In this paper, we introduce the technique of geometric amortization for enumeration algorithms. This technique can be used to make the delay of enumeration algorithms more regular without much overhead on the space it uses. More precisely, we are interested in enumeration algorithms having incremental linear delay, that is, algorithms enumerating a set $A$ of size $K$ such that for every $t \leq K$, it outputs at least $t$ solutions in time $O(tp)$, where $p$ is the incremental delay of the algorithm. While it is folklore that one can transform such an algorithm into an algorithm with delay $O(p)$, the naive transformation may blow the space exponentially. We show that, using geometric amortization, such an algorithm can be transformed into an algorithm with delay $O(p\log K)$ and $O(s\log K)$ space, where $s$ is the space used by the original algorithm. We apply geometric amortization to show that one can trade the delay of flashlight search algorithms for their average delay modulo a factor of $O(\log K)$. We illustrate how this tradeoff may be advantageous for the enumeration of solutions of DNF formulas.
翻译:在本文中, 我们引入了用于查点算法的几何摊还法技术。 这个技术可以用来使查算算法的拖延更加常规化, 而不必花费它所使用的空间。 更确切地说, 我们感兴趣的是, 查算算算法具有递增线性延迟, 也就是说, 算算法计算出一套数额为K美元的固定美元, 这样每1美元美元, 它至少能产生美元为美元( tp) 的解决方案, 其中美元为递增算法的递延延时间。 虽然人们可以将这种算法转换成一种有延迟的算法而无需花费O( p) 美元, 但天候变迁可能会使空间发生急剧的爆炸。 我们表明, 使用几何比例的摊算法, 这种算法可以转换成一种有延迟的算法, $( p\ log) 美元 和 $( slog K) 美元空间, 其中美元是原始算法所使用的空间。 我们应用几何配法来表明, 闪光搜索算算法的延迟性算算算算算算算算算算算算算算算算算算算算算算算算算算算算算算算算算算算算算算算算算算算算算算算算算算算算算算算算算算算算。 我们算算算算算算算算算算算算算算算算算算算算算算算算算算算算算算算算算算算算算算算算算算算算算算算算算算算算算算算算算算算算算算算算算算算算算算算算算算。 。