惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

博客园 - Franky
Microsoft Azure Blog
Microsoft Azure Blog
阮一峰的网络日志
阮一峰的网络日志
宝玉的分享
宝玉的分享
量子位
N
Netflix TechBlog - Medium
M
MIT News - Artificial intelligence
GbyAI
GbyAI
Apple Machine Learning Research
Apple Machine Learning Research
博客园_首页
博客园 - 叶小钗
Cyber Security Advisories - MS-ISAC
Cyber Security Advisories - MS-ISAC
酷 壳 – CoolShell
酷 壳 – CoolShell
T
Tailwind CSS Blog
Y
Y Combinator Blog
L
LangChain Blog
The Cloudflare Blog
T
The Blog of Author Tim Ferriss
U
Unit 42
Martin Fowler
Martin Fowler
aimingoo的专栏
aimingoo的专栏
G
Google Developers Blog
freeCodeCamp Programming Tutorials: Python, JavaScript, Git & More
月光博客
月光博客

cs.DS updates on arXiv.org

PAC Learning with Bandit Feedback: Sharp Sample Complexity in the Realizable Setting Algorithms with Polynomially-Improved Approximation Factors for the $2 \rightarrow q$ Norm, and Applications A computational phase transition for learning-to-sample from Ising models Covering vertices by sequential stars Fermi-Dirac machines as quantizations of neurons A Comprehensive Evaluation of Vertex Elimination Algorithms for Algorithmic Differentiation A Tight Bound on Localization of Electrical Flows Optimal Dimension-Free Sampling for Regularized Classification Reducing the Randomness in Partition Oracles for Bounded Degree Minor-Free Graphs Beyond the Half-Approximation: Fair and Efficient Online Class Matching Efficient Uniform Sampling of Surjections via their Profiles Tractable Maximization of Budgeted Phylogenetic Diversity on Networks Utilizing Node Scanwidth Fairness in Aggregation: Optimal Top-$k$ and Improved Full Ranking Learning-Augmented Online Scheduling with Parsimonious Preemption Entropy Equivalence Testing Lumberjack: Better Differentially Private Random Forests through Heavy Hitter Detection in Trees The Secretary Problem with a Stochastic Precursor Polynomial-Time Robust Multiclass Linear Classification under Gaussian Marginals Efficient Banzhaf-Based Data Valuation for $k$-Nearest Neighbors Classification Block-Sphere Vector Quantization An Approximation Algorithm for Graph Label Selection Iterative Chow Filtering for Learning with Distribution Shift Complexity of Non-Log-Concave Sampling in Fisher Information Stochastic Matching via Local Sparsification Finite Sample Bounds for Learning with Score Matching What is Learnable in Valiant's Theory of the Learnable? Provable Quantization with Randomized Hadamard Transform Min-Max Optimization Requires Exponentially Many Queries Fast and Compact Graph Cuts for the Boykov-Kolmogorov Algorithm A proximal gradient algorithm for composite log-concave sampling
Temporal Routing in Static Networks: The Schedule Complet...
[Submitted on 30 Apr 2026 (v1), last revised 4 Aug 2026 (this ve · 2026-04-30 · via cs.DS updates on arXiv.org

View PDF

Abstract:We introduce the Temporally Edge Disjoint Schedule Completion (TEDSC) problem in which we need to cover a set of temporal edge demands $D$ by routing $k$ temporal walks through a directed static graph while remaining temporally edge disjoint. This problem combines the temporal aspects of train routing and passenger demands with the static nature of real-world rail networks. We show how to solve TEDSC in polynomial time. Motivated by real-world constraints, we next investigate two restricted variants of TEDSC in which each walk can travel only for some bounded distance or time $h$. For both variants, we present a $(2-h^{-1})$-approximation algorithm and fully characterize the parameterized landscape with respect to $k$, $h$, and $|D|$. Surprisingly, if we restrict the underlying train network, the two variants diverge: The distance variant stays $W[1]$-hard parameterized by $k$ even on a path of three vertices, whereas the time variant admits a polynomial-time algorithm on every fixed bidirected star graph.

Submission history

From: Niklas Mohrin [view email]
[v1] Thu, 30 Apr 2026 11:45:04 UTC (631 KB)
[v2] Wed, 6 May 2026 12:50:34 UTC (631 KB)
[v3] Tue, 4 Aug 2026 14:05:32 UTC (667 KB)