LIPIcs.TIME.2024.20.pdf
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FastMinTC+: A Fast and Effective Heuristic for Minimum Timeline Cover on Temporal Networks
Authors
Giorgio Lazzarinetti 
,
Sara Manzoni ,
Italo Zoppis ,
Riccardo Dondi
-
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Volume:
31st International Symposium on Temporal Representation and Reasoning (TIME 2024)
Series: Leibniz International Proceedings in Informatics (LIPIcs)
Conference: International Symposium on Temporal Representation and Reasoning (TIME) - License:
Creative Commons Attribution 4.0 International license
- Publication Date: 2024-10-22
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Giorgio Lazzarinetti, Sara Manzoni, Italo Zoppis, and Riccardo Dondi. FastMinTC+: A Fast and Effective Heuristic for Minimum Timeline Cover on Temporal Networks. In 31st International Symposium on Temporal Representation and Reasoning (TIME 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 318, pp. 20:1-20:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)
https://doi.org/10.4230/LIPIcs.TIME.2024.20
https://doi.org/10.4230/LIPIcs.TIME.2024.20
Abstract
The analysis and summarization of temporal networks are crucial for understanding complex interactions over time, yet pose significant computational challenges. This paper introduces FastMinTC+, an innovative heuristic approach designed to efficiently solve the Minimum Timeline Cover (MinTCover) problem in temporal networks. Our approach focuses on the optimization of activity timelines within temporal networks, aiming to provide both effective and computationally feasible solutions. By employing a low-complexity approach, FastMinTC+ adeptly handles massive temporal graphs, improving upon existing methods. Indeed, comparative evaluations on both synthetic and real-world datasets demonstrate that our algorithm outperforms established benchmarks with remarkable efficiency and accuracy. The results highlight the potential of heuristic approaches in the domain of temporal network analysis and open up new avenues for further research incorporating other computational techniques, for example deep learning, to enhance the adaptability and precision of such heuristics.
Subject Classification
ACM Subject Classification
- Mathematics of computing → Graph algorithms
- Theory of computation → Design and analysis of algorithms
- Theory of computation → Mathematical optimization
- Theory of computation → Discrete optimization
Keywords
- Temporal Networks
- Activity Timeline
- Timeline Cover
- Vertex Cover
- Optimization
- Heuristic
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References
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