Name
Title | ||
|---|---|---|
Decomposition Based Interior Point Methods for Two-Stage Stochastic Convex Quadratic Programs with Recourse |
Abstract | ||
|---|---|---|
Zhao 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-stage solutions. In this paper, we show that the recourse function is also strongly self-concordant and forms a self-concordant family for the two-stage stochastic convex quadratic programs with recourse. This allows us to develop Bender's decomposition based linearly convergent interior point algorithms. An analysis of such an algorithm is given in this paper. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1287/opre.1080.0659 | Operations Research |
Keywords | Field | DocType |
linearly convergent interior point,recourse function,interior point methods,self-concordant family,two-stage stochastic convex quadratic,two-stage stochastic linear program,log barrier,self-concordant barrier,first-stage solution,interior point method,linear program | Mathematical optimization,Quadratic equation,Decomposition method (constraint satisfaction),Regular polygon,Linear programming,Quadratic programming,Interior point method,Convex optimization,Stochastic programming,Mathematics | Journal |
Volume | Issue | ISSN |
57 | 4 | 0030-364X |
Citations | PageRank | References |
10 | 0.78 | 17 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sanjay Mehrotra | 1 | 521 | 77.18 |
| M. Gokhan Ozevin | 2 | 10 | 0.78 |