%0 Conference Paper
%B Proceedings of the eighteenth annual ACM-SIAM symposium on Discrete algorithms
%D 2007
%T Approximation algorithms for stochastic and risk-averse optimization
%A Srinivasan, Aravind
%X We present improved approximation algorithms in stochastic optimization. We prove that the multi-stage stochastic versions of covering integer programs (such as set cover and vertex cover) admit essentially the same approximation algorithms as their standard (non-stochastic) counterparts; this improves upon work of Swamy & Shmoys that shows an approximability which depends multiplicatively on the number of stages. We also present approximation algorithms for facility location and some of its variants in the 2-stage recourse model, improving on previous approximation guarantees.
%B Proceedings of the eighteenth annual ACM-SIAM symposium on Discrete algorithms
%S SODA '07
%I Society for Industrial and Applied Mathematics
%C Philadelphia, PA, USA
%P 1305 - 1313
%8 2007///
%@ 978-0-898716-24-5
%G eng
%U http://dl.acm.org/citation.cfm?id=1283383.1283523