Browsing by Author "Mehrotra, Sanjay"

Now showing items 1-6 of 6

2008-07-05Buch

Convergence Analysis of a Weighted Barrier Decomposition Algorithm for Two Stage Stochastic Programming

Mehrotra, Sanjay; Ozevin, M. Gokhan

Mehrotra and Ozevin [7] computationally found that a weighted primal barrier decomposition algorithm signiﬁcantly outperforms the barrier decomposition proposed and analyzed in [11; 6; 8]. Thispaper provides a theoretical ...
2004-04-20Buch

Decomposition-based interior point methods for two-stage stochastic convex quadratic programs with recourse

Mehrotra, Sanjay; Ozevin, M. Gokhan

Zhao [28] recently showed that the log barrier associated with the recourse function of two-stage stochastic linear programs behaves as a strongly self-concordant barrier and forms a self concordant family on the first ...
2008-04-05Buch

Epi-convergent scenario generation method for stochastic problems via sparse grid

Chen, Michael; Mehrotra, Sanjay

One central problem in solving stochastic programming problems is to generate moderate-sized scenario trees which represent well the risk faced by a decision maker. In this paper we propose an efﬁcient scenario generation ...
2007-07-08Buch

Self-concordant Tree and Decomposition Based Interior Point Methods for Stochastic Convex Optimization Problem

Chen, Michael; Mehrotra, Sanjay

We consider barrier problems associated with two and multistage stochastic convex optimization problems. We show that the barrier recourse functions at any stage form a self-concordant family with respect to the barrier ...
2005-03-11Buch

Two-stage stochastic semidefinite programming and decomposition based interior point methods

Mehrotra, Sanjay; Özevin, M. Gökhan

We introduce two stage stochastic semidefinite programs with recourse and present a Benders decomposition based linearly convergent interior point algorithm to solve them. This extends the results in Zhao [16] wherein it ...
2000-01-24Buch

Volumetric center method for stochastic convex programs using sampling

Mehrotra, Sanjay

We develop an algorithm for solving the stochastic convex program (SCP) by combining Vaidya's volumetric center interior point method (VCM) for solving non-smooth convex programming problems with the Monte-Carlo sampling ...