|edoc-Server der Humboldt-Universität zu Berlin|
|Author(s):||Sanjay Mehrotra, Northwestern University, Evanston||Title:||Volumetric center method for stochastic convex programs using sampling|
|Date of Acceptance:||24.01.2000|
Stochastic Programming E-Print Series |
|Editors:||Julie L. Higle; Werner Römisch; Surrajeet Sen|
|Keywords (eng):||Stochastic Programming, Volumetric Center, Analytic Center, Interior PointMethods, Convex Programming|
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|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 technique to compute a subgradient. A near-central cut variant of VCM is developed, and for this method an approach to perform bulk cut translation, and adding multiple cuts is given. We show that by using near-central VCM the SCP can be solved to a desirable accuracy with any given probability. For the two-stage SCP the solution time is independent of the number of scenarios.|
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