Minimizing Reachability Times on Temporal Graphs via Shifting Labels

Authors: Argyrios Deligkas, Eduard Eiben, George Skretas

IJCAI 2023 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Theoretical We study how we can minimize the maximum time a set of sources needs to reach every vertex, when we are allowed to shift some of the connections. If we restrict the allowed number of changes, we prove that, already for a single source, the problem is NP-hard, and W[2]-hard when parameterized by the number of changes. Then we focus on unconstrained number of changes. We derive a polynomial-time algorithm when there is one source. When there are two sources, we show that the problem becomes NP-hard; on the other hand, we design an FPT algorithm parameterized by the treewidth of the graph plus the lifetime of the optimal solution, that works for any number of sources. Finally, we provide polynomial-time algorithms for several graph classes.
Researcher Affiliation Academia 1Royal Holloway, University of London 2Hasso Plattner Institute, University of Potsdam {argyrios.deligkas, eduard.eiben}@rhul.ac.uk, georgios.skretas@hpi.de
Pseudocode Yes Algorithm 1: One Source Reach Fast Algorithm
Open Source Code No The paper does not include any explicit statement or link indicating the availability of open-source code for the described methodology.
Open Datasets No The paper is theoretical and does not involve empirical evaluation on datasets, thus it does not provide information about dataset availability or access.
Dataset Splits No The paper is theoretical and does not involve empirical evaluation on datasets, thus it does not provide information about training/validation/test dataset splits.
Hardware Specification No The paper is theoretical and does not describe empirical experiments, thus no hardware specifications are mentioned.
Software Dependencies No The paper is theoretical and does not describe empirical experiments, thus no specific software dependencies with version numbers are provided.
Experiment Setup No The paper is theoretical and does not describe empirical experiments, thus no experimental setup details like hyperparameters or training configurations are provided.