A decomposition-based warm-start method for stochastic programming
Abstract: In this paper we propose a warm-start technique for interior point methods applicable to multi-stage stochastic programming problems. The main idea is to generate an initial point for the interior point solver by decomposing the barrier problem associated with the deterministic equivalent at the sec- ond stage and using a concatenation of the solutions of the subproblems as a starting point for the complete instance. We analyse this scheme and produce theoretical conditions under which the warm-start iterate is successful. We describe the implementation within the OOPS solver and the results of the numerical tests we performed.
Keywords: Stochastic Programming, Interior Point Methods, Warm-starting
Category 1: Stochastic Programming
Citation: Technical Report ERGO 09-008, School of Mathematics, The University of Edinburgh, Edinburgh EH9 3JZ, UK. July 2009, revised April 2010.
Entry Submitted: 04/01/2010
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