Template-Type: ReDIF-Paper 1.0
Author-Name: Frenk, J.B.G.
Author-Name-Last: Frenk
Author-Name-First: Hans
Author-Name: Sturm, J.F.
Author-Name-Last: Sturm
Author-Name: Zhang, S.
Author-Name-Last: Zhang
Author-Name-First: Shuzhong
Title: An interior point subgradient method for linearly constrained nondifferentiable convex programming
Abstract: We propose in this paper an algorithm for solving linearly constrained nondifferentiable convex programming problems. This algorithm combines the ideas of the affine scaling method with the subgradient method. It is a generalization of the dual and interior point method for min-max problems proposed by Sturm and Zhang [J.F. Sturm and S. Zhang, A dual and interior point approach to solve convex min-max problems, in: D.-Z. Du and P.M. Pardalos eds., Minimax and Applications, (1995) 69-78, Kluwer]. In the new method, the search direction is obtained by projecting in a scaled space a subgradient of the objective function with a logarithmic barrier term. The stepsize choice is analogous to the stepsize choice in the usual subgradient method. Convergence of the method is established.
Creation-Date: 1996-01-01
Series: RePEc:ems:eureir
Number: EI 9612-/A
Keywords: affine scaling, interior point method, nondifferentiable convex programming, subgradient
Handle: RePEc:ems:eureir:1376