On computing optimal temporal branchings and spanning subgraphs

IF 1.1 3区 计算机科学 Q1 BUSINESS, FINANCE Journal of Computer and System Sciences Pub Date : 2024-10-22 DOI:10.1016/j.jcss.2024.103596
Daniela Bubboloni , Costanza Catalano , Andrea Marino , Ana Silva
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Abstract

We extend the concept of out/in-branchings spanning the vertices of a digraph to temporal graphs, which are digraphs where arcs are available only at prescribed times. While the literature has focused on minimum weight/earliest arrival time Temporal Out-Branchings (tob), we solve the problem for other optimization criteria (travel duration, departure time, number of transfers, total waiting time, traveling time). For some criteria we provide a log linear algorithm for computing such branchings, while for others we prove that deciding the existence of a spanning tob is NP-complete. The same results hold for optimal temporal in-branchings. We also investigate the related problem of computing a spanning temporal subgraph with the minimum number of arcs and optimizing a chosen criterion; this problem turns out to be always NP-hard. The hardness results are quite surprising, as computing optimal paths between nodes is always polynomial-time.
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关于计算最佳时间分支和跨度子图
我们将跨越数字图顶点的出/入分支概念扩展到时间图,即弧只在规定时间内可用的数字图。文献主要关注最小权重/最早到达时间时空外分支(tob),而我们则针对其他优化标准(旅行持续时间、出发时间、换乘次数、总等待时间、旅行时间)来解决这个问题。对于某些标准,我们提供了计算此类分支的对数线性算法,而对于其他标准,我们则证明了决定是否存在跨时分支是 NP-完全的。同样的结果也适用于最优时间内分支。我们还研究了计算具有最少弧数的跨时序子图并优化所选准则的相关问题;结果证明这个问题总是 NP-困难。由于计算节点间的最优路径总是需要多项式时间,因此这一困难性结果令人十分惊讶。
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
Journal of Computer and System Sciences
Journal of Computer and System Sciences 工程技术-计算机:理论方法
CiteScore
3.70
自引率
0.00%
发文量
58
审稿时长
68 days
期刊介绍: The Journal of Computer and System Sciences publishes original research papers in computer science and related subjects in system science, with attention to the relevant mathematical theory. Applications-oriented papers may also be accepted and they are expected to contain deep analytic evaluation of the proposed solutions. Research areas include traditional subjects such as: • Theory of algorithms and computability • Formal languages • Automata theory Contemporary subjects such as: • Complexity theory • Algorithmic Complexity • Parallel & distributed computing • Computer networks • Neural networks • Computational learning theory • Database theory & practice • Computer modeling of complex systems • Security and Privacy.
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