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arXiv 2201.04165cs.DS
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用划分计算逼近子集和比

Approximating Subset Sum Ratio via Partition Computations

Giannis Alonistiotis, Antonis Antonopoulos, Nikolaos Melissinos, Aris Pagourtzis, Stavros Petsalakis, Manolis Vasilakis

摘要:

我们提出了一个新的FPTAS的子集和比问题,其中,给定一组整数,要求两个不相交的子集,使它们的总和之比尽可能接近$1$。我们的方案利用精确和近似算法来解决密切相关的分区问题,因此,在这些方面的任何进展-例如Bringmann和Nakos [SODA 2021]最近的改进-都将延续到我们的FPTAS。根据输入集$n$的大小与误差容限$\varepsilon$之间的关系,我们改进了Melissinos和Pagourtzis [COCOON 2018]的复杂度为$O(n^4 / \varepsilon)$的当前最佳算法。特别地,在我们提出的方案中的$n$的指数可以降低到$2$,这取决于所使用的分区算法。此外,虽然以$O((n + 1 / \varepsilon)^c)$形式表示的上述现有技术的复杂性具有恒定的$c = 5$,但我们的结果确定$c < 5$。

英文摘要:

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 Partition 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 Partition 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 $c < 5$.

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