M-matrices leading to semiconvergent splittings

An M-matrix as defined by Ostrowski is a matrix that can be split into A = sI ? B, s > 0, B ? 0 with s ? ρ(B), the spectral radius of B. M-matrices with the property that the powers of T = (1/s)B converge for some s are studied and are characterized here in terms of the nonnegativity of the group generalized inverse of A on the range space of A, extending the well-known property that A^{? 1} ? 0 whenever A is nonsingular.     

Singular M-matrices and inverse positivity

For a matrix decomposable as A=sI?B, where B?0, it is well known that A^?1?0 if and only if the spectral radius ρ(B)>s. An extension of this result to the singular case ρ(B)=s is made by replacing A^?1 by [A+t(I?AA^D)]^?1, where A^D is the Drazin generalized inverse.     

Completely mixed games and M-matrices

Any non-singular M-matrix is a completely mixed matrix game with positive value. We exploit this property to give game-theoretic proofs of several well-known characterizations of such matrices. The same methods yield also many theorems on S₀-irreducible matrices that are closely related to M-matrices.     

A note on factorizations of singular M-matrices

Supposing that M is a singular M-matrix, we show that there exists a permutation matrix P such that PMP^T = LU, where L is a lower triangular M-matrix and U is an upper triangular singular M-matrix. An example is given to illustrate that the above result is the best possible one.     

Tridiagonal and upper triangular inverse M-matrices

In this paper we characterize the nonnegative nonsingular tridiagonal matrices belonging to the class of inverse M-matrices. We give a geometric equivalence for a nonnegative nonsingular upper triangular matrix to be in this class. This equivalence is extended to include some reducible matrices.     

A stability concept for matrix game optimal strategies and its application to linear programming sensitivity analysis

This paper studies a class of perturbations of a game matrix that alters each row by a different amount. We find that completely mixed optimal strategies are stable under these perturbations provided the norm of the vector of additive amounts is sufficiently small. Using this concept we give a new characterization of completely mixed grames. We also obtain a sensitivity result for a class of perturbations of the technological coefficient matrix of positive linear programs. The stability of an optimal strategy holds throughout at least a spherical neighborhood of the zero perturbation. We give a computational formula and equivalent programming formulations for the radius of this neighborhood.     

Comparison results on preconditioned SOR-type iterative method for Z-matrices linear systems

In this paper, we present some comparison theorems on preconditioned iterative method for solving Z-matrices linear systems, Comparison results show that the rate of convergence of the Gauss–Seidel-type method is faster than the rate of convergence of the SOR-type iterative method.     

Convergence of block iterative methods for linear systems with generalized H-matrices

The paper studies the convergence of some block iterative methods for the solution of linear systems when the coefficient matrices are generalized H$H$-matrices. A truth is found that the class of conjugate generalized H$H$-matrices is a subclass of the class of generalized H$H$-matrices and the convergence results of R. Nabben [R. Nabben, On a class of matrices which arises in the numerical solution of Euler equations, Numer. Math. 63 (1992) 411–431] are then extended to the class of generalized H$H$-matrices. Furthermore, the convergence of the block AOR iterative method for linear systems with generalized H$H$-matrices is established and some properties of special block tridiagonal matrices arising in the numerical solution of Euler equations are discussed. Finally, some examples are given to demonstrate the convergence results obtained in this paper.     

A trace inequality for M-matrices and the symmetrizability of a real matrix by a positive diagonal matrix

The question of whether a real matrix is symmetrizable via multiplication by a diagonal matrix with positive diagonal entries is reduced to the corresponding question for M-matrices and related to Hadamard products. In the process, for a nonsingular M-matrix A, it is shown that tr(A^-1A^T) ? n, with equality if and only if A is symmetric, and that the minimum eigenvalue of A^-1 ° A is ? 1 with equality in the irreducible case if and only if A is positive diagonally symmetrizable.     

On classes of matrices containing M-matrices and hermitian positive semidefinite matrices

Two new classes of matrices are introduced, containing hermitian positive semi-definite matrices and M-matrices. The relation to other well-known classes such as ω and τ-matrices and weakly sign symmetric matrices is examined, and invariance properties are shown.     

Error bounds for linear complementarity problems of DB-matrices

Doubly B-matrices (DB-matrices), which properly contain B-matrices, are introduced by Peña (2003) [2]. In this paper we present error bounds for the linear complementarity problem when the matrix involved is a DB-matrix and a new bound for linear complementarity problem of a B-matrix. The numerical examples show that the bounds are sharp.     

A comparison of error bounds for linear complementarity problems of H-matrices

We give new error bounds for the linear complementarity problem when the involved matrix is an H-matrix with positive diagonals. We find classes of H-matrices for which the new bounds improve considerably other previous bounds. We also show advantages of these new bounds with respect the computational cost. A new perturbation bound of H-matrices linear complementarity problems is also presented.     

The Kahan S.O.R. convergence bound for nonsingular and irreducible M-matrices

Let A be a nonsingular M-matrix, and let π be a block partitioning of A such that the diagonal blocks are square. Denote by J^A_π and

^A_πω the block Jacobi and the block S.O.R. iteration matrices arising from and associated with the partitioning π of A, respectively. In [5] Kahan showed that ρ (

^A_πω<1 for all 0<ω<ω':=2/[1+ρ(J^A_π)]. Under the assumption that J^A_π is irreducible we examine the question of when ρ(

^A_πω')=1 for certain recurring M-matrices.     

An application of sensitivity analysis to a linear programming problem

Summary In an ordinary linear programming problem with a given set of statistical data, it is not known generally how reliable is the optimal basic solution. Our object here is to indicate a general method of reliability analysis for testing the sensitivity of the optimal basic solution and other basic solutions, in terms of expectation and variance when sample observations are available. For empirical illustration the time series data on input-output coefficients of a single farm producing three crops with three resources is used. The distributions of the first, second, and third best solutions are estimated assuming the vectors of net prices and resources to be constant and the coefficient matrix to be stochastic. Our method of statistical estimation is a combination of the Pearsonian method of moments and the maximum likelihood method.In our illustrative example we observe that the skewness of the distribution of the first best solution exceeds that of the distributions of the second and third best solution. We have also analyzed the time paths for the three ordered solutions to see how far one could apply the idea of a regression model based on inequality constraints. A sensitivity index for a particular sample is suggested based on the spread of the maximum and minimum values of the solutions.

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Zusammenfassung Im allgemeinen ist bei Linear-Programming-Problemen mit statistischen Einflüssen die Zuverlässigkeit der optimalen Basislösung nicht bekannt. Unser Ziel ist es, eine allgemeine Methode anzugeben, um die Empfindlichkeit der optimalen Basislösung und anderer Basislösungen durch den Erwartungswert und die Varianz bei gegebener Stichprobe zu testen. Zur Illustration wird eine Zeitreihe der input-output-Koeffizienten einer einzigen Farm benutzt, die drei Getreidesorten erzeugt, wobei drei Ressourcen benützt werden. Es werden die Verteilungen der ersten drei besten Lösungen geschätzt bei vorausgesetzten konstanten Nettopreisen und Ressourcen und stochastischer Koeffizientenmatrix. Die verwendete Methode der statistischen Schätzung ist eine Kombination der Pearsonschen Momentenmethode und der Maximum-Likelihood-Methode.In unserem Beispiel stellen wir fest, daß die Schiefe der Verteilung der besten Lösung größer ist als die der Verteilung der zweit- und drittbesten Lösungen. Ferner wurden die Zeitläufe der ersten drei geordneten Lösungen analysiert, um festzustellen, wie weit sich die Idee eines Regressionsmodells, das auf Ungleichungsrestriktionen basiert, anwenden läßt. Für eine Stichprobe wird ein Empfindlichkeitsindex empfohlen, der sich aus der Spannweite der maximalen und minimalen Werte der Lösungen ableitet.

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Research partly supported by the NSF project No. 420-04-70 at the Department of Economics, Iowa State University, Ames.The results of this paper are closely related in some theoretical aspects to the following papers. Sengupta, J. K., G. Tintner andC. Millham. On some theorems of stochastic linear programming with applications, Management Science, vol. 10, October 1963, pp. 143–159. Sengupta, J. K., G. Tintner andB. Morrison. Stochastic linear programming with applications to economic models, Economica, August 1963, pp. 262–276. Sengupta, J. K.: On the stability of truncated solutions of stochastic linear programming (to be published in Econometrica, October, 1965).     

A control parametrization algorithm for optimal control problems involving linear systems and linear 1

Computational schemes based on control parametrization techniques are known to be very efficient for solving optimal control problems. However, the convergence result is only available for the case in which the dynamic system is linear and without the terminal equality and inequality constraints. This paper is to improve this convergence result by allowing the presence of the linear terminal inequality. For illustration, an example arising in the study of optimally one-sided heating of a metal slab in a furnace is considered.     

Doubly coprime representation of linear systems and its application to simultaneous stabilization

This paper develops a new representation theory of multivariabletime-invariant linear systems based on the well-known coprimefactorizations of their transfer matrices. This representationfully uses the algebraic structure of coprime factorizations,and hence has a number of advantages for describing variousproperties of linear systems in simpler and/or more compactforms than the usual transfer matrix representation. In theframework of this new representation theory, various stabilityand stabilizability properties of linear systems are characterizedand finally a simultaneous stabilization problem for a givenset of linear systems is examined.     

A linear mixed-integer model for a purchasing problem involving discount structures

In a recent paper a quadratic mixed-integer programming model was presented for an industrial purchasing problem involving complicated discount structures. The solution method presented in the paper for this model involved the solution of a series of quadratic zero-one programming problems. The disadvantages of such an approach are immediately obvious to anyone familiar with the state-of-the-art of solution methods for nonlinear integer programming problems. In this paper a linear model is constructed for the same problem and its computational advantages over the nonlinear model are discussed.