A Computational Study of the Homogeneous Algorithm for Large-Scale Convex Optimization

A Computational Study of the Homogeneous Algorithm for Large-Scale Convex Optimization (1997)

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by Erling D. Andersen , Yinyu Ye

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Datum	Value	Source
TITLE	A Computational Study of the Homogeneous Algorithm for Large-Scale Convex Optimization	user correction - Legacy Corrections
AUTHOR NAME	Erling D. Andersen	SVM HeaderParse 0.1
AUTHOR AFFIL	Department of Management, Odense University	SVM HeaderParse 0.2
AUTHOR ADDR	Campusvej 55, DK-5230 Odense M, Denmark.	SVM HeaderParse 0.1
AUTHOR NAME	Yinyu Ye	SVM HeaderParse 0.1
AUTHOR AFFIL	y; Department of Management Sciences, The University of Iowa	SVM HeaderParse 0.2
AUTHOR ADDR	Iowa City, Iowa 52242, USA.	SVM HeaderParse 0.1
ABSTRACT	Recently the authors have proposed a homogeneous and self-dual algorithm for solving the monotone complementarity problem (MCP) [5]. The algorithm is a single phase interior-point type method, nevertheless it yields either an approximate optimal solution or detects a possible infeasibility of the problem. In this paper we specialize the algorithm to the solution of general smooth convex optimization problems that also possess nonlinear inequality constraints and free variables. We discuss an implementation of the algorithm for large-scale sparse convex optimization. Moreover, we present computational results for solving quadratically constrained quadratic programming and geometric programming problems, where some of the problems contain more than 100,000 constraints and variables. The results indicate that the proposed algorithm is also practically efficient. Department of Management, Odense University, Campusvej 55, DK-5230 Odense M, Denmark. E-mail: eda@busieco.ou.dk y ...	user correction - Legacy Corrections
YEAR	1997	user correction - Legacy Corrections
CITATIONS	50 found	ParsCit 1.0