High utility itemset mining (HUIM) is a hot research topic andhas been extensively studied in the literature. In this paper,we study the problem of HUIM with multiple minimum utility thresholds, and develop an efficient algorithm named FHUIM. A comprehensive empirical study shows that FHUIM significantly outperforms the state-of-the-art algorithm MHUI in terms of runtime, memory consumption and number of candidates.