We present a new FPTAS for the Subset Sum Ratio problem, which, given a set of integers, asks for two disjoint subsets such that the ratio of their sums is as close to $1$ as possible. Our scheme makes use of exact and approximate algorithms for the closely related Subset Sum problem, hence any progress over those -- such as the recent improvement due to Bringmann and Nakos [SODA 2021] -- carries over to our FPTAS. Depending on the relationship between the size of the input set $n$ and the error margin $\varepsilon$, we improve upon the best currently known algorithm of Melissinos and Pagourtzis [COCOON 2018] of complexity $O(n^4 / \varepsilon)$. In particular, the exponent of $n$ in our proposed scheme may decrease down to $2$, depending on the Subset Sum algorithm used. Furthermore, while the aforementioned state of the art complexity, expressed in the form $O((n + 1 / \varepsilon)^c)$, has constant $c = 5$, our results establish that $c < 5$.
翻译:我们为子设定总比率问题提出了一个新的FPTAS, 以一组整数为根据, 我们要求两个脱节子集, 使这些子集的比重尽可能接近1美元。 我们的计划使用精确和大致算法来解决密切相关的子集问题, 特别是, 我们的拟议办法中由于Bringmann和Nakos [SODA 2021] 带来的最近改善, 任何进展都将转移到我们的FPTAS。 取决于设定的输入量( $) 和差值( varepslon $ ) 之间的关系, 我们改进了目前已知的Melissinos 和 Pagourtzis [COON 2018] 最复杂的成本( $ (n) 4 /\ varepslon) 的算法。 特别是, 我们的拟议办法中扣除的美元可能下降到2美元,, 取决于所使用的子设置总算法。 此外, 以美元( + 1 /\ varepslon) = $ (c) 美元表示的上述复杂度状况, 我们的计算结果固定为5美元。