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Piecewise static policies for two-stage adjustable robust linear optimization problems under uncertainty

Omar El Housni(oe2148***at***columbia.edu)
Vineet Goyal(vg2277***at***columbia.edu)

Abstract: In this paper, we consider two-stage adjustable robust linear optimization problems under uncertain constraints and study the performance of piecewise static policies. These are a generalization of static policies where we divide the uncertainty set into several pieces and specify a static solution for each piece. We show that in general there is no piecewise static policy with a polynomial number of pieces that has a significantly better performance than an optimal static policy. This is quite surprising as piecewise static policies are significantly more general than static policies. The proof is based on a combinatorial argument and the structure of piecewise static policies.

Keywords: Robust Optimization, Adaptive Optimization, Piecewise Static Policies

Category 1: Robust Optimization

Citation:

Download: [PDF]

Entry Submitted: 11/30/2015
Entry Accepted: 11/30/2015
Entry Last Modified: 11/30/2015

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