Improved Approximation Algorithms by Generalizing the Primal-Dual Method Beyond Uncrossable Functions

IF 0.9 4区 计算机科学 Q4 COMPUTER SCIENCE, SOFTWARE ENGINEERING Algorithmica Pub Date : 2024-05-20 DOI:10.1007/s00453-024-01235-2
Ishan Bansal, Joseph Cheriyan, Logan Grout, Sharat Ibrahimpur
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Abstract

We address long-standing open questions raised by Williamson, Goemans, Vazirani and Mihail pertaining to the design of approximation algorithms for problems in network design via the primal-dual method (Williamson et al. in Combinatorica 15(3):435–454, 1995. https://doi.org/10.1007/BF01299747). Williamson et al. prove an approximation ratio of two for connectivity augmentation problems where the connectivity requirements can be specified by uncrossable functions. They state: “Extending our algorithm to handle non-uncrossable functions remains a challenging open problem. The key feature of uncrossable functions is that there exists an optimal dual solution which is laminar ... A larger open issue is to explore further the power of the primal-dual approach for obtaining approximation algorithms for other combinatorial optimization problems.” Our main result proves that the primal-dual algorithm of Williamson et al. achieves an approximation ratio of \(16\) for a class of functions that generalizes the notion of an uncrossable function. There exist instances that can be handled by our methods where none of the optimal dual solutions has a laminar support. We present three applications of our main result to problems in the area of network design. (1)  A \(16\)-approximation algorithm for augmenting a family of small cuts of a graph G. The previous best approximation ratio was \(O(\log {|V(G)|})\). (2)  A \(16\cdot {\lceil k/u_{min} \rceil }\)-approximation algorithm for the Cap-k-ECSS problem which is as follows: Given an undirected graph \(G = (V,E)\) with edge costs \(c \in {\mathbb {Q}}_{\ge 0}^E\) and edge capacities \(u \in {\mathbb {Z}}_{\ge 0}^E\), find a minimum-cost subset of the edges \(F\subseteq E\) such that the capacity of any cut in (VF) is at least k; \(u_{min}\) (respectively, \(u_{max}\)) denotes the minimum (respectively, maximum) capacity of an edge in E, and w.l.o.g. \(u_{max} \le k\). The previous best approximation ratio was \(\min (O(\log {|V|}), k, 2u_{max})\). (3)  A \(20\)-approximation algorithm for the model of (p, 2)-Flexible Graph Connectivity. The previous best approximation ratio was \(O(\log {|V(G)|})\), where G denotes the input graph.

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超越不可交函数,通过推广原初-双重方法改进逼近算法
我们解决了 Williamson、Goemans、Vazirani 和 Mihail 提出的长期悬而未决的问题,这些问题涉及通过初等二元方法设计网络设计问题的近似算法(Williamson 等人,载于《Combinatorica》15(3):435-454, 1995. https://doi.org/10.1007/BF01299747)。Williamson 等人证明了连通性增强问题的近似率为 2,在这种情况下,连通性要求可由不可交函数指定。他们指出"将我们的算法扩展到处理不可交函数仍然是一个具有挑战性的开放问题。不可交函数的主要特点是存在一个层状的最优对偶解......"。一个更大的悬而未决的问题是进一步探索初等二元方法的力量,以获得其他组合优化问题的近似算法"。我们的主要结果证明,Williamson 等人的初等二元算法对一类函数的近似率达到了\(16\),这类函数概括了不可交叉函数的概念。我们的方法可以处理的情况是,没有一个最优对偶解具有层状支撑。我们介绍了我们的主要结果在网络设计领域问题中的三个应用。(1) \(16\)-approximation algorithm for augmenting a family of small cuts of a graph G. 以前的最佳近似率是\(O(\log {|V(G)|})\).(2) Cap-k-ECSS 问题的 \(16\cdot {\lceil k/u_{min} \rceil }\) 近似算法如下:给定一个无向图(G = (V,E)),其边成本为 c(在{\mathbb {Q}}_{\ge 0}^E\中),边容量为 u(在{\mathbb {Z}}_{\ge 0}^E\中),找到一个最小成本的边子集(F(subseteq E\ ),使得(V, F)中任何切口的容量至少为 k;\(u_{min}\) (分别为 \(u_{max}/))表示 E 中一条边的最小(分别为最大)容量,w.l.o.g. (u_{max} \le k\ )。之前的最佳近似率是(\min (O(\log {|V|}), k, 2u_{max})\)。(3) (p, 2)-Flexible Graph Connectivity 模型的 \(20\)-approximation 算法。之前的最佳近似率为 \(O(\log {|V(G)|})\), 其中 G 表示输入图。
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来源期刊
Algorithmica
Algorithmica 工程技术-计算机:软件工程
CiteScore
2.80
自引率
9.10%
发文量
158
审稿时长
12 months
期刊介绍: Algorithmica is an international journal which publishes theoretical papers on algorithms that address problems arising in practical areas, and experimental papers of general appeal for practical importance or techniques. The development of algorithms is an integral part of computer science. The increasing complexity and scope of computer applications makes the design of efficient algorithms essential. Algorithmica covers algorithms in applied areas such as: VLSI, distributed computing, parallel processing, automated design, robotics, graphics, data base design, software tools, as well as algorithms in fundamental areas such as sorting, searching, data structures, computational geometry, and linear programming. In addition, the journal features two special sections: Application Experience, presenting findings obtained from applications of theoretical results to practical situations, and Problems, offering short papers presenting problems on selected topics of computer science.
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