连接阻断的FPTAS。

IF 2.1 2区 数学 Q2 COMPUTER SCIENCE, SOFTWARE ENGINEERING
Mathematical Programming Pub Date : 2026-01-01 Epub Date: 2025-12-16 DOI:10.1007/s10107-025-02312-2
Chien-Chung Huang, Nidia Obscura Acosta, Sorrachai Yingchareonthawornchai
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引用次数: 0

摘要

在连通性阻断问题中,我们被要求找到一个全局图切割,并在预算约束下删除一个边缘子集,使该切割中剩余边缘的总权重最小。这个问题很容易包含背包问题作为一个特例,因此它是np困难的。对于这个问题,Zenklusen [Zenklusen'14]设计了一个多项式时间近似方案(PTAS)和精确算法,用于单位边缘成本的特殊情况。他提出了一个问题,即对于一般情况,是否可能有一个完全多项式时间近似方案(FPTAS)。我们给予肯定的答复。对于单位边缘代价的特殊情况,我们也给出了更快的精确和近似算法。我们的主要技术贡献是建立了与中间图切问题的联系,称为归一化最小切,粗略地说,当更多的边被免费取出时,它会更严重地惩罚剩余边的权重。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An FPTAS for Connectivity Interdiction.

In the connectivity interdiction problem, we are asked to find a global graph cut and remove a subset of edges under a budget constraint, so that the total weight of the remaining edges in this cut is minimized. This problem easily includes the knapsack problem as a special case, hence it is NP-hard. For this problem, Zenklusen [Zenklusen'14] designed a polynomial-time approximation scheme (PTAS) and exact algorithms for the special case of unit edge costs. He posed the question of whether a fully polynomial-time approximation scheme (FPTAS) is possible for the general case. We give an affirmative answer. For the special case of unit edge costs, we also give faster exact and approximation algorithms. Our main technical contribution is to establish a connection with an intermediate graph cut problem, called the normalized min-cut, which, roughly speaking, penalizes the edge weights of the remaining edges more severely, when more edges are taken out for free.

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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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