Multiparametric Linear Complementarity Problems

Author

Jones, Colin N. ; Morrari, Manfred

Author_Institution

Autom. Control Lab., Swiss Fed. Inst. of Technol., Zurich

fYear

2006

fDate

13-15 Dec. 2006

Firstpage

5687

Lastpage

5692

Abstract

The linear complementarity problem (LCP) is a general problem that unifies linear and quadratic programs and bimatrix games. In this paper, we present an efficient algorithm for the solution to multiparametric linear complementarity problems (pLCPs) that are defined by positive semi-definite matrices. This class of problems includes the multiparametric linear (pLP) and semi-definite quadratic programs (pQP), where parameters are allowed to appear linearly in the cost and the right hand side of the constraints. We demonstrate that the proposed algorithm is equal in efficiency to the best of current pLP and pQP solvers for all problems that they can solve, and yet extends to a much larger class

Keywords

linear programming; matrix algebra; quadratic programming; bimatrix games; linear programs; multiparametric linear complementarity problems; positive semidefinite matrices; semidefinite quadratic programs; Constraint optimization; Cost function; Current measurement; Inspection; Laboratories; Predictive models; Robustness; Sampling methods; USA Councils; Velocity measurement;

fLanguage

English

Publisher

ieee

Conference_Titel

Decision and Control, 2006 45th IEEE Conference on

Conference_Location

San Diego, CA

Print_ISBN

1-4244-0171-2

Type

conf

DOI

10.1109/CDC.2006.377797

Filename

4177564