The complexity landscape of disaster-aware network extension problems

IF 1.6 4区计算机科学 Q4 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE Networks Pub Date : 2023-12-12 DOI:10.1002/net.22199

Balázs Vass, Beáta Éva Nagy, Balázs Brányi, János Tapolcai

引用次数: 0

Abstract

This article deals with the complexity of problems related to finding cost-efficient, disaster-aware cable routes. We overview various mathematical problems studied to augment a backbone network topology to make it more robust against regional failures. These problems either consider adding a single cable, multiple cables, or even nodes too. They adapt simplistic or more sophisticated regional failure models. Their objective is to identify the network's weak points or minimize the investment cost concerning the risk of a network outage. We investigate the tradeoffs in mathematical modeling for the same real-world scenario, where more sophisticated models face more computationally challenging problems. We have seen how efficiently computational geometry algorithms can be used to solve simplified problems even for sufficiently large networks. In this article, we aim to understand why different mathematical models formulated for the same real-world scenario can or cannot be solved efficiently. In particular, we show simplistic mathematical models that formulate NP-hard problems.

查看原文

微信好友朋友圈 QQ好友复制链接

本刊更多论文

灾害感知网络扩展问题的复杂性状况

本文讨论与寻找具有成本效益和灾害意识的电缆路由相关的复杂问题。我们概述了各种数学问题的研究，以增加骨干网络的拓扑结构，使其对区域故障更健壮。这些问题可以考虑添加单个电缆、多个电缆，甚至还可以添加节点。它们采用了简单或更复杂的区域失效模型。他们的目标是确定网络的弱点或最小化与网络中断风险有关的投资成本。我们研究了相同的现实世界场景的数学建模中的权衡，其中更复杂的模型面临更多的计算挑战问题。我们已经看到，即使对于足够大的网络，计算几何算法也可以有效地用于解决简化问题。在本文中，我们的目标是理解为什么为相同的现实世界场景制定的不同数学模型可以或不能有效地解决。特别是，我们展示了制定np困难问题的简单数学模型。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文去求助

来源期刊

Networks 工程技术-计算机：硬件

CiteScore

4.40

自引率

9.50%

发文量

审稿时长

12 months

期刊介绍： Network problems are pervasive in our modern technological society, as witnessed by our reliance on physical networks that provide power, communication, and transportation. As well, a number of processes can be modeled using logical networks, as in the scheduling of interdependent tasks, the dating of archaeological artifacts, or the compilation of subroutines comprising a large computer program. Networks provide a common framework for posing and studying problems that often have wider applicability than their originating context. The goal of this journal is to provide a central forum for the distribution of timely information about network problems, their design and mathematical analysis, as well as efficient algorithms for carrying out optimization on networks. The nonstandard modeling of diverse processes using networks and network concepts is also of interest. Consequently, the disciplines that are useful in studying networks are varied, including applied mathematics, operations research, computer science, discrete mathematics, and economics. Networks publishes material on the analytic modeling of problems using networks, the mathematical analysis of network problems, the design of computationally eﬃcient network algorithms, and innovative case studies of successful network applications. We do not typically publish works that fall in the realm of pure graph theory (without signiﬁcant algorithmic and modeling contributions) or papers that deal with engineering aspects of network design. Since the audience for this journal is then necessarily broad, articles that impact multiple application areas or that creatively use new or existing methodologies are especially appropriate. We seek to publish original, well-written research papers that make a substantive contribution to the knowledge base. In addition, tutorial and survey articles are welcomed. All manuscripts are carefully refereed.