LIPIcs.GD.2024.51.pdf
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Evolutionary Algorithms for One-Sided Bipartite Crossing Minimisation (Poster Abstract)
Authors
Jakob Baumann 
,
Ignaz Rutter ,
Dirk Sudholt
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Volume:
32nd International Symposium on Graph Drawing and Network Visualization (GD 2024)
Series: Leibniz International Proceedings in Informatics (LIPIcs)
Conference: Graph Drawing and Network Visualization (GD) - License:
Creative Commons Attribution 4.0 International license
- Publication Date: 2024-10-28
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Jakob Baumann, Ignaz Rutter, and Dirk Sudholt. Evolutionary Algorithms for One-Sided Bipartite Crossing Minimisation (Poster Abstract). In 32nd International Symposium on Graph Drawing and Network Visualization (GD 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 320, pp. 51:1-51:3, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)
https://doi.org/10.4230/LIPIcs.GD.2024.51
Abstract
Evolutionary algorithms (EAs) are universal solvers inspired by principles of natural evolution. In many applications, EAs produce astonishingly good solutions. To complement recent theoretical advances in the analysis of EAs on graph drawing [Baumann et al., 2024], we contribute a fundamental empirical study. We consider the so-called One-Sided Bipartite Crossing Minimisation (OBCM): given two layers of a bipartite graph and a fixed horizontal order of vertices on the first layer, the task is to order the vertices on the second layer to minimise the number of edge crossings. We empirically analyse the performance of simple EAs for OBCM and compare different mutation operators on the underlying permutation ordering problem: exchanging two elements (exchange), swapping adjacent elements (swap) and jumping an element to a new position (jump). EAs using jumps easily outperform all deterministic algorithms in terms of solution quality after a reasonable number of generations. We also design variations of the best-performing EAs to reduce the execution time for each generation. The improved EAs can obtain the same solution quality as before and run up to 100 times faster.
Subject Classification
ACM Subject Classification
- Theory of computation → Design and analysis of algorithms
Keywords
- Mutation Operator
- Layered Graphs
- Crossing Minimisation
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References
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