如何包装比最佳适合:平均情况下的紧密边界在线箱包装

P. Shor
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引用次数: 38

摘要

给出了一种耗时O(n log n)的在线算法,用于将(0,1)上i.i.d uniform的物品打包到大小为1的箱子中,期望浪费空间为Theta (n/sup 1/2/ log /sup 1/2/n)。这与没有在线算法可以实现O(n/sup 1/2/ log /sup 1/2/ n)浪费空间的最低界限相匹配。它是通过分析另一种算法来完成的,该算法涉及将球在线放入桶中。第二种算法的分析还给出了随机向右匹配问题的界,该问题不仅在分析上述在线装箱问题时出现,而且在分析二维矩形装箱成半无限条问题时也会出现。因此,右匹配的边界为二维条形布局问题提供了良好的边界。
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How to pack better than best fit: tight bounds for average-case online bin packing
An O(n log n)-time online algorithm is given for packing items i.i.d. uniform on (0, 1) into bins of size 1 with expected wasted space Theta (n/sup 1/2/ log /sup 1/2/n). This matches the lowest bound that no online algorithm can achieve O(n/sup 1/2/ log /sup 1/2/ n) wasted space. It is done by analyzing another algorithm which involves putting balls into buckets online. The analysis of this second algorithm also gives bound on the stochastic rightward matching problem, which arises in analyzing not only the above online bin packing problem, but also a 2-D problem of packing rectangles into a half-infinite strip. The bounds on rightward matching thus give good bounds for the 2-D strip packing problem.<>
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