%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