A 4 3 -approximation for the maximum leaf spanning arborescence problem in DAGs.

IF 2.1 2区 数学 Q2 COMPUTER SCIENCE, SOFTWARE ENGINEERING
Mathematical Programming Pub Date : 2026-01-01 Epub Date: 2025-05-24 DOI:10.1007/s10107-025-02233-0
Meike Neuwohner
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引用次数: 0

Abstract

The Maximum Leaf Spanning Arborescence problem (MLSA) in directed acyclic graphs (dags) is defined as follows: Given a directed acyclic graph G and a vertex r ∈ V ( G ) from which every other vertex is reachable, find a spanning arborescence rooted at r maximizing the number of leaves (vertices with out-degree zero). The MLSA in dags is known to be APX-hard as reported by Nadine Schwartges, Spoerhase, and Wolff (Approximation and Online Algorithms, Springer, Berlin Heidelberg, 2012) and the best known approximation guarantee of 7 5 is due to Fernandes and Lintzmayer (J. Comput. Syst. Sci. 135: 158-174,2023): They prove that any α -approximation for the hereditary 3-set packing problem, a special case of weighted 3-set packing, yields a max { 4 3 , α } -approximation for the MLSA in dags, and provide a 7 5 -approximation for the hereditary 3-set packing problem. In this paper, we improve upon this result by providing a 4 3 -approximation for the hereditary 3-set packing problem, and, thus, the MLSA in dags. The algorithm that we study is a simple local search procedure considering swaps of size up to 10 and can be analyzed via a two-stage charging argument. We further provide a clear picture of the general connection between the MLSA in dags and set packing by rephrasing the MLSA in dags as a hereditary set packing problem. With a much simpler proof, we extend the reduction by Fernandes and Lintzmayer and show that an α -approximation for the hereditary k-set packing problem implies a max { k + 1 k , α } -approximation for the MLSA dags. On the other hand, we provide lower bound examples proving that our approximation guarantee of 4 3 is best possible for local search algorithms with constant improvement size.

dag中最大叶跨越乔木问题的43 - 3近似。
有向无环图(daags)中的最大叶子生成树形问题(MLSA)定义如下:给定一个有向无环图G和一个顶点r∈V (G),从该顶点r∈V (G)可以到达,找到一个根在r的生成树形,该生成树形使叶子(出度为0的顶点)的数量最大化。据Nadine Schwartges、Spoerhase和Wolff (Approximation and Online Algorithms, b施普林格,Berlin Heidelberg, 2012)报道,dags中的MLSA是APX-hard的,最著名的逼近保证是Fernandes和Lintzmayer (J. Comput)。系统。他们证明了遗传3集布局问题(加权3集布局的一种特殊情况)的任意α -逼近都能得到dag中MLSA的max {4.3, α} -逼近,并提供了遗传3集布局问题的一个75 -逼近。在本文中,我们改进了这一结果,为遗传的3集布局问题提供了一个4 - 3逼近,从而得到了袋中的MLSA。我们研究的算法是一个简单的局部搜索过程,考虑大小为10的交换,可以通过两阶段收费论证进行分析。我们进一步提供了一个清晰的画面之间的一般联系的MLSA在袋和集包装通过重新表述MLSA在袋作为一个遗传集包装问题。通过一个更简单的证明,我们扩展了Fernandes和Lintzmayer的简化,并证明了遗传k集填充问题的α -近似意味着MLSA包的max {k + 1k, α} -近似。另一方面,我们提供了下界例子,证明了我们的近似保证为43是局部搜索算法在改进规模恒定时的最佳可能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Mathematical Programming
Mathematical Programming 数学-计算机:软件工程
CiteScore
5.70
自引率
11.10%
发文量
160
审稿时长
4-8 weeks
期刊介绍: Mathematical Programming publishes original articles dealing with every aspect of mathematical optimization; that is, everything of direct or indirect use concerning the problem of optimizing a function of many variables, often subject to a set of constraints. This involves theoretical and computational issues as well as application studies. Included, along with the standard topics of linear, nonlinear, integer, conic, stochastic and combinatorial optimization, are techniques for formulating and applying mathematical programming models, convex, nonsmooth and variational analysis, the theory of polyhedra, variational inequalities, and control and game theory viewed from the perspective of mathematical programming.
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