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2005
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How to Pay, Come What May: Approximation Algorithms for Demand-Robust Covering Problems

8 years 9 months ago
How to Pay, Come What May: Approximation Algorithms for Demand-Robust Covering Problems
Robust optimization has traditionally focused on uncertainty in data and costs in optimization problems to formulate models whose solutions will be optimal in the worstcase among the various uncertain scenarios in the model. While these approaches may be thought of defining data- or cost-robust problems, we formulate a new “demand-robust” model motivated by recent work on two-stage stochastic optimization problems. We propose this in the framework of general covering problems and prove a general structural lemma about special types of first-stage solutions for such problems: there exists a first-stage solution that is a minimal feasible solution for the union of the demands for some subset of the scenarios and its objective function value is no more than twice the optimal. We then provide approximation algorithms for a variety of standard discrete covering problems in this setting, including minimum cut, minimum multi-cut, shortest paths, Steiner trees, vertex cover and un-capa...
Kedar Dhamdhere, Vineet Goyal, R. Ravi, Mohit Sing
Added 24 Jun 2010
Updated 24 Jun 2010
Type Conference
Year 2005
Where FOCS
Authors Kedar Dhamdhere, Vineet Goyal, R. Ravi, Mohit Singh
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