Text summarization is an important problem since it has numerous applications. This problem has been extensively studied and many approaches have been pro-posed in the literature for its solution. One such interesting approach is that of posing summarization as an optimization problem and using genetic algorithms to solve this optimization problem. In this paper we present
elegant randomized algorithms for summarization based on sampling. Our experimental results show that our algorithms yield nearly the same accuracy as the genetic algorithms while significantly saving on time. We have employed data from Document Understanding Conference 2002 and 2004 (DUC-2002, DUC-2004) in our experiments