In this paper, we show an analysis about approximated winner determination algorithms for iteratively conducted combinatorial auctions. Our algorithms are designed to effectively reuse last-cycle solutions to speed up the initial approximation performance on the next cycle. Experimental results show that our proposed algorithms outperform existing algorithms when a large number of similar bids are contained through iterations. Also, we show an enhanced algorithm effectively avoids undesirable reuses of the last solutions in the algorithm without serious computational overheads.