Solving more linear complementarity problems with Murty's bard-type algorithm

The linear complementarity problem (M|q) is to findw andz inR ⁿ such thatw–Mz=q,w0,z0,w ^t z=0, givenM inR ^n×n andq in . Murty's Bard-type algorithm for solving LCP is modeled as a digraph.Murty's original convergence proof considered allq inR ⁿ andM inR ^n×n , aP-matrix. We show how to solve more LCP's by restricting the set ofq vectors and enlarging the class ofM matrices beyondP-matrices. The effect is that the graph contains an embedded graph of the type considered by Stickney and Watson wheneverM is a matrix containing a principal submatrix which is aP-matrix. Examples are presented which show what can happen when the hypotheses are further weakened.     

Existence and uniqueness of solutions for the generalized linear complementarity problem

Cottle and Dantzig (Ref. 1) showed that the generalized linear complementarity problem has a solution for anyqR ^m ifM is a vertical blockP-matrix of type (m ₁,...,m _n ). They also extended known characterizations of squareP-matrices to vertical blockP-matrices.Here we show, using a technique similar to Murty's (Ref. 2), that there exists a unique solution for anyqR ^m if and only ifM is a vertical blockP-matrix of type (m ₁,...,m _n ). To obtain this characterization, we employ a generalization of Tucker's theorem (Ref. 3) and a generalization of a theorem initially introduced by Gale and Nikaido (Ref. 4).     

An infeasible-interior-point algorithm for linear complementarity problems

We modify the algorithm of Zhang to obtain anO(n²L) infeasible-interior-point algorithm for monotone linear complementarity problems that has an asymptoticQ-subquadratic convergence rate. The algorithm requires the solution of at most two linear systems with the same coefficient matrix at each iteration.This research was supported by the Office of Scientific Computing, U.S. Department of Energy, under Contract W-31-109-Eng-38.     

Degeneracy in linear complementarity problems: a survey

Given a square matrixM of ordern and a vectorq ⁿ , the linear complementarity problem is the problem of either finding aw ⁿ and az ⁿ such thatw–Mz=q,w0,z0 andw ^T z=0 or showing that no such (w, z) exists. This problem is denoted asLCP(q, M). We say that a solution (w, z) toLCP(q, M) is degenerate if the number of positive coordinates in (w, z) is less thann. As in linear programming, degeneracy may cause cycling in an adjacent vertex following methods like Lemke's algorithm. Moreover, ifLCP(0,M) has a nontrivial solution, a condition related to degeneracy, then unless certain other conditions are satisfied, the algorithm may not be able to decide about the solvability of the givenLCP(q, M). In this paper we review the literature on the implications of degeneracy to the linear complementarity theory.     

An improvement of the error bounds for linear complementarity problems of Nekrasov matrices

A new error bound for the linear complementarity problems, which involves a parameter, is given when the involved matrices are Nekrasov matrices. It is shown that there exists an optimal value of the parameter such that the new bound is sharper than that provided by Li et al. (Numer Algor. 2017;74:997–1009). Numerical examples are given to illustrate the corresponding results.     

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.     

Generalized linear complementarity problems

It has been shown by Lemke that if a matrix is copositive plus on ⁿ , then feasibility of the corresponding linear complementarity problem implies solvability. In this article we show, under suitable conditions, that feasibility of ageneralized linear complementarity problem (i.e., defined over a more general closed convex cone in a real Hilbert space) implies solvability whenever the operator is copositive plus on that cone. We show that among all closed convex cones in a finite dimensional real Hilbert Space, polyhedral cones are theonly ones with the property that every copositive plus, feasible GLCP is solvable. We also prove a perturbation result for generalized linear complementarity problems.This research has been partially supported by the Air Force Office of Scientific Research under grants #AFOSR-82-0271 and #AFOSR-87-0350.     

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.     

Robust solutions to uncertain linear complementarity problems

In this paper,we adopt the robust optimization method to consider linear complementarity problems in which the data is not specified exactly or is uncertain,and it is only known to belong to a prescribed uncertainty set.We propose the notion of the p- robust counterpart and the p-robust solution of uncertain linear complementarity problems.We discuss uncertain linear complementarity problems with three different uncertainty sets,respectively,including an unknown-but-bounded uncertainty set,an ellipsoidal uncertainty set and an intersection-of-ellipsoids uncertainty set,and present some sufficient and necessary(or sufficient) conditions which p- robust solutions satisfy.Some special cases are investigated in this paper.     

A note on a quadratic formulation for linear complementarity problems

In this note, we discuss some properties of a quadratic formulation for linear complementarity problems. Projected SOR methods proposed by Mangasarian apply to symmetric matrices only. The quadratic formulation discussed here makes it possible to use these SOR methods for solving nonsymmetric LCPs. SOR schemes based on this formulation preserve sparsity. For proper choice of a free parameter, this quadratic formulation also preserves convexity. The value of the quadratic function for the solution of original LCP is also known.     

<Emphasis FontCategory="NonProportional">L</Emphasis>-Matrices and solvability of linear complementarity problems by a linear program-Matrices and solvability of linear complementarity problems by a linear program

The classes ofL ₁-matrices,L ₂-matrices,L ₃-matrices andW-matrices are introduced to study solvability of a linear complementarity problem via solving a linear program. Three sufficient conditions are presented to guarantee that a linear complementarity problem is solvable via a linear program. The new sufficient conditions are weaker than the ones introduced by Mangasarian. This fact is also illustrated by an example. Partially supported by NSFC. This author is also with College of Business Administration of Human University as a Lotus chair professor.     

A note on solvability of a class of linear complementarity problems

We give a characterization of unique solvability of an infinite family of linear complementarity problems of a special form by means of a finite subset of this family.     

Infeasible-interior-point paths for sufficient linear complementarity problems and their analyticity

In this paper we study the behavior of infeasible-interior-point-paths for solving horizontal linear complementarity problems that are sufficient in the sense of Cottle et al. (R. W. Cottle, J.-S. Pang, Venkateswaran, Linear Algebra Appl. 114/115 (1989) 231–249). We show that these paths converge to a central point of the set of solutions. It is also shown that these are analytic functions of the path parameter even at the limitpoint, if the complementarity problem has a strictly complementary solution, and have a simple branchpoint, if it is solveable, but has no strictly complementarity solution.     

Multiple-objective approximation of feasible but unsolvable linear complementarity problems

Using a multiple-objective framework, feasible linear complementarity problems (LCPs) are handled in a unified manner. The resulting procedure either solves the feasible LCP or, under certain conditions, produces an approximate solution which is an efficient point of the associated multiple-objective problem. A mathematical existence theory is developed which allows both specialization and extension of earlier results in multiple-obkective programming. Two perturbation approaches to finding the closest solvable LCPs to a given unsolvable LCP are proposed. Several illustrative examples are provided and discussed.     

On computer-assisted proofs for solutions of linear complementarity problems

In this paper we consider the linear complementarity problem where the components of the input data M and q are not exactly known but can be enclosed in intervals. We compare three tests to each other each of which can be used by a computer that supports interval arithmetic to give guaranteed bounds for a solution of the LCP defined by M and q.     

Basic-set algorithm for a generalized linear complementarity problem

In this paper, the authors develop a new direct method for the solution of a BLCP, that is, a linear complementarity problem (LCP) with upper bounds, when its matrix is a symmetric or an unsymmetricP-matrix. The convergence of the algorithm is established by extending Murty's principal pivoting method to an LCP which is equivalent to the BLCP. Computational experience with large-scale BLCPs shows that the basic-set method can solve efficiently large-scale BLCPs with a symmetric or an unsymmetricP-matrix.     

Error bounds for monotone linear complementarity problems

We give a bound on the distance between an arbitrary point and the solution set of a monotone linear complementarity problem in terms of a condition constant that depends on the problem data only and a residual function of the violations of the complementary problem conditions by the point considered. When the point satisfies the linear inequalities of the complementarity problem, the residual consists of the complementarity condition plus its square root. This latter term is essential and without it the error bound cannot hold. We also show that another natural residual that has been employed to bound errors for strictly monotone linear complementarity problems fails to bound errors for the monotone case considered here. Sponsored by the United States Army under contract No. DAAG29-80-C-0041. This material is based on research sponsored by National Foundation Grant DCR-8420963 and Air Force Office of Scientific Research Grant AFOSR-ISSA-85-00080.     

A superquadratic infeasible-interior-point method for linear complementarity problems

We consider a modification of a path-following infeasible-interior-point algorithm described by Wright. In the new algorithm, we attempt to improve each major iterate by reusing the coefficient matrix factors from the latest step. We show that the modified algorithm has similar theoretical global convergence properties to those of the earlier algorithm while its asymptotic convergence rate can be made superquadratic by an appropriate parameter choice. The work of this author was based on research supported by the Office of Scientific Computing, US Department of Energy, under Contract W-31-109-Eng-38. The work of this author was based on research supported in part by the US Department of Energy under Grant DE-FG02-93ER25171.     

Ky Fan's N-matrices and linear complementarity problems

We consider the linear complementarity problem (LCP),w=Az + q, w0,z0,w ^T z=0, when all the off-diagonal entries ofA are nonpositive (the class of Z-matrices), all the proper principal minors ofA are positive and the determinant ofA is negative (the class of almost P-matrices). We shall call this the class of F-matrices. We show that ifA is a Z-matrix, thenA is an F-matrix if and only if LCP(q, A) has exactly two solutions for anyq0,q0, and has at most two solutions for any otherq. Research supported by AFOSR-89-0512.     

A Newton-type method for positive-semidefinite linear complementarity problems

The paper presents a damped and perturbed Newton-type method for solving linear complementarity problems with positive-semidefinite matricesM. In particular, the following properties hold: all occurring subproblems are linear equations; each subproblem is uniquely solvable without any assumption; every accumulation point generated by the method solves the linear complementarity problem. The additional property ofM to be an R₀-matrix is sufficient, but not necessary, for the boundedness of the iterates. Provided thatM is positive definite on a certain subspace, the method converges Q-quadratically.The author would like to thank the anonymous referees and Dr. K. Schönefeld for their valuable comments and suggestions. He is also grateful to Prof. Dr. J. W. Schmidt for his continuous interest in this study.