A new pivoting algorithm for the linear complementarity problem allowing for an arbitrary starting point

The linear complementarity problem is to find nonnegative vectors which are affinely related and complementary. In this paper we propose a new complementary pivoting algorithm for solving the linear complementarity problem as a more efficient alternative to the algorithms proposed by Lemke and by Talman and Van der Heyden. The algorithm can start at an arbitrary nonnegative vector and converges under the same conditions as Lemke's algorithm.This research is part of the VF-program Competition and Cooperation.     

A short proof of finiteness of Murty's principal pivoting algorithm

We give a short proof of the finiteness of Murty's principal pivoting algorithm for solving the linear complementarity problemy = Mz + q, y ^T z = 0,y 0,z 0 withP-matrixM.     

A constructive characterization ofQ o-matrices with nonnegative principal minors

In [2] we characterized the class of matrices with nonnegative principla minors for which the linear-complementarity problem always has a solution. That class is contained in the one we study here. Our main result gives a finitely testable set of necessary and sufficient conditions under which a matrix with nonnegative principal minors has the property that if a corresponding linear complementarity problem is feasible then it is solvable. In short, we constructively characterize the matrix class known asQ _o ∩P _o . Research partially supported by the National Science Foundation Grant DMS-8420623 and U.S. Department of Energy Contract DE-AA03-76SF00326, PA # DE-AS03-76ER72018.     

GAUSSIAN PIVOTING METHOD FORSOLVING LINEAR COMPLEMENTARITY PROBLEM

In this paper, a new direct algorithm for solving linear complementarity problem with Z-matrix is proposed. The algorithm exhibits either a solution or its nonexistence after at most n steps (where n is the dimension of the problem) and the computational complexity is at most 1/3n^2 O(n^2)     

On a “stability” in the linear complementarity problem

In this work we re-wrote the Linear Complementarity Problem in a formulation based on unknown projector operators. In particular, this formulation allows the introduction of a concept of “stability” that, in a certain way, might explain the way block pivotal algorithm performs.     

EXPONENTIAL TRICHOTOMY,ORTHOGONALITY CONDITION AND THEIR APPLICATION

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An exponential example for Terlaky's pivoting rule for the criss-cross simplex method

Recently T. Terlaky has proposed a new pivoting rule for the criss-cross simplex method for linear programming and he proved that his rule is convergent. In this note we show that the required number of iterations may be exponential in the number of variables and constraints of the problem.     

Graph polynomials from principal pivoting

The recursive computation of the interlace polynomial introduced by Arratia, Bollobás and Sorkin is defined in terms of a new pivoting operation on undirected simple graphs. In this paper, we interpret the new pivoting operation on graphs in terms of standard pivoting (on matrices). Specifically, we show that, up to swapping vertex labels, Arratia et al.'s pivoting operation on a graph is equivalent to a principal pivot transform on the graph's adjacency matrix, provided that all computations are performed in the Galois field F₂. Principal pivoting on adjacency matrices over F₂ has a natural counterpart on isotropic systems. Thus, our view of the interlace polynomial is closely related to the one by Aigner and van der Holst.The observations that adjacency matrices of undirected simple graphs are skew-symmetric in F₂ and that principal pivoting preserves skew-symmetry in all fields suggest to extend Arratia et al.'s pivoting operation to fields other than F₂. Thus, the interlace polynomial extends to polynomials on gain graphs, namely bidirected edge-weighted graphs whereby reversed edges carry non-zero weights that differ only by their sign. Extending a proof by Aigner and van der Holst, we show that the extended interlace polynomial can be represented in a non-recursive form analogous to the non-recursive form of the original interlace polynomial, i.e., the Martin polynomial.For infinite fields it is shown that the extended interlace polynomial does not depend on the (non-zero) gains, as long as they obey a non-singularity condition. These gain graphs are all supported by a single undirected simple graph. Thus, a new graph polynomial is defined for undirected simple graphs. The recursive computation of the new polynomial can be done such that all ends of the recursion correspond to independent sets. Moreover, its degree equals the independence number. However, the new graph polynomial is different from the independence polynomial.     

An algorithm for the linear complementarity problem with upper and lower bounds

In this paper, we adapt the octahedral simplicial algorithm for solving systems of nonlinear equations to solve the linear complementarity problem with upper and lower bounds. The proposed algorithm generates a piecewise linear path from an arbitrarily chosen pointz ⁰ to a solution point. This path is followed by linear programming pivot steps in a system ofn linear equations, wheren is the size of the problem. The starting pointz ⁰ is left in the direction of one of the 2 ⁿ vertices of the feasible region. The ray along whichz ⁰ is left depends on the sign pattern of the function value atz ⁰. The sign pattern of the linear function and the location of the points in comparison withz ⁰ completely govern the path of the algorithm.This research is part of the VF-Program Equilibrium and Disequilibrium in Demand and Supply, approved by the Netherlands Ministry of Education, Den Haag, The Netherlands.     

Fully copositive matrices

The class of fully copositive (C ₀ ^f ) matrices introduced in [G.S.R. Murthy, T. Parthasarathy, SIAM Journal on Matrix Analysis and Applications 16 (4) (1995) 1268–1286] is a subclass of fully semimonotone matrices and contains the class of positive semidefinite matrices. It is shown that fully copositive matrices within the class ofQ ₀-matrices areP ₀-matrices. As a corollary of this main result, we establish that a bisymmetricQ ₀-matrix is positive semidefinite if, and only if, it is fully copositive. Another important result of the paper is a constructive characterization ofQ ₀-matrices within the class ofC ₀ ^f . While establishing this characterization, it will be shown that Graves's principal pivoting method of solving Linear Complementarity Problems (LCPs) with positive semidefinite matrices is also applicable toC ₀ ^f Q ₀ class. As a byproduct of this characterization, we observe that aC ₀ ^f -matrix is inQ ₀ if, and only if, it is completelyQ ₀. Also, from Aganagic and Cottle's [M. Aganagic, R.W. Cottle, Mathematical Programming 37 (1987) 223–231] result, it is observed that LCPs arising fromC ₀ ^f Q ₀ class can be processed by Lemke's algorithm. © 1998 The Mathematical Programming Society, Inc. Published by Elsevier Science B.V.Corresponding author.     

An investigation of interior-point and block pivoting algorithms for large-scale symmetric monotone linear complementarity problems

In this paper we describe a computational study of block principal pivoting (BP) and interior-point predictor-corrector (PC) algorithms for the solution of large-scale linear complementarity problems (LCP) with symmetric positive definite matrices. This study shows that these algorithms are in general quite appropriate for this type of LCPs. The BP algorithm does not seem to be sensitive to bad scaling and degeneracy of the unique solution of the LCP, while these aspects have some effect on the performance of the PC algorithm. On the other hand, the BP method has not performed well in two LCPs with ill-conditioned matrices for which the PC algorithm has behaved quite well.A hybrid algorithm combining these two techniques is also introduced and seems to be the most robust procedure for the solution of large-scale LCPs with symmetric positive definite matrices.Support of this work has been provided by the Instituto de Telecomunicações.     

Sign reversing and matrix classes

The concept of sign reversing is a useful tool to characterize certain matrix classes in linear complementarity problems. In this paper, we characterize the sign-reversal set of an arbitrary square matrixM in terms of the null spaces of the matricesI–⁁+⁁M, where ⁁ is a diagonal matrix such that 0⁁I. These matrices are used to characterize the membership ofM in the classes P₀, P, and the class of column-sufficient matrices. A simple proof of the Gale and Nikaido characterization theorem for the membership in P is presented.We also study the class of diagonally semistable matrices. We prove that this class is contained properly in the class of sufficient matrices. We show that to characterize the diagonally semistable property is equivalent to solving a concave Lagrangian dual problem. For 2×2 matrices, there is no duality gap between a primal problem and its Lagrangian problem. Such a primal problem is motivated by the definition of column sufficiency.The author would like to thank Professor Richard W. Cottle for his helpful comments on earlier versions of this paper. The author would also like to thank an anonymous referee for numerous helpful comments on this paper.     

On local w-uniqueness of solutions to linear complementarity problem

We introduce the classes of column (row) competent matrices and prove that the local w-uniqueness of solutions to linear complementarity problem can be completely characterized by column competent matrices.     

The combinatorics of pivoting for the maximum weight clique

In this paper we prove the equivalence between a pivoting-based heuristic (PBH) for the maximum weight clique problem and a combinatorial greedy heuristic. It is also proved that PBH always returns a local solution although this is not always guaranteed for Lemke's method, on which PBH is based.     

Zum satz von ljapunov in vektorverbänden

Let K be a closed convex order-bounded set of an order-complete vector lattice and let A be a him continuous linear operator. Then the equality AK = A(ext K) is proved, where ext K is the set of all extremal points of K. It is shown that various generalizations of the Ljapunov-theorem on the range of vector-measures are special cases of this general statement.     

A new method for a class of linear variational inequalities

In this paper we introduce a new iterative scheme for the numerical solution of a class of linear variational inequalities. Each iteration of the method consists essentially only of a projection to a closed convex set and two matrix-vector multiplications. Both the method and the convergence proof are very simple.This work is supported by the National Natural Science Foundation of the P.R. China and NSF of Jiangsu.     

A note on the convergence of the MSMAOR method for linear complementarity problems

Modulus‐based splitting, as well as multisplitting iteration methods, for linear complementarity problems are developed by Zhong‐Zhi Bai. In related papers (see Bai, Z.‐Z., Zhang, L.‐L.: Modulus‐Based Synchronous Multisplitting Iteration Methods for Linear Complementarity Problems. Numerical Linear Algebra with Applications 20 (2013) 425–439, and the references cited therein), the problem of convergence for two‐parameter relaxation methods (accelerated overrelaxation‐type methods) is analyzed under the assumption that one parameter is greater than the other. Here, we will show how we can avoid this assumption and, consequently, improve the convergence area. Copyright © 2013 John Wiley & Sons, Ltd.     

Robustness and nondegenerateness for linear complementarity problems

In this paper the main focus is on a stability concept for solutions of a linear complementarity problem. A solution of such a problem is robust if it is stable against slight perturbations of the data of the problem. Relations are investigated between the robustness, the nondegenerateness and the isolatedness of solutions. It turns out that an isolated nondegenerate solution is robust and also that a robust nondegenerate solution is isolated. Since the class of linear complementarity problems with only robust solutions or only nondegenerate solutions is not an open set, attention is paid to Garcia's classG _n of linear complementarity problems. The nondegenerate problems inG _n form an open set.     

A new polynomial time method for a linear complementarity problem

The purpose of this paper is to present a new polynomial time method for a linear complementarity problem with a positive semi-definite matrix. The method follows a sequence of points. If we generate the sequence on a path, we can construct a path following method, and if we generate the sequence based on a potential function, we can construct a potential reduction method. The method has the advantage that it requires at most iterations for any initial feasible point whose components lie between 2^–O(L) and 2^O(L).Research was supported in part by Grant-in-Aids for Encouragement of Young Scientists (63730014) and for General Scientific Research (63490010) of The Ministry of Education, Science and Culture.