A Unified Approach to Interior Point Algorithms for Linear Complementarity Problems

A Unified Approach to Interior Point Algorithms for Linear Complementarity Problems

by Masakazu Kojima, Nimrod Megiddo, Toshihito Noma, Akiko Yoshise
     
 

Following Karmarkar's 1984 linear programming algorithm,
numerous interior-point algorithms have been proposed for various mathematical programming problems such as linear programming, convex quadratic programming and convex programming in general. This monograph presents a study of interior-point algorithms for the linear complementarity problem (LCP) which is

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Overview

Following Karmarkar's 1984 linear programming algorithm,
numerous interior-point algorithms have been proposed for various mathematical programming problems such as linear programming, convex quadratic programming and convex programming in general. This monograph presents a study of interior-point algorithms for the linear complementarity problem (LCP) which is known as a mathematical model for primal-dual pairs of linear programs and convex quadratic programs. A large family of potential reduction algorithms is presented in a unified way for the class of LCPs where the underlying matrix has nonnegative principal minors
(P0-matrix). This class includes various important subclasses such as positive semi-definite matrices,
P-matrices, P*-matrices introduced in this monograph, and column sufficient matrices. The family contains not only the usual potential reduction algorithms but also path following algorithms and a damped Newton method for the LCP. The main topics are global convergence, global linear convergence,
and the polynomial-time convergence of potential reduction algorithms included in the family.

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Product Details

ISBN-13:
9783540545095
Publisher:
Springer Berlin Heidelberg
Publication date:
10/28/1991
Series:
Lecture Notes in Computer Science Series, #538
Edition description:
1991
Pages:
112
Product dimensions:
9.21(w) x 6.14(h) x 0.26(d)

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