We discuss text summarization in terms of maximum coverage problem and its variant. We explore some decoding algorithms including the ones never used in this summarization formulation, such as a greedy algorithm with performance guarantee, a randomized algorithm, and a branch-andbound method. On the basis of the results of comparative experiments, we also augment the summarization model so that it takes into account the relevance to the document cluster.