How Many Lines to Paint the City: Exact Edge-Cover in Temporal Graphs
Abstract
Logistics and transportation networks require a large amount of resources to realise necessary connections between locations and minimizing these resources is a vital aspect of planning research. Since such networks have dynamic connections that are only available at specific times, intricate models are needed to portray them accurately. In this paper, we study the problem of minimizing the number of resources needed to realise a dynamic network, using the temporal graphs model. In a temporal graph, edges appear at specific points in time. Given a temporal graph and a natural number k, we ask whether we can cover every temporal edge exactly once using at most k temporal journeys; in a temporal journey consecutive edges have to adhere to the order of time. We conduct a thorough investigation of the complexity of the problem with respect to four dimensions: (a) whether the type of the temporal journey is a walk, a trail, or a path; (b) whether the chronological order of edges in the journey is strict or non-strict; (c) whether the temporal graph is directed or undirected; (d) whether the start and end points of each journey are given. We almost completely resolve the complexity of these problems and provide dichotomies for each of them with respect to k.
Cite
Text
Deligkas et al. "How Many Lines to Paint the City: Exact Edge-Cover in Temporal Graphs." AAAI Conference on Artificial Intelligence, 2025. doi:10.1609/AAAI.V39I25.34850Markdown
[Deligkas et al. "How Many Lines to Paint the City: Exact Edge-Cover in Temporal Graphs." AAAI Conference on Artificial Intelligence, 2025.](https://mlanthology.org/aaai/2025/deligkas2025aaai-many/) doi:10.1609/AAAI.V39I25.34850BibTeX
@inproceedings{deligkas2025aaai-many,
title = {{How Many Lines to Paint the City: Exact Edge-Cover in Temporal Graphs}},
author = {Deligkas, Argyrios and Döring, Michelle and Eiben, Eduard and Goldsmith, Tiger-Lily and Skretas, George and Tennigkeit, Georg},
booktitle = {AAAI Conference on Artificial Intelligence},
year = {2025},
pages = {26498-26506},
doi = {10.1609/AAAI.V39I25.34850},
url = {https://mlanthology.org/aaai/2025/deligkas2025aaai-many/}
}