Mining skyline frequent-utility patterns (SFUPs) is the discovery of itemsets that surpasses all other itemsets in both frequency and utility in transactional database. The discovery of these itemsets is important for managers in finding items that customers buy many times and bring high profits for businesses. In recent years, there have been many algorithms proposed to exploit skyline frequent-utility patterns, of which SKYFUP-D is the most efficient algorithm. However, this algorithm still has limitations in both execution time and storage space. In this paper, we propose an effective method to exploit SFUPs faster by applying pruning strategies to reduce the number of candidates. Experimental results show that the execution time and storage space are significantly improved.