Numerical validation of solutions of linear complementarity problems

Summary. This paper proposes a validation method for solutions of linear complementarity problems. The validation procedure consists of two sufficient conditions that can be tested on a digital computer. If the first condition is satisfied then a given multidimensional interval centered at an approximate solution of the problem is guaranteed to contain an exact solution. If the second condition is satisfied then the multidimensional interval is guaranteed to contain no exact solution. This study is based on the mean value theorem for absolutely continuous functions and the reformulation of linear complementarity problems as nonsmooth nonlinear systems of equations.

[1]  O. Mangasarian Equivalence of the Complementarity Problem to a System of Nonlinear Equations , 1976 .

[2]  O. Mangasarian Solution of symmetric linear complementarity problems by iterative methods , 1977 .

[3]  G. Stewart The Efficient Generation of Random Orthogonal Matrices with an Application to Condition Estimators , 1980 .

[4]  G. Alefeld,et al.  Introduction to Interval Computation , 1983 .

[5]  F. Clarke Optimization And Nonsmooth Analysis , 1983 .

[6]  Michael Minkoff,et al.  Randomly Generated Test Problems for Positive Definite Quadratic Programming , 1984, TOMS.

[7]  A. Neumaier,et al.  Interval Slopes for Rational Functions and Associated Centered Forms , 1985 .

[8]  Katta G. Murty,et al.  Linear complementarity, linear and nonlinear programming , 1988 .

[9]  W. Deren,et al.  On the optimal properties of the krawczyk-type interval operator∗ , 1989 .

[10]  A. Frommer,et al.  On the R -order of Newton-like methods for enclosing solutions of nonlinear equations , 1990 .

[11]  E T. Leighton,et al.  Introduction to parallel algorithms and architectures , 1991 .

[12]  F. Leighton,et al.  Introduction to Parallel Algorithms and Architectures: Arrays, Trees, Hypercubes , 1991 .

[13]  Eldon Hansen,et al.  Global optimization using interval analysis , 1992, Pure and applied mathematics.

[14]  G. Isac Complementarity Problems , 1992 .

[15]  A. Fischer A special newton-type optimization method , 1992 .

[16]  Ulrich W. Kulisch,et al.  Numerical Toolbox for Verified Computing I , 1993 .

[17]  Jong-Shi Pang,et al.  Nonsmooth Equations: Motivation and Algorithms , 1993, SIAM J. Optim..

[18]  F. Potra,et al.  Efficient numerical validation of solutions of nonlinear systems , 1994 .

[19]  S. Rump Verification methods for dense and sparse systems of equations , 1994 .

[20]  Siegfried M. Rump Expansion and estimation of the range of nonlinear functions , 1996, Math. Comput..

[21]  R. B. Kearfott Rigorous Global Search: Continuous Problems , 1996 .

[22]  Stephen J. Wright Primal-Dual Interior-Point Methods , 1997, Other Titles in Applied Mathematics.

[23]  Xiaojun Chen,et al.  Random test problems and parallel methods for quadratic programs and quadratic stochastic programs , 2000 .

[24]  K. G. Murty,et al.  Complementarity problems , 2000 .