to interval systems, in particular, weak, strong, tolerance and control solutions as its special cases. We state full characterizations of AE solutions for the two-sided interval max-plus systems, including both linear inequalities and linear equations. Moreover, we provide a specific example to illustrate an efficient method of finding the AE solution set.

Keywords: Two-sided interval linear systems, Max-plus algebra, AE solutions

Introduction

The max-plus algebra (Rmax,,) has appeared under the name extremal algebra for many years [1, 2]. In this algebra, several types of solvability of interval linear systems, including both interval linear equations and interval linear inequalities, have been studied in the literature, see, e.g., weak and strong solvability in [3, 4], tolerance solvability in [57], and control solvability in [8]. A detailed discussion of interval solutions can be found in Chap. 6 of [9] and a brief review of the max-plus linear systems in [10].

Two-sided systems of max-plus linear systems containing a vector xRmaxn on both sides had been studied by many authors. The theories of these systems in the classical algebra can be found in, e.g., [1114] and the references therein.

In classical linear algebra, interval linear systems are often used for modeling information systems and engineering problems. Over the past decades, these uncertain systems have been discussed widely, see, e.g., [9, 1518]. One of the main difficulties when dealing with interval uncertainty is how to understand the concepts of solutions. Shary first proposed the concept of AE solutions for interval linear equations in 2002, a rather general concept which includes many traditional concepts of solutions to interval systems as its special cases [19]. Sharaya considered the interval linear system with both equations and inequalities [20]. Recently, Hladík [21] extended the AE solutions to the general interval linear systems of equations, inequalities, or both. Some new results on AE solutions can be found in, e.g., [2224]. Similar methods have been utilized for interval inequalities and interval linear programming for some special cases [2530].

In this paper, we first extend the concept of AE solutions to max-plus algebra in two-sided interval systems. A practical motivation or studying AE solutions of two-sided interval systems in max-plus algebra is presented in Example 1. Necessary and sufficient conditions for checking the AE solvability of two-sided interval systems in max-plus algebra are formulated in Sects. 4 and 5. Then, in Sect. 6, we present an efficient method to find the AE solution set of two-sided interval linear systems. In Sect. 7, we show that each particular result of weak, strong, tolerance and control solutions established for interval linear systems in existing literature is a special case of the main results of this paper. The conclusion and future application are drawn in Sect. 8.

Preliminaries

In this section, let us introduce some notations first (see [9]). By a max-plus algebra we understand a triple (Rmax,,), where Rmax=R{ε}, R is the set of all real numbers and ⊕,⊗ are binary operations defined as

ab=max{a,b},ab=a+b,

where ε=. Let E be a matrix consisting entirely of ε. The operations ⊕,⊗ are extended to matrices and vectors in the same way as in conventional linear algebra. If ARmaxm×n,BRmaxn×p, we define the product ABRmaxm×p with entries (AB)ij defined for i=1,,m,j=1,,p as follows:

(AB)ij=k=1naikbkj=max1kn{aik+bkj}.

If ARmaxm×n,BRmaxm×n, we define the sum ABRmaxm×n with entries (AB)ij defined for i=1,,m,j=1,,n as follows:

(AB)ij=max{aij,bij}.

An interval matrix is defined as

A=[A_,A]={ARmaxm×n|A_AA},

where A_,ARmaxm×n, A_A, and “≤” is understood componentwise. An interval vector b=[b_,b]={bRmaxm|b_bb} is understood as one-column interval matrix. In the max-plus algebra, the set of all m×n interval matrices will be denoted by IRmaxm×n, and the set of all m-dimensional interval vectors by IRmaxm.

Given AIRmaxm×n and BIRmaxm×n, the corresponding two-sided interval linear system of inequalities

AxBx 2.1

is the family of systems

AxBx, 2.2

where AA,BB.

Similarly, the corresponding interval system of equations of the form

Ax=Bx 2.3

represents the set of all systems of linear max-plus systems of the form

Ax=Bx, 2.4

where AA,BB.

The following lemmas will be used in the proofs of our results.

Lemma 2.1

Let A=(aij)Rmaxm×n, B=(bij)Rmaxm×n. If AB, then AxBx.

Proof

Note that aijbij, and for i=1,,m, we have

[Ax]i=j=1n(aijxj)=j=1n(aij+xj)=max1jn{aij+xj}

and

[Bx]i=j=1n(bijxj)=j=1n(bij+xj)=max1jn{bij+xj}.

Thus, [Ax]i[Bx]i, for i=1,,m, i.e., AxBx. □

Lemma 2.2

Let A=(aij)Rmaxm×n, B=(bij)Rmaxm×n, C=(cij)Rmaxm×n. If AC, then ABBC.

Proof

Note that aijcij, we have

(AB)ij=max{aij,bij}max{cij,bij}=(BC)ij

for i=1,,m,j=1,,n, i.e., ABBC. □

AE solutions to interval max-plus systems

Let us recall the concept of AE solutions of interval inequalities in classical algebra [19, 21, 22]. The interval matrix can be split as A=A+A, where A is the interval matrix comprising universally quantified coefficients, and A concerns existentially quantified coefficients. A vector xRn is an AE solution of Axb if

AA,bb,AA,bb

such that

(A+A)xb+b.

Analogously, in the max-plus algebra, by using forall-exists quantification of interval parameters, we decompose the interval matrix as A=AA, where the components in the matrix A at the positions associated with the existential quantifier are intervals [ε,ε] and components in the matrix A at the positions associated with the universal quantifier are intervals [ε,ε].

Now we extend the concept of AE solutions of an interval linear system in classical algebra to the max-plus algebra.

Definition 3.1

A vector xRmaxn is an AE solution of system AxBx(or Ax=Bx) if for AA,BB,AA,BB such that

(AA)x(BB)x 3.1
(or (AA)x=(BB)x). 3.2

The next example demonstrates how this type of solution can be applied to an application problem.

Example 1

A sportswear company produces m types of sport suit, including top and bottom. All the clothes are made from three kinds of material: cotton, polyester fibre and chemical fiber. Due to the varieties of product and material, the production time of each type of suit corresponding to three different kinds of material is different. Each clothing item is finished only after all the material is completed.

Suppose that the production time data of each type of top and bottom, corresponding to three different kinds of material are interval times [aij_,aij] and [bij_,bij]. Before processing, preparing time xj for each material is required. If the working durations aij and bij are fixed, the time at which each type of top and bottom are completed is

max{ai11+x1,ai21+x2,,ain1+xn}

and

max{bi11+x1,bi21+x2,,bin1+xn}.

The packaging should be completed only after the suits, including both tops and the bottoms, are finished.

To optimize production, the company needs to set the preparation time xj for each material such that each type of top and bottom is completed at the same time. This task is equivalent to solving the system of equations

max{ai11+x1,ai21+x2,,ain1+xn}=max{bi11+x1,bi21+x2,,bin1+xn},

for each i{1,2,,m}, which can be simplified to the matrix form

[a11a12a1nam1am2amn][x1xn]=[b11b12b1nbm1bm2bmn][x1xn].

Under uncertain working durations, it becomes the interval system

[[a11_,a11][a1n_,a1n][am1_,am1][amn_,amn]][x1xn]=[[b11_,b11][b1n_,b1n][bm1_,bm1][bmn_,bmn]][x1xn]. 3.3

In production, the company may not be able to improve parts of its interval production times [aij_,aij] and [bij_,bij]. In this situation, an AE solution (x1,x2,,xn)T of system (3.3), when n=3, may exist if the company is able to fix the other parts of production times aij and bij.

Characterization of AE solutions for two-sided interval linear inequalities

Consider a two-sided interval system of equations of the following form:

AxBx,

where AIRmaxm×n, BIRmaxm×n.

A sufficient and necessary characterization of AE solutions to interval system of max-plus linear inequalities (2.1) is described in the following theorem.

Theorem 4.1

A vector xRmaxn is an AE solution of two-sided interval linear max-plus inequalities (2.1) if and only if

(AA_)x(B_B)x. 4.1

Proof

Assume that x is an AE solution of system AxBx. Then for AA, BB, system (2.1) is solvable for some A=A0 and B=B0. That is, for AA, BB,

(AA0)x(BB0)x.

Due to the isotone properties presented in Lemmas 2.1 and 2.2, we have

(AA_)x(AA0)x(BB0)x(BB)x. 4.2

Particularly, letting A=A and B=B_ in (4.2), we have

(Ax)(A_x)(B_x)(Bx).

Therefore, inequalities (4.1) hold.

Conversely, assume that vector xRmaxn satisfies inequalities (4.1). According to Lemma 2.1, for all AA, BB, we have

(AA_)x(AA_)x(B_B)x(BB)x.

Therefore, for all AA, BB, there exist A=A_, B=B such that the inequalities

(AA)x(BB)x

hold.

Hence xRmaxn is an AE solution of AxBx. This completes the proof. □

Characterization of AE solutions for two-sided interval linear equations

Consider a two-sided interval system of equations of the following form:

Ax=Bx,

where AIRmaxm×n, BIRmaxm×n.

A sufficient and necessary characterization of AE solutions to interval system of max-plus linear equations (2.3) is described in the following theorem.

Theorem 5.1

A vector xRmaxn is an AE solution of two-sided interval linear max-plus equations (2.3) if and only if

(AA_)x(B_B)x, 5.1
(A_A)x(BB_)x. 5.2

Proof

Assume that x is an AE solution of system Ax=Bx, then it is an AE solution of AxBx and an AE solution of BxAx. Therefore, inequalities (5.1) and (5.2) hold due to Theorem 4.1.

Conversely, assume that vector xRmaxn satisfies inequalities (5.1) and (5.2). For the opposite implication, suppose that vector x is not an AE solution of Ax=Bx. Then, by definition, A˜A, B˜B, AA, BB such that

(A˜A)x(B˜B)x.

Therefore, there exists an i0{1,,m} such that

((A˜A_)x)i0>((B˜B)x)i0 5.3

or

((A˜A)x)i0<((B˜B_)x)i0. 5.4

If inequality (5.3) is satisfied, due to the isotone property, we have

((AA_)x)i0((A˜A_)x)i0>((B˜B)x)i0((B_B)x)i0,

which leads to a contradiction of (5.1).

If inequality (5.4) is satisfied, due to the isotone property, we have

((A_A)x)i0((A˜A)x)i0<((B˜B_)x)i0((BB_)x)i0,

which leads to a contradiction of (5.2).

Thus vector x is an AE solution of Ax=Bx. This completes the proof. □

Deriving the solution algorithm

From Theorems 4.1 and 5.1, we observe that the equivalent systems of AE solutions are both in a general form of a two-sided systems of max-plus linear inequalities

AxBx.

In this section, we present Example 2 in order to show how to find the AE solution set of a two-sided interval linear system of inequalities AxBx, by using the following theorems proposed in [10]. And this method is also suitable for finding the AE solution set of Ax=Bx.

Theorem 6.1

([10])

Let ARmaxm×n and BRmaxm×n. If there exists an iM={1,2,,m} such that {jN={1,2,,n}:aijbij}=, then the trivial solution x=(ε,ε,,ε)T is a unique solution of system Ax=Bx.

Theorem 6.2

([10])

Let A=[aij] and B=[bij] be in Rmaxm×n. A vector xRmaxn is a solution of AxBx if and only if x belongs to the set

(ji)iMH{xRmaxn:Cxx},

where Hi={jN:aijbij} for each iM, M={iM:HiN}, H=iMHi, (ji)iM=(ji1,,ji|M|), i1<<i|M| and CRmaxn×n has the following components:

cjk={ε,j=kmaxji=j,iM{aikbij},jk.

Theorem 6.3

([10])

Let C=[cij]Rmaxn×n be such that cij=ε for all i=j. If cij+cji>0 for some i>j, then Cxx has no non-trivial solution.

Theorem 6.4

([10])

Let C=[cij]Rmaxn×n be such that cij=ε for all i=j and cij+cji0 for all i>j. A vector xRmaxn is a solution of Cxx if and only if x is a solution of the interval inclusion linear system

Dxh,

in which

D=[11111111111111]Rn(n1)2×nandh=[[c12,c21][c1n,cn1][c23,c32][c2n,cn2][cn2,n1,cn1,n2][cn2,n,cn,n2][cn1,n,cn,n1]]IRmaxn(n1)2.

Example 2

Consider the system

[[1,4][0,1][2,6][2,4][4,6][1,3][3,5]3[1,4][2,3][0,1][2,3]][x1x2x3][[0,1][5,8][1,3][3,5][3,4][0,1][0,2][0,4][1,2][2,4][1,2][2,1]][x1x2x3], 6.1

where

A=[[1,4][0,1]εε[4,6]εεεε[2,3][0,1][2,3]],A=[εε[2,6][2,4]ε[1,3][3,5]3[1,4]εεε],B=[εε[1,3][3,5]ε[0,1][0,2][0,4]εεεε],B=[[0,1][5,8]εε[3,4]εεε[1,2][2,4][1,2][2,1]].

By Theorem 4.1, we can obtain the equivalent system of AE solutions,

(AA_)x(B_B)x,

that is,

[412261331313][x1x2x3][181340002421][x1x2x3]. 6.2

By Theorem 6.1, we know that the trivial solution x=(ε,ε,,ε)T is not a unique solution of system (6.2), because {jN={1,2,3}:aijbij} for each iM={1,2,3,4}.

Next, by Theorem 6.2, we have H1={2},H2={1},H3={3},H4={1,2},M={1,2,3,4},H=i=14Hi and

(ji)iMH{xRmaxn:Cxx}

equals

{xRmaxn:[ε321ε111ε]xx}{xRmaxn:[ε314ε611ε]xx}. 6.3

By Theorems 6.3 and 6.4, we derive that the solution set is

{xRmaxn:[ε321ε111ε]xx}= 6.4

because c21+c12=4>0, and the solution set

{xRmaxn:[ε314ε611ε]xx} 6.5

equals

{xRmaxn:Dxh},D=[110101011],h=[[3,4]1[6,1]].

Thus, a vector x is an AE solution of system (6.1) if and only if x satisfies

[316][110101011]x[411], 6.6

for instance, vector x=(0,3,1)T is an AE solution of system (6.1).

Special cases of AE solutions of two-sided interval linear systems

As we know, mathematical definitions of various traditional solution types (weak, strong, tolerance, control) of the two-sided interval linear systems of equations Ax=Bx were presented in [10] as follows:

Definition 7.1

([10])

A vector xRmaxn is called

  • (i)

    a weak solution of system (2.3) if Ax=Bx for some AA, BB;

  • (ii)

    a strong solution of system (2.3) if Ax=Bx for all AA, BB;

  • (iii)

    a tolerance solution of system (2.3) if Ax=Bx for all AA for some BB;

  • (iv)

    a control solution of system (2.3) if Ax=Bx for some AA for all BB.

In this section, we first extend the analogous concepts of solutions for two-sided interval linear systems of inequalities AxBx.

Definition 7.2

A vector xRmaxn is called

  • (i)

    a weak solution of system (2.1) if AxBx for some AA, BB;

  • (ii)

    a strong solution of system (2.1) if AxBx for all AA, BB;

  • (iii)

    a tolerance solution of system (2.1) if AxBx for all AA for some BB;

  • (iv)

    a control solution of system (2.1) if AxBx for all BB for some AA.

From the definition of AE solutions, it is easy to obtain that the weak, strong, tolerance and control solutions are all special cases of AE solutions.

Then we propose the full characterizations of four different types of solution of system AxBx.

Corollary 7.1

A vector xRmaxn is a weak solution of the interval system (2.1) if and only if

A_xBx.

Proof

The assertion follows immediately from Theorem 4.1 if we set A=E,B=E. □

Corollary 7.2

A vector xRmaxn is a strong solution of the interval system (2.1) if and only if

AxB_x.

Proof

The assertion follows immediately from Theorem 4.1 if we set A=E,B=E. □

Corollary 7.3

A vector xRmaxn is a tolerance solution of the interval system (2.1) if and only if

AxBx.

Proof

The assertion follows immediately from Theorem 4.1 if we set A=E,B=E. □

Corollary 7.4

A vector xRmaxn is a control solution of the interval system (2.1) if and only if

A_xB_x.

Proof

The assertion follows immediately from Theorem 4.1 if we set A=E,B=E. □

Moreover, we find that the equivalent conditions for checking such solvability types of two-sided interval systems of equations in the max-plus algebra formulated in [10] are also special cases in Theorem 5.1.

Corollary 7.5

([10])

A vector xRmaxn is a weak solution of the interval system (2.3) if and only if

A_xBx,AxB_x.

Proof

The assertion follows immediately from Theorem 5.1 if we set A=E,B=E. □

Corollary 7.6

([10])

A vector xRmaxn is a strong solution of the interval system (2.3) if and only if

AxB_x,A_xBx.

Proof

The assertion follows immediately from Theorem 5.1 if we set A=E,B=E. □

Corollary 7.7

([10])

A vector xRmaxn is a tolerance solution of the interval system (2.3) if and only if

AxBx,A_xB_x.

Proof

The assertion follows immediately from Theorem 5.1 if we set A=E,B=E. □

Corollary 7.8

([10])

A vector xRmaxn is a control solution of the interval system (2.3) if and only if

A_xB_x,AxBx.

Proof

The assertion follows immediately from Theorem 5.1 if we set A=E,B=E. □

Conclusion

We introduced a new concept of AE solutions to two-sided interval linear systems over the max-plus algebra. The full characterizations of AE solutions to the two-sided interval max-plus systems, including both inequalities (2.1) and equations (2.3), were developed. Furthermore, we presented a specific example to illustrate an efficient algorithm of finding the AE solution set of two-sided interval linear systems. The characterizations of several traditional solutions for interval max-plus linear systems are all special cases of of our main results.

An interesting direction for further research is to characterize the so-called EA solutions to two-sided interval linear systems over the max-plus algebra, which can be regarded as dual to AE solutions. In the definition of EA solutions, the separating predicate is such that all the occurrences of the existential quantifier “∃” precede the occurrences of the universal quantifier “∀”. More specifically, a vector xRmaxn is an EA solution of system (2.1) (or system (2.3)) if, for AA,BB,AA,BB, (2.2) (or (2.4)) holds. Recently, the characteristics of EA solutions over ordinary interval algebra have just been established [31]. The characterization of EA solutions to interval linear systems over the max-plus algebra remains to be an open problem, which is worth studying further.

Acknowledgements

The authors would like to thank anonymous referees for their constructive comments and suggestions that helped to improve the paper.

Authors’ contributions

All authors contributed significantly in writing this paper. All authors read and approved the final manuscript.

Funding

The authors were partially supported by the NNSF of China (Grant Nos. 11701506, U1509217, 71471051).

Competing interests

The authors declare that they have no competing interests.

Footnotes

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Contributor Information

Lihua Wang, Email: lhuawang@126.com.

Wei Li, Email: weilihz@126.com.

Haohao Li, Email: hhli@zufe.edu.cn.

References

  • 1.Cuninghame-Green R. Minimax Algebra. Berlin: Springer; 1979. [Google Scholar]
  • 2.Vorobjov N.N. Extremal algebra of positive matrices. Datenverarbeitung und Kybernetik. 1967;3:39–71. [Google Scholar]
  • 3.Cechlárová K. International Symposium on Operational Research. 2001. Solutions of interval linear systems in (max;+)-algebra; pp. 321–326. [Google Scholar]
  • 4.Cechlárová K., Cuninghame-Green R.A. Interval systems of max-separable linear equations. Linear Algebra Appl. 2002;403:215–224. doi: 10.1016/S0024-3795(01)00405-0. [DOI] [Google Scholar]
  • 5.Gavalec M., Plavka J., Ponce D. Tolerance types of interval eigenvectors in max-plus algebra. Inf. Sci. 2016;367–368:14–27. doi: 10.1016/j.ins.2016.05.023. [DOI] [Google Scholar]
  • 6.Myčková H. Interval systems of max-separable linear equations. Linear Algebra Appl. 2005;403:263–272. doi: 10.1016/j.laa.2005.02.011. [DOI] [Google Scholar]
  • 7.Myčková H. Interval max-plus matrix equations. Linear Algebra Appl. 2016;492:111–127. doi: 10.1016/j.laa.2015.10.031. [DOI] [Google Scholar]
  • 8.Myčková H. Control solvability of interval systems of max-separable linear equations. Linear Algebra Appl. 2006;416(2):215–223. doi: 10.1016/j.laa.2005.11.008. [DOI] [Google Scholar]
  • 9.Fiedler M., Nedoma J., Ramík J., Rohn J., Zimmermann K. Linear Optimization Problems with Inexact Data. New York: Springer; 2006. [Google Scholar]
  • 10.Leela-Apiradee W., Lodwick W.A., Thipwiwatpotjana P. An algorithm for solving two-sided interval system of max-plus linear equations. Inf. Sci. 2017;399:183–200. doi: 10.1016/j.ins.2017.03.003. [DOI] [Google Scholar]
  • 11.Butkovič P., Hegedüs G. An elimination method for finding all solutions of the system of linear equations over an extremal algebra. Ekonomicko Matematicky Obzor. 1984;20(2):203–215. [Google Scholar]
  • 12.Butkovič P., Zimmermann K. A strongly polynomial algorithm for solving two-sided linear systems in max-algebra. Discrete Appl. Math. 2006;154(3):437–446. doi: 10.1016/j.dam.2005.09.008. [DOI] [Google Scholar]
  • 13.Cuninghame-Green R.A., Butkovič P.P. The equation ax=by over (max,+) Theor. Comput. Sci. 1991;293(1):3–12. doi: 10.1016/S0304-3975(02)00228-1. [DOI] [Google Scholar]
  • 14.Walkup E.A., Borriello G. Idempotency. Cambridge: Cambridge University Press; 1998. A general linear max–plus solution technique; pp. 406–415. [Google Scholar]
  • 15.Moore R.E., Baker Kearfott R., Cloud M.J. Introduction to Interval Analysis. Philadelphia: SIAM; 2009. [Google Scholar]
  • 16.Neumaier A. Interval Methods for Systems of Equations. Cambridge: Cambridge University Press; 1990. [Google Scholar]
  • 17.Rohn J. System of linear interval equations. Linear Algebra Appl. 1989;126:39–78. doi: 10.1016/0024-3795(89)90004-9. [DOI] [Google Scholar]
  • 18.Shary S.P. Solving the linear interval tolerance problem. Math. Comput. Simul. 1995;39:53–85. doi: 10.1016/0378-4754(95)00135-K. [DOI] [Google Scholar]
  • 19.Shary S.P. A new technique in systems analysis under interval uncertainty and ambiguity. Reliab. Comput. 2002;8(5):321–418. doi: 10.1023/A:1020505620702. [DOI] [Google Scholar]
  • 20.Sharaya I.A. Quantifier-free descriptions for interval-quantifier linear systems. Trudy Instituta Matematiki i Mekhaniki UrO RAN. 2014;20(2):311–323. [Google Scholar]
  • 21.Hladík M. AE solutions and AE solvability to general interval linear systems. Linear Algebra Appl. 2015;465:221–238. doi: 10.1016/j.laa.2014.09.030. [DOI] [Google Scholar]
  • 22.Goldsztejn A. A right-preconditioning process for the formal-algebraic approach to inner and outer estimation of AE-solution sets. Reliab. Comput. 2005;11(6):443–478. doi: 10.1007/s11155-005-0404-x. [DOI] [Google Scholar]
  • 23.Popova E.D. Explicit description of AE solution sets for parametric linear systems. SIAM J. Matrix Anal. Appl. 2012;33(4):1172–1189. doi: 10.1137/120870359. [DOI] [Google Scholar]
  • 24.Popova E.D., Hladík M. Outer enclosures to the parametric AE solution set. Soft Comput. 2013;17(8):1403–1414. doi: 10.1007/s00500-013-1011-0. [DOI] [Google Scholar]
  • 25.Li H., Luo J., Wang Q. Solvability and feasibility of interval linear equations and inequalities. Linear Algebra Appl. 2014;463:78–94. doi: 10.1016/j.laa.2014.08.027. [DOI] [Google Scholar]
  • 26.Luo J., Li W. Strong optimal solutions of interval linear programming. Linear Algebra Appl. 2013;439(8):2479–2493. doi: 10.1016/j.laa.2013.06.022. [DOI] [Google Scholar]
  • 27.Li W., Luo J., Deng C. Necessary and sufficient conditions of some strong optimal solutions to the interval linear programming. Linear Algebra Appl. 2013;439(10):3241–3255. doi: 10.1016/j.laa.2013.08.013. [DOI] [Google Scholar]
  • 28.Li W., Luo J., Wang Q. Checking strong optimality of interval linear programming with inequality constraints and nonnegative constraints. J. Comput. Appl. Math. 2014;260:180–190. doi: 10.1016/j.cam.2013.09.075. [DOI] [Google Scholar]
  • 29.Li W., Liu X., Li H. Generalized solutions to interval linear programs and related necessary and sufficient optimality conditions. Optim. Methods Softw. 2015;30(3):516–530. doi: 10.1080/10556788.2014.940948. [DOI] [Google Scholar]
  • 30.Hladík M. Robust optimal solutions in interval linear programming with forall–exists quantifiers. Eur. J. Oper. Res. 2014;254(3):705–714. doi: 10.1016/j.ejor.2016.04.032. [DOI] [Google Scholar]
  • 31. Huang, J., Wang, C., Li, H.: EA solutions to general interval linear systems. Linear Multilinear Algebra (Submitted)

Articles from Journal of Inequalities and Applications are provided here courtesy of Springer

RESOURCES