Improved Exact Algorithm for Finding a Maximum Exploratory Equivalent Partition

An exploratory equivalent partition (EE partition) of a graph G with nontrivial automorphisms is a partition of its vertex set that can be directly translated into a set of constraints to speed up the search for occurrences of G in an arbitrary host graph. The maximum EE partition problem is to find an EE partition leading to the greatest speedup. However, this problem is NP-hard and the naïve algorithm is only practicable for small symmetry-rich graphs. In this paper, we propose a series of improvements based on computational group theory that vastly increase the algorithm’s range of practicability. For example, the improved algorithm spends less time on the 10-hypercube graph (1024 vertices, 5120 edges, ≈3.7×109 automorphisms) than the naïve algorithm does on the 4-hypercube graph (16 vertices, 32 edges, 384 automorphisms). We prove that all improvements maintain the algorithm’s correctness and confirm their contribution to the speed of execution through extensive experimentation.

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Publication Details

Journal
Symmetry
Published
2026-09-25
DOI
https://doi.org/10.3390/sym18101604
Primary Topic
Graph Labeling and Dimension Problems
Type
article
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Improved Exact Algorithm for Finding a Maximum Exploratory Equivalent Partition

Luka Fürst, Uroš Čibej, Jurij Mihelič, Lovro Sikošek
Symmetry
Graph Labeling and Dimension Problems
article

Improved Exact Algorithm for Finding a Maximum Exploratory Equivalent Partition

Luka Fürst, Uroš Čibej, Jurij Mihelič, Lovro Sikošek
article en

Abstract

An exploratory equivalent partition (EE partition) of a graph G with nontrivial automorphisms is a partition of its vertex set that can be directly translated into a set of constraints to speed up the search for occurrences of G in an arbitrary host graph. The maximum EE partition problem is to find an EE partition leading to the greatest speedup. However, this problem is NP-hard and the naïve algorithm is only practicable for small symmetry-rich graphs. In this paper, we propose a series of improvements based on computational group theory that vastly increase the algorithm’s range of practicability. For example, the improved algorithm spends less time on the 10-hypercube graph (1024 vertices, 5120 edges, ≈3.7×109 automorphisms) than the naïve algorithm does on the 4-hypercube graph (16 vertices, 32 edges, 384 automorphisms). We prove that all improvements maintain the algorithm’s correctness and confirm their contribution to the speed of execution through extensive experimentation.

SymmetryVol. 18(10)
TU Wien (AT), University of Ljubljana (SI)
Openalex Percentile: Top 9%
Graph Labeling and Dimension Problems
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Improved Exact Algorithm for Finding a Maximum Exploratory Equivalent Partition — Luka Fürst, Uroš Čibej, et al. · Symmetry (2026) | TGRS Research Map | TGRS