Susumu Shindoh

Interior-Point Methods for the Monotone Semidefinite Linear Complementarity Problem in Symmetric Matrices

The SDLCP (semidefinite linear complementarity problem) in symmetric matrices introduced in this paper provides a unified mathematical model for various problems arising from systems and control theory and combinatorial optimization. It is defined as the problem of finding a pair

Local convergence of predictor--corrector infeasible-interior-point algorithms for SDPs and SDLCPs

(\X,\Y)

A Predictor-Corrector Interior-Point Algorithm for the Semidefinite Linear Complementarity Problem Using the Alizadeh--Haeberly--Overton Search Direction

of

Strongly Stable Equilibrium Points of N-Person Noncooperative Games

n \times n

Existence and Uniqueness of Search Directions in Interior-Point Algorithms for the SDP and the Monotone SDLCP

symmetric positive semidefinite matrices which lies in a given

A note on the Nesterov-Todd and the Kojima-Shindoh-hara search directions in semidefinite programming

n(n+1)/2

Centers of monotone generalized complementarity problems

dimensional affine subspace

Manifold Structure of the Karush–Kuhn–Tucker Stationary Solution Set with Two Parameters

\FC

Interior Point Methods for the Monotone Linear Complementarity Problem in Symmetric Matrices

of

Search directions in the SDP and the monotone SDLCP : generalization and inexact computation

\SC^2