Volume
LIPIcs, Volume 338
23rd International Symposium on Experimental Algorithms (SEA 2025)
-
Part of:
Series:
Leibniz International Proceedings in Informatics (LIPIcs)
Conference: International Symposium on Experimental Algorithms (SEA)
Event
SEA 2025, July 22-24, 2025, Venice, ItalyEditors
Publication Details
- published at: 2025-07-15
- Publisher: Schloss Dagstuhl – Leibniz-Zentrum für Informatik
- ISBN: 978-3-95977-375-1
- DBLP: db/conf/wea/sea2025
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Document
Complete Volume
LIPIcs, Volume 338, SEA 2025, Complete Volume
Abstract
LIPIcs, Volume 338, SEA 2025, Complete Volume
Cite as
23rd International Symposium on Experimental Algorithms (SEA 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 338, pp. 1-502, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)
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@Proceedings{mutzel_et_al:LIPIcs.SEA.2025,
title = {{LIPIcs, Volume 338, SEA 2025, Complete Volume}},
booktitle = {23rd International Symposium on Experimental Algorithms (SEA 2025)},
pages = {1--502},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-375-1},
ISSN = {1868-8969},
year = {2025},
volume = {338},
editor = {Mutzel, Petra and Prezza, Nicola},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SEA.2025},
URN = {urn:nbn:de:0030-drops-239259},
doi = {10.4230/LIPIcs.SEA.2025},
annote = {Keywords: LIPIcs, Volume 338, SEA 2025, Complete Volume}
}
Document
Front Matter
Front Matter, Table of Contents, Preface, Conference Organization
Abstract
Front Matter, Table of Contents, Preface, Conference Organization
Cite as
23rd International Symposium on Experimental Algorithms (SEA 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 338, pp. 0:i-0:xviii, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)
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@InProceedings{mutzel_et_al:LIPIcs.SEA.2025.0,
author = {Mutzel, Petra and Prezza, Nicola},
title = {{Front Matter, Table of Contents, Preface, Conference Organization}},
booktitle = {23rd International Symposium on Experimental Algorithms (SEA 2025)},
pages = {0:i--0:xviii},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-375-1},
ISSN = {1868-8969},
year = {2025},
volume = {338},
editor = {Mutzel, Petra and Prezza, Nicola},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SEA.2025.0},
URN = {urn:nbn:de:0030-drops-239249},
doi = {10.4230/LIPIcs.SEA.2025.0},
annote = {Keywords: Front Matter, Table of Contents, Preface, Conference Organization}
}
Document
Polymorphic Cycle Basis in a Sequence of Graphs to Analyze the Structural Evolution of a Molecular Dynamic Trajectory
Abstract
Molecular dynamics analysis is a fundamental topic in chemistry, in particular the study of the formation and dissolution of hydrogen bonds over time. The dynamics of these bonds create and break cycles which are crucial to the structure of the molecules. The challenge in cycle analysis is twofold: there is an exponential number of cycles, and some cycles are very close.
We introduce a graph-based approach using minimum cycle bases to assist in molecular dynamics analysis. Given a set of graphs representing a molecule trajectory, we determine, for each graph, a minimum cycle basis and construct a graph of cycles which represents the cycles of minimum bases and their interactions. Then, we aggregate all information from these graphs of cycles into a polygraph. Each vertex of the polygraph represents a class of cycles appearing in different minimum bases and playing equivalent roles in the trajectory.
This paper introduces our approach, establishes the complexity of associated problems, and suggests an implementation. Simulations are conducted on both real and generated data to evaluate the performance of our approach.
Cite as
Ylène Aboulfath, Dominique Barth, Thierry Mautor, Dimitri Watel, and Marc-Antoine Weisser. Polymorphic Cycle Basis in a Sequence of Graphs to Analyze the Structural Evolution of a Molecular Dynamic Trajectory. In 23rd International Symposium on Experimental Algorithms (SEA 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 338, pp. 1:1-1:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)
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@InProceedings{aboulfath_et_al:LIPIcs.SEA.2025.1,
author = {Aboulfath, Yl\`{e}ne and Barth, Dominique and Mautor, Thierry and Watel, Dimitri and Weisser, Marc-Antoine},
title = {{Polymorphic Cycle Basis in a Sequence of Graphs to Analyze the Structural Evolution of a Molecular Dynamic Trajectory}},
booktitle = {23rd International Symposium on Experimental Algorithms (SEA 2025)},
pages = {1:1--1:14},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-375-1},
ISSN = {1868-8969},
year = {2025},
volume = {338},
editor = {Mutzel, Petra and Prezza, Nicola},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SEA.2025.1},
URN = {urn:nbn:de:0030-drops-232399},
doi = {10.4230/LIPIcs.SEA.2025.1},
annote = {Keywords: Graph theory, Cycle basis, Molecular analysis}
}
Document
IBB: Fast Burrows-Wheeler Transform Construction for Length-Diverse DNA Data
Abstract
The Burrows-Wheeler transform (BWT) is integral to the FM-index, which is used extensively in text compression, indexing, pattern search, and bioinformatic problems as de novo assembly and read alignment. Thus, efficient construction of the BWT in terms of time and memory usage is key to these applications. We present a novel external-memory algorithm called Improved-Bucket Burrows-Wheeler transform (IBB) for constructing the BWT of DNA datasets with highly diverse sequence lengths. IBB uses a right-aligned approach to efficiently handle sequences of varying lengths, a tree-based data structure to manage relative insert positions and ranks, and fine buckets to reduce the necessary amount of input and output to external memory. Our experiments demonstrate that IBB is 10% to 40% faster than the best existing state-of-the-art BWT construction algorithms on most datasets while maintaining competitive memory consumption.
Cite as
Enno Adler, Stefan Böttcher, Rita Hartel, and Cederic Alexander Steininger. IBB: Fast Burrows-Wheeler Transform Construction for Length-Diverse DNA Data. In 23rd International Symposium on Experimental Algorithms (SEA 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 338, pp. 2:1-2:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)
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@InProceedings{adler_et_al:LIPIcs.SEA.2025.2,
author = {Adler, Enno and B\"{o}ttcher, Stefan and Hartel, Rita and Steininger, Cederic Alexander},
title = {{IBB: Fast Burrows-Wheeler Transform Construction for Length-Diverse DNA Data}},
booktitle = {23rd International Symposium on Experimental Algorithms (SEA 2025)},
pages = {2:1--2:18},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-375-1},
ISSN = {1868-8969},
year = {2025},
volume = {338},
editor = {Mutzel, Petra and Prezza, Nicola},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SEA.2025.2},
URN = {urn:nbn:de:0030-drops-232402},
doi = {10.4230/LIPIcs.SEA.2025.2},
annote = {Keywords: burrows-wheeler transform, self-indexes, external-memory}
}
Document
A Practical Algorithm for 2-Admissibility
Abstract
The 2-admissibility of a graph is a promising measure to identify real-world networks which have an algorithmically favourable structure. In contrast to other related measures, like the weak/strong 2-colouring numbers or the maximum density of graphs that appear as 1-subdivisions, the 2-admissibility can be computed in polynomial time. However, so far these results are theoretical only and no practical implementation to compute the 2-admissibility exists.
Here we present an algorithm which decides whether the 2-admissibility of an input graph G is at most p in time O(p⁴ |V(G)|) and space O(|E(G)| + p²). The simple structure of the algorithm makes it easy to implement. We evaluate our implementation on a corpus of 214 real-world networks and find that the algorithm runs efficiently even on networks with millions of edges, that it has a low memory footprint, and that indeed many networks have a small 2-admissibility.
Cite as
Christine Awofeso, Patrick Greaves, Oded Lachish, and Felix Reidl. A Practical Algorithm for 2-Admissibility. In 23rd International Symposium on Experimental Algorithms (SEA 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 338, pp. 3:1-3:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)
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@InProceedings{awofeso_et_al:LIPIcs.SEA.2025.3,
author = {Awofeso, Christine and Greaves, Patrick and Lachish, Oded and Reidl, Felix},
title = {{A Practical Algorithm for 2-Admissibility}},
booktitle = {23rd International Symposium on Experimental Algorithms (SEA 2025)},
pages = {3:1--3:19},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-375-1},
ISSN = {1868-8969},
year = {2025},
volume = {338},
editor = {Mutzel, Petra and Prezza, Nicola},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SEA.2025.3},
URN = {urn:nbn:de:0030-drops-232413},
doi = {10.4230/LIPIcs.SEA.2025.3},
annote = {Keywords: Sparse graphs, admissibility}
}
Document
U-Index: A Universal Indexing Framework for Matching Long Patterns
Abstract
Motivation. Text indexing is a fundamental and well-studied problem. Classic solutions to this problem either replace the original text with a compressed representation, e.g., the FM-index and its variants, or keep it uncompressed but attach some redundancy - an index - to accelerate matching, e.g., the suffix array. The former solutions thus retain excellent compressed space, but are practically slow to construct and query. The latter approaches, instead, sacrifice space efficiency but are typically faster; for example, the suffix array takes much more space than the text itself for commonly used alphabets, like ASCII or DNA, but it is very fast to construct and query.
Methods. In this paper, we show that efficient text indexing can be achieved using just a small extra space on top of the original text, provided that the query patterns are sufficiently long. More specifically, we develop a new indexing paradigm in which a sketch of a query pattern is first matched against a sketch of the text. Once candidate matches are retrieved, they are verified using the original text. This paradigm is thus universal in the sense that it allows us to use any solution to index the sketched text, like a suffix array, FM-index, or r-index.
Results. We explore both the theory and the practice of this universal framework. With an extensive experimental analysis, we show that, surprisingly, universal indexes can be constructed much faster than their unsketched counterparts and take a fraction of the space, as a direct consequence of (i) having a lower bound on the length of patterns and (ii) working in sketch space. Furthermore, these data structures have the potential of retaining or even improving query time, because matching against the sketched text is faster and verifying candidates can be theoretically done in constant time per occurrence (or, in practice, by short and cache-friendly scans of the text).
Finally, we discuss some important applications of this novel indexing paradigm to computational biology. We hypothesize that such indexes will be particularly effective when the queries are sufficiently long, and so we demonstrate applications in long-read mapping.
Cite as
Lorraine A. K. Ayad, Gabriele Fici, Ragnar Groot Koerkamp, Grigorios Loukides, Rob Patro, Giulio Ermanno Pibiri, and Solon P. Pissis. U-Index: A Universal Indexing Framework for Matching Long Patterns. In 23rd International Symposium on Experimental Algorithms (SEA 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 338, pp. 4:1-4:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)
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@InProceedings{ayad_et_al:LIPIcs.SEA.2025.4,
author = {Ayad, Lorraine A. K. and Fici, Gabriele and Groot Koerkamp, Ragnar and Loukides, Grigorios and Patro, Rob and Pibiri, Giulio Ermanno and Pissis, Solon P.},
title = {{U-Index: A Universal Indexing Framework for Matching Long Patterns}},
booktitle = {23rd International Symposium on Experimental Algorithms (SEA 2025)},
pages = {4:1--4:18},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-375-1},
ISSN = {1868-8969},
year = {2025},
volume = {338},
editor = {Mutzel, Petra and Prezza, Nicola},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SEA.2025.4},
URN = {urn:nbn:de:0030-drops-232420},
doi = {10.4230/LIPIcs.SEA.2025.4},
annote = {Keywords: Text Indexing, Sketching, Minimizers, Hashing}
}
Document
A Comparative Study of Compressed, Learned, and Traditional Indexing Methods for Integer Data
Abstract
The rapid evolution of learned data structures has revolutionized database indexing, particularly for sorted integer datasets. While learned indexes excel in static scenarios due to their low memory footprint, reduced storage requirements, and fast lookup times, benchmarks like SOSD and TLI have largely overlooked compressed indexes and SIMD-based implementations of traditional indexes. This paper addresses this gap by introducing a comprehensive benchmarking framework that (i) evaluates traditional, learned, and compressed indexes across 12 datasets (real and synthetic) of varying types and sizes; (ii) integrates state-of-the-art SIMD-enhanced B-Tree variants; and (iii) measures critical performance metrics such as memory usage, construction time, and lookup efficiency. Our findings reveal that while learned indexes minimize memory usage, a feature useful when internal memory constraints are mandatory, SIMD-enhanced B-Trees consistently achieve superior lookup times with comparable extra space. On the other hand, compressed indexes like LA-vector and EliasFano provide very effective compression of the indexed data with slower access speeds (2x-3x). Another contribution of this paper is a publicly available benchmarking framework (composed of code and datasets) that makes our experiments reproducible and extensible to other indexes and datasets.
Cite as
Lorenzo Bellomo, Giuseppe Cianci, Luca de Rosa, Paolo Ferragina, and Mattia Odorisio. A Comparative Study of Compressed, Learned, and Traditional Indexing Methods for Integer Data. In 23rd International Symposium on Experimental Algorithms (SEA 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 338, pp. 5:1-5:23, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)
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@InProceedings{bellomo_et_al:LIPIcs.SEA.2025.5,
author = {Bellomo, Lorenzo and Cianci, Giuseppe and de Rosa, Luca and Ferragina, Paolo and Odorisio, Mattia},
title = {{A Comparative Study of Compressed, Learned, and Traditional Indexing Methods for Integer Data}},
booktitle = {23rd International Symposium on Experimental Algorithms (SEA 2025)},
pages = {5:1--5:23},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-375-1},
ISSN = {1868-8969},
year = {2025},
volume = {338},
editor = {Mutzel, Petra and Prezza, Nicola},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SEA.2025.5},
URN = {urn:nbn:de:0030-drops-232439},
doi = {10.4230/LIPIcs.SEA.2025.5},
annote = {Keywords: indexing data structures, compression, algorithm engineering, benchmark}
}
Document
Planar Network Diversion
Abstract
Network Diversion is a graph problem that has been extensively studied in both the network-analysis and operations-research communities as a measure of how robust a network is against adversarial disruption. In Network Diversion we want to enforce all s-t-paths through a specific edge b by removing edges from G. This problem is especially well motivated in transportation networks, which are often assumed to be planar. Motivated by this and recent theoretical advances for Network Diversion on planar input graphs, we develop a fast O(n log n) time algorithm and present a practical implementation of this algorithm that is able to solve instances with millions of vertices in a matter of seconds.
Cite as
Matthias Bentert, Pål Grønås Drange, Fedor V. Fomin, and Steinar Simonnes. Planar Network Diversion. In 23rd International Symposium on Experimental Algorithms (SEA 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 338, pp. 6:1-6:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)
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@InProceedings{bentert_et_al:LIPIcs.SEA.2025.6,
author = {Bentert, Matthias and Drange, P\r{a}l Gr{\o}n\r{a}s and Fomin, Fedor V. and Simonnes, Steinar},
title = {{Planar Network Diversion}},
booktitle = {23rd International Symposium on Experimental Algorithms (SEA 2025)},
pages = {6:1--6:14},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-375-1},
ISSN = {1868-8969},
year = {2025},
volume = {338},
editor = {Mutzel, Petra and Prezza, Nicola},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SEA.2025.6},
URN = {urn:nbn:de:0030-drops-232448},
doi = {10.4230/LIPIcs.SEA.2025.6},
annote = {Keywords: Minimal cuts, Bridges, Network interdiction, Algorithm engineering}
}
Document
Continuous Map Matching to Paths Under Travel Time Constraints
Abstract
In this paper, we study the problem of map matching with travel time constraints. Given a sequence of k spatio-temporal measurements and an embedded path graph with travel time costs, the goal is to snap each measurement to a close-by location in the graph, such that consecutive locations can be reached from one another along the path within the timestamp difference of the respective measurements. This problem arises in public transit data processing as well as in map matching of movement trajectories to general graphs. We show that the classical approach for this problem, which relies on selecting a finite set of candidate locations in the graph for each measurement, cannot guarantee to find a consistent solution. We propose a new algorithm that can deal with an infinite set of candidate locations per measurement. We prove that our algorithm always detects a consistent map matching path (if one exists). Despite the enlarged candidate set, we also demonstrate that our algorithm has superior running time in theory and practice. For a path graph with n nodes, we show that our algorithm runs in 𝒪(k² n log {nk}) and under mild assumptions in 𝒪(k n ^λ + n log³ n) for λ ≈ 0.695. This is a significant improvement over the baseline, which runs in 𝒪(k n²) and which might not even identify a correct solution. The performance of our algorithm hinges on an efficient segment-circle intersection data structure. We describe how to design and implement such a data structure for our application. In the experimental evaluation, we demonstrate the usefulness of our novel algorithm on a diverse set of generated measurements as well as GTFS data.
Cite as
Yannick Bosch and Sabine Storandt. Continuous Map Matching to Paths Under Travel Time Constraints. In 23rd International Symposium on Experimental Algorithms (SEA 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 338, pp. 7:1-7:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)
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@InProceedings{bosch_et_al:LIPIcs.SEA.2025.7,
author = {Bosch, Yannick and Storandt, Sabine},
title = {{Continuous Map Matching to Paths Under Travel Time Constraints}},
booktitle = {23rd International Symposium on Experimental Algorithms (SEA 2025)},
pages = {7:1--7:17},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-375-1},
ISSN = {1868-8969},
year = {2025},
volume = {338},
editor = {Mutzel, Petra and Prezza, Nicola},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SEA.2025.7},
URN = {urn:nbn:de:0030-drops-232457},
doi = {10.4230/LIPIcs.SEA.2025.7},
annote = {Keywords: Map matching, Travel time, Segment-circle intersection data structure}
}
Document
A Simple Integer Successor-Delete Data Structure
Abstract
We consider a simple decremental data structure for maintaining a set of integers, that supports initializing the set to {1,2,…,n} followed by d deletions and s successor queries in arbitrary order in total 𝒪(n+d+s⋅(1+log_{max(2,s/n)} min(s,n))) time. The data structure consists of a single array of n integers. A straightforward modification allows the data structure to also support p predecessor and r range queries, with a total output k, in total 𝒪(n+d+k+q ⋅ (1+log_{max(2,q/n)} min(q,n))) time, where q = s+p+r. The data structure is essentially a special case of the classic union-find data structure with path compression but with unweighted linking (i.e., without linking by rank or size), that is known to achieve logarithmic amortized time bounds (Tarjan and van Leeuwen, 1984). In this paper we study the efficiency of this simple data structure, and compare it to other, theoretically superior, data structures.
Cite as
Gerth Stølting Brodal. A Simple Integer Successor-Delete Data Structure. In 23rd International Symposium on Experimental Algorithms (SEA 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 338, pp. 8:1-8:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)
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@InProceedings{brodal:LIPIcs.SEA.2025.8,
author = {Brodal, Gerth St{\o}lting},
title = {{A Simple Integer Successor-Delete Data Structure}},
booktitle = {23rd International Symposium on Experimental Algorithms (SEA 2025)},
pages = {8:1--8:16},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-375-1},
ISSN = {1868-8969},
year = {2025},
volume = {338},
editor = {Mutzel, Petra and Prezza, Nicola},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SEA.2025.8},
URN = {urn:nbn:de:0030-drops-232461},
doi = {10.4230/LIPIcs.SEA.2025.8},
annote = {Keywords: Successor queries, deletions, interval union-find, union-find}
}
Document
Incremental Reachability Index
Abstract
We study the reachability problem in append-only DAGs: given two nodes u and v, is there a path from u to v? While the problem is linear in general, it can be answered faster by using a precomputed index, which gives a compressed representation of the transitive closure of the graph.
Index algorithms are evaluated on three dimensions: the query time that the algorithm needs to answer whether there is a path from one node to another, the memory that the index uses per node, and the indexing time that is required to update the index when a node is added to the graph.
In this paper, we combine Jagadish’s static index [Jagadish, 1990] with Felsner’s online chain-decomposition algorithm [Stefan Felsner, 1997] to create an incremental index: data associated with a node is immutable, guaranteeing that queries are answered properly even if new nodes are inserted while the query is processed.
Its query time is constant, but its index size is heavily dependent on the graph width, and as such is not competitive with recent indexing algorithms (2-hop, tree-chain, ...). We also propose a version of that incremental algorithm with a much lighter index. In the most compressed version, the query time becomes O(log n). However, constant-time queries can be retained depending on the desired time/memory trade-off.
Cite as
Laurent Bulteau, Pierre-Yves David, Florian Horn, and Euxane Tran-Girard. Incremental Reachability Index. In 23rd International Symposium on Experimental Algorithms (SEA 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 338, pp. 9:1-9:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)
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@InProceedings{bulteau_et_al:LIPIcs.SEA.2025.9,
author = {Bulteau, Laurent and David, Pierre-Yves and Horn, Florian and Tran-Girard, Euxane},
title = {{Incremental Reachability Index}},
booktitle = {23rd International Symposium on Experimental Algorithms (SEA 2025)},
pages = {9:1--9:16},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-375-1},
ISSN = {1868-8969},
year = {2025},
volume = {338},
editor = {Mutzel, Petra and Prezza, Nicola},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SEA.2025.9},
URN = {urn:nbn:de:0030-drops-232477},
doi = {10.4230/LIPIcs.SEA.2025.9},
annote = {Keywords: Directed acyclic graphs, reachability, append-only, index}
}
Document
Algorithm Engineering of SSSP with Negative Edge Weights
Abstract
Computing shortest paths is one of the most fundamental algorithmic graph problems. It is known since decades that this problem can be solved in near-linear time if all weights are nonnegative. A recent break-through by [Aaron Bernstein et al., 2022] presented a randomized near-linear time algorithm for this problem. A subsequent improvement in [Karl Bringmann et al., 2023] significantly reduced the number of logarithmic factors and thereby also simplified the algorithm. It is surprising and exciting that both of these algorithms are combinatorial and do not contain any fundamental obstacles for being practical.
We launch the, to the best of our knowledge, first extensive investigation towards a practical implementation of [Karl Bringmann et al., 2023]. To this end, we give an accessible overview of the algorithm and discuss what adaptions are necessary to obtain a fast algorithm in practice. We manifest these adaptions in an efficient implementation. We test our implementation on a benchmark data set that is adapted to be more difficult for our implementation in order to allow for a fair comparison. As in [Karl Bringmann et al., 2023] as well as in our implementation there are multiple parameters to tune, we empirically evaluate their effect and thereby determine the best choices. Our implementation is then extensively compared to one of the state-of-the-art algorithms for this problem [Andrew V. Goldberg and Tomasz Radzik, 1993]. On the hardest instance type, we are faster by up to almost two orders of magnitude.
Cite as
Alejandro Cassis, Andreas Karrenbauer, André Nusser, and Paolo Luigi Rinaldi. Algorithm Engineering of SSSP with Negative Edge Weights. In 23rd International Symposium on Experimental Algorithms (SEA 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 338, pp. 10:1-10:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)
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@InProceedings{cassis_et_al:LIPIcs.SEA.2025.10,
author = {Cassis, Alejandro and Karrenbauer, Andreas and Nusser, Andr\'{e} and Rinaldi, Paolo Luigi},
title = {{Algorithm Engineering of SSSP with Negative Edge Weights}},
booktitle = {23rd International Symposium on Experimental Algorithms (SEA 2025)},
pages = {10:1--10:20},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-375-1},
ISSN = {1868-8969},
year = {2025},
volume = {338},
editor = {Mutzel, Petra and Prezza, Nicola},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SEA.2025.10},
URN = {urn:nbn:de:0030-drops-232486},
doi = {10.4230/LIPIcs.SEA.2025.10},
annote = {Keywords: Single Source Shortest Paths, Negative Weights, Near-Linear Time}
}
Document
CluStRE: Streaming Graph Clustering with Multi-Stage Refinement
Abstract
We present CluStRE, a novel streaming graph clustering algorithm that balances computational efficiency with high-quality clustering using multi-stage refinement. Unlike traditional in-memory clustering approaches, CluStRE processes graphs in a streaming setting, significantly reducing memory overhead while leveraging re-streaming and evolutionary heuristics to improve solution quality. Our method dynamically constructs a quotient graph, enabling modularity-based optimization while efficiently handling large-scale graphs. We introduce multiple configurations of CluStRE to provide trade-offs between speed, memory consumption, and clustering quality. Experimental evaluations demonstrate that CluStRE improves solution quality by 89.8%, operates 2.6× faster, and uses less than two-thirds of the memory required by the state-of-the-art streaming clustering algorithm on average. Moreover, our strongest mode enhances solution quality by up to 150% on average. With this, CluStRE achieves comparable solution quality to in-memory algorithms, i.e. over 96% of the quality of clustering approaches, including Louvain, effectively bridging the gap between streaming and traditional clustering methods.
Cite as
Adil Chhabra, Shai Dorian Peretz, and Christian Schulz. CluStRE: Streaming Graph Clustering with Multi-Stage Refinement. In 23rd International Symposium on Experimental Algorithms (SEA 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 338, pp. 11:1-11:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)
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@InProceedings{chhabra_et_al:LIPIcs.SEA.2025.11,
author = {Chhabra, Adil and Dorian Peretz, Shai and Schulz, Christian},
title = {{CluStRE: Streaming Graph Clustering with Multi-Stage Refinement}},
booktitle = {23rd International Symposium on Experimental Algorithms (SEA 2025)},
pages = {11:1--11:20},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-375-1},
ISSN = {1868-8969},
year = {2025},
volume = {338},
editor = {Mutzel, Petra and Prezza, Nicola},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SEA.2025.11},
URN = {urn:nbn:de:0030-drops-232493},
doi = {10.4230/LIPIcs.SEA.2025.11},
annote = {Keywords: graph clustering, community, streaming, online, memetic, evolutionary}
}
Document
Bit Packed Encodings for Grammar-Compressed Strings Supporting Fast Random Access
Abstract
Grammar-based compression is a powerful compression technique that allows for computation over the compressed data. While there has been extensive theoretical work on grammar and encoding size, there has been little work on practical grammar encodings. In this work, we consider the canonical array-of-arrays grammar representation and present a general bit packing approach for reducing its space requirements in practice. We then present three bit packing strategies based on this approach - one online and two offline - with different space-time trade-offs. This technique can be used to encode any grammar-compressed string while preserving the virtues of the array-of-arrays representation. We show that our encodings are Nlog₂ N away from the information-theoretic bound, where N is the number of symbols in the grammar, and that they are much smaller than methods that meet the information-theoretic bound in practice. Moreover, our experiments show that by using bit packed encodings we can achieve state-of-the-art performance both in grammar encoding size and run-time performance of random-access queries.
Cite as
Alan M. Cleary, Joseph Winjum, Jordan Dood, Hiroki Shibata, and Shunsuke Inenaga. Bit Packed Encodings for Grammar-Compressed Strings Supporting Fast Random Access. In 23rd International Symposium on Experimental Algorithms (SEA 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 338, pp. 12:1-12:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)
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@InProceedings{cleary_et_al:LIPIcs.SEA.2025.12,
author = {Cleary, Alan M. and Winjum, Joseph and Dood, Jordan and Shibata, Hiroki and Inenaga, Shunsuke},
title = {{Bit Packed Encodings for Grammar-Compressed Strings Supporting Fast Random Access}},
booktitle = {23rd International Symposium on Experimental Algorithms (SEA 2025)},
pages = {12:1--12:17},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-375-1},
ISSN = {1868-8969},
year = {2025},
volume = {338},
editor = {Mutzel, Petra and Prezza, Nicola},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SEA.2025.12},
URN = {urn:nbn:de:0030-drops-232506},
doi = {10.4230/LIPIcs.SEA.2025.12},
annote = {Keywords: String algorithms, data compression, random access, grammar-based compression}
}
Document
Pangenome Graph Indexing via the Multidollar-BWT
Abstract
Indexing pangenome graphs is a major algorithmic challenge in computational pangenomics, a recent and active research field that seeks to use graphs as representations of multiple genomes. Since these graphs are constructed from whole genome sequences of a species population, they can become very large, making indexing one of the most challenging problems.
In this paper, we propose gindex, a novel indexing approach to solve the Graph Pattern Matching Problem based on the multidollar-BWT. Specifically, gindex aims to find all occurrences of a pattern in a sequence-labeled graph by overcoming two main limitations of GCSA2, one of the most widely used graph indexes: handling queries of arbitrary length and scaling to large graphs without pruning any complex regions. Moreover, we show how a smart preprocessing step can optimize the use of multidollar-BWT to skip small redundant sub-patterns and enhance gindex’s querying capabilities.
We demonstrate the effectiveness of our approach by comparing it to GCSA2 in terms of index construction and query time, using different preprocessing modes on three pangenome graphs: one built from Drosophila genomes and two produced by the Human Pangenome Reference Consortium.
The results show that gindex can scale on human pangenome graphs - which GCSA2 cannot index using large amounts of RAM - with acceptable memory and time requirements. Moreover, gindex achieves fast query times, although not as fast as GCSA2, which may produce false positives.
Cite as
Davide Cozzi, Brian Riccardi, Luca Denti, Simone Ciccolella, Kunihiko Sadakane, and Paola Bonizzoni. Pangenome Graph Indexing via the Multidollar-BWT. In 23rd International Symposium on Experimental Algorithms (SEA 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 338, pp. 13:1-13:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)
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@InProceedings{cozzi_et_al:LIPIcs.SEA.2025.13,
author = {Cozzi, Davide and Riccardi, Brian and Denti, Luca and Ciccolella, Simone and Sadakane, Kunihiko and Bonizzoni, Paola},
title = {{Pangenome Graph Indexing via the Multidollar-BWT}},
booktitle = {23rd International Symposium on Experimental Algorithms (SEA 2025)},
pages = {13:1--13:17},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-375-1},
ISSN = {1868-8969},
year = {2025},
volume = {338},
editor = {Mutzel, Petra and Prezza, Nicola},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SEA.2025.13},
URN = {urn:nbn:de:0030-drops-232515},
doi = {10.4230/LIPIcs.SEA.2025.13},
annote = {Keywords: Multidollar-BWT, Graph Index, Graph Pattern Matching, Pangenome Graph}
}
Document
Efficient Terabyte-Scale Text Compression via Stable Local Consistency and Parallel Grammar Processing
Abstract
We present compression algorithms designed to process terabyte-sized datasets in parallel. Our approach builds on locally consistent grammars, a lightweight form of compression, combined with simple post-processing techniques to achieve further space reductions. Locally consistent grammar algorithms are suitable for scaling as they need minimal satellite information to compact the text, but they are not inherently parallel. To enable parallelisation, we introduce a novel concept that we call stable local consistency. A grammar algorithm ALG is stable if for any pattern P occurring in a collection 𝒯 = {T_1, T_2, …, T_k}, instances ALG(T_1), ALG(T_2), …, ALG(T_k) independently produce cores for P with the same topology. In a locally consistent grammar, the core of P is a subset of nodes and edges in the parse tree of 𝒯 that remains the same in all the occurrences of P. This feature enables compression, but it only holds if ALG defines a common set of nonterminal symbols for the strings. Stability removes this restriction, allowing us to run ALG(T_1), ALG(T_2), …, ALG(T_k) in parallel and subsequently merge their grammars into a single output equivalent to that of ALG(𝒯). We implemented our ideas and tested them on massive datasets. Our experiments showed that our method could process 7.9 TB of bacterial genomes in around nine hours, using 16 threads and 0.43 bits/symbol of working memory, achieving a compression ratio of 85x.
Cite as
Diego Díaz-Domínguez. Efficient Terabyte-Scale Text Compression via Stable Local Consistency and Parallel Grammar Processing. In 23rd International Symposium on Experimental Algorithms (SEA 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 338, pp. 14:1-14:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)
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@InProceedings{diazdominguez:LIPIcs.SEA.2025.14,
author = {D{\'\i}az-Dom{\'\i}nguez, Diego},
title = {{Efficient Terabyte-Scale Text Compression via Stable Local Consistency and Parallel Grammar Processing}},
booktitle = {23rd International Symposium on Experimental Algorithms (SEA 2025)},
pages = {14:1--14:20},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-375-1},
ISSN = {1868-8969},
year = {2025},
volume = {338},
editor = {Mutzel, Petra and Prezza, Nicola},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SEA.2025.14},
URN = {urn:nbn:de:0030-drops-232525},
doi = {10.4230/LIPIcs.SEA.2025.14},
annote = {Keywords: Grammar compression, locally consistent parsing, hashing}
}
Document
Succinct Rank Dictionaries Revisited
Abstract
We study data structures for representing sets of m elements drawn from the universe [0..n-1] that support access and rank queries. A classical approach to this problem, foundational to the fields of succinct and compact data structures, is to represent the set as a bitvector X of n bits, where X[i] = 1 iff i is a member of the set. Our particular focus in this paper is on structures taking log₂{n choose m} + o(n) bits, which stem from the so-called RRR bitvector scheme (Raman et al., ACM Trans. Alg., 2007). In RRR bitvectors, X is conceptually divided into n/b blocks of b bits each. A block containing c 1 bits is then encoded using log₂ b + log₂{b choose c} bits, where log b bits are used to encode c, and log₂{b choose c} bits are used to say which of the {b choose c} possible combinations the block represents. In all existing RRR implementations the code assigned to a block is its lexicographical rank amongst the {b choose c} combinations of its class. In this paper we explore alternative non-lexicographical assignments of codes to blocks. We show these approaches can lead to faster query times and offer relevant space-time trade-offs in practice compared to state-of-the-art implementations (Gog and Petri, Software, Prac. & Exp., 2014) from the Succinct Data Structures Library.
Cite as
Saska Dönges and Simon J. Puglisi. Succinct Rank Dictionaries Revisited. In 23rd International Symposium on Experimental Algorithms (SEA 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 338, pp. 15:1-15:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)
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@InProceedings{donges_et_al:LIPIcs.SEA.2025.15,
author = {D\"{o}nges, Saska and Puglisi, Simon J.},
title = {{Succinct Rank Dictionaries Revisited}},
booktitle = {23rd International Symposium on Experimental Algorithms (SEA 2025)},
pages = {15:1--15:18},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-375-1},
ISSN = {1868-8969},
year = {2025},
volume = {338},
editor = {Mutzel, Petra and Prezza, Nicola},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SEA.2025.15},
URN = {urn:nbn:de:0030-drops-232530},
doi = {10.4230/LIPIcs.SEA.2025.15},
annote = {Keywords: data structures, data compression, succinct data structures, compressed data structures, weighted de Bruijn sequence, text indexing, string algorithms}
}
Document
Exact Lower Bounds for the Number of Comparisons in Selection
Abstract
Selection is the problem of finding the i-th smallest element among n elements. We apply computer search to find optimal algorithms for small instances of the selection problem. Using new algorithmic ideas, we establish tighter lower bounds for the number of comparisons required, denoted as V_i(n). Our results include optimal algorithms for n up to 15 and arbitrary i, and for n = 16 when i ≤ 6. We determine the precise values V₇(14) = 25, V₆(15) = V₇(15) = 26, and V₈(15) = 27, where previously, only a range was known.
Cite as
Josua Dörrer, Konrad Gendle, Johanna Betz, Julius von Smercek, Andreas Steding, and Florian Stober. Exact Lower Bounds for the Number of Comparisons in Selection. In 23rd International Symposium on Experimental Algorithms (SEA 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 338, pp. 16:1-16:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)
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@InProceedings{dorrer_et_al:LIPIcs.SEA.2025.16,
author = {D\"{o}rrer, Josua and Gendle, Konrad and Betz, Johanna and von Smercek, Julius and Steding, Andreas and Stober, Florian},
title = {{Exact Lower Bounds for the Number of Comparisons in Selection}},
booktitle = {23rd International Symposium on Experimental Algorithms (SEA 2025)},
pages = {16:1--16:15},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-375-1},
ISSN = {1868-8969},
year = {2025},
volume = {338},
editor = {Mutzel, Petra and Prezza, Nicola},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SEA.2025.16},
URN = {urn:nbn:de:0030-drops-232547},
doi = {10.4230/LIPIcs.SEA.2025.16},
annote = {Keywords: selection, lower bounds, exhaustive computer search}
}
Document
Computing the Exact Radius of Large Graphs
Abstract
The radius of a graph is an important structural parameter which plays a key role in social network analysis and related applications. It measures the minimum shortest path distance that is required to reach all nodes in the graph from a single node. A node from which all other nodes are within a distance equal to the radius is called a center of the graph. In a graph with n nodes and m edges, the center and the radius can be determined in Õ(nm) by computing shortest path distances between all pairs of nodes. Fine-grained complexity results suggest that asymptotically faster algorithms are unlikely to exist. In this paper, we describe a novel randomized algorithm for exact radius computation in weighted digraphs with an expected running time in Õ(d³m) where d is the so-called combinatorial dimension. Our methodology is inspired by Clarkson’s algorithm for LP-type problems. The value of d denotes the size of a basis, which is a smallest subset of nodes which enforce the same radius as the whole node set. While we show that there exist graphs with d ∈ Θ(n), our empirical analysis reveals that even large real-world graphs have small combinatorial dimension. This allows us to compute the radius in near-linear time on such instances. The significantly improved scalability can be clearly observed in our experimental evaluation on a diverse set of benchmark graphs.
Cite as
Stefan Funke, Claudius Proissl, and Sabine Storandt. Computing the Exact Radius of Large Graphs. In 23rd International Symposium on Experimental Algorithms (SEA 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 338, pp. 17:1-17:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)
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@InProceedings{funke_et_al:LIPIcs.SEA.2025.17,
author = {Funke, Stefan and Proissl, Claudius and Storandt, Sabine},
title = {{Computing the Exact Radius of Large Graphs}},
booktitle = {23rd International Symposium on Experimental Algorithms (SEA 2025)},
pages = {17:1--17:14},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-375-1},
ISSN = {1868-8969},
year = {2025},
volume = {338},
editor = {Mutzel, Petra and Prezza, Nicola},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SEA.2025.17},
URN = {urn:nbn:de:0030-drops-232555},
doi = {10.4230/LIPIcs.SEA.2025.17},
annote = {Keywords: Radius, Graph Center, LP-type, Combinatorial Dimension}
}
Document
Engineering Insights into Biclique Partitions and Fractional Binary Ranks of Matrices
Abstract
We investigate structural properties of the binary rank of Kronecker powers of binary matrices, equivalently, the biclique partition numbers of the corresponding bipartite graphs. To this end, we engineer a Column Generation approach to solve linear optimization problems for the fractional biclique partition number of bipartite graphs, specifically examining the Domino graph and its Kronecker powers. We address the challenges posed by the double exponential growth of the number of bicliques in increasing Kronecker powers. We discuss various strategies to generate suitable initial sets of bicliques, including an inductive method for increasing Kronecker powers. We show how to manage the number of active bicliques to improve running time and to stay within memory limits. Our computational results reveal that the fractional binary rank is not multiplicative with respect to the Kronecker product. Hence, there are binary matrices, and bipartite graphs, respectively, such as the Domino, where the asymptotic fractional binary rank is strictly smaller than the fractional binary rank. While we used our algorithm to reduce the upper bound, we formally prove that the fractional biclique cover number is a lower bound, which is at least as good as the widely used isolating (or fooling set) bound. For the Domino, we obtain that the asymptotic fractional binary rank lies in the interval [2,2.373]. Since our computational resources are not sufficient to further reduce the upper bound, we encourage further exploration using more substantial computing resources or further mathematical engineering techniques to narrow the gap and advance our understanding of biclique partitions, particularly, to settle the open question whether binary rank and biclique partition number are multiplicative with respect to the Kronecker product.
Cite as
Angikar Ghosal and Andreas Karrenbauer. Engineering Insights into Biclique Partitions and Fractional Binary Ranks of Matrices. In 23rd International Symposium on Experimental Algorithms (SEA 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 338, pp. 18:1-18:12, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)
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@InProceedings{ghosal_et_al:LIPIcs.SEA.2025.18,
author = {Ghosal, Angikar and Karrenbauer, Andreas},
title = {{Engineering Insights into Biclique Partitions and Fractional Binary Ranks of Matrices}},
booktitle = {23rd International Symposium on Experimental Algorithms (SEA 2025)},
pages = {18:1--18:12},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-375-1},
ISSN = {1868-8969},
year = {2025},
volume = {338},
editor = {Mutzel, Petra and Prezza, Nicola},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SEA.2025.18},
URN = {urn:nbn:de:0030-drops-232568},
doi = {10.4230/LIPIcs.SEA.2025.18},
annote = {Keywords: Asymptotic Binary Rank, Algorithm Engineering, Combinatorics of Bipartite Graphs, Linear Programming}
}
Document
GreedyML: A Parallel Algorithm for Maximizing Constrained Submodular Functions
Abstract
We describe a parallel approximation algorithm for maximizing monotone submodular functions subject to hereditary constraints on distributed memory multiprocessors. Our work is motivated by the need to solve submodular optimization problems on massive data sets, for practical contexts such as data summarization, machine learning, and graph sparsification.
Our work builds on the randomized distributed RandGreeDI algorithm, proposed by Barbosa, Ene, Nguyen, and Ward (2015). This algorithm computes a distributed solution by randomly partitioning the data among all the processors and then employing a single accumulation step in which all processors send their partial solutions to one processor. However, for large problems, the accumulation step exceeds the memory available on a processor, and the processor which performs the accumulation becomes a computational bottleneck.
Hence we propose a generalization of the RandGreeDI algorithm that employs multiple accumulation steps to reduce the memory required. We analyze the approximation ratio and the time complexity of the algorithm (in the BSP model). We evaluate the new GreedyML algorithm on three classes of problems, and report results from large-scale data sets with millions of elements. The results show that the GreedyML algorithm can solve problems where the sequential Greedy and distributed RandGreeDI algorithms fail due to memory constraints. For certain computationally intensive problems, the GreedyML algorithm is faster than the RandGreeDI algorithm. The observed approximation quality of the solutions computed by the GreedyML algorithm closely matches those obtained by the RandGreeDI algorithm on these problems.
Cite as
Shivaram Gopal, S M Ferdous, Alex Pothen, and Hemanta Maji. GreedyML: A Parallel Algorithm for Maximizing Constrained Submodular Functions. In 23rd International Symposium on Experimental Algorithms (SEA 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 338, pp. 19:1-19:21, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)
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@InProceedings{gopal_et_al:LIPIcs.SEA.2025.19,
author = {Gopal, Shivaram and Ferdous, S M and Pothen, Alex and Maji, Hemanta},
title = {{GreedyML: A Parallel Algorithm for Maximizing Constrained Submodular Functions}},
booktitle = {23rd International Symposium on Experimental Algorithms (SEA 2025)},
pages = {19:1--19:21},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-375-1},
ISSN = {1868-8969},
year = {2025},
volume = {338},
editor = {Mutzel, Petra and Prezza, Nicola},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SEA.2025.19},
URN = {urn:nbn:de:0030-drops-232572},
doi = {10.4230/LIPIcs.SEA.2025.19},
annote = {Keywords: Combinatorial optimization, submodular functions, distributed algorithms, approximation algorithms, data summarization}
}
Document
SimdMinimizers: Computing Random Minimizers, fast
Abstract
Motivation. Because of the rapidly-growing amount of sequencing data, computing sketches of large textual datasets has become an essential preprocessing task. These sketches are typically much smaller than the input sequences, but preserve sufficient information for downstream analysis. Minimizers are an especially popular sketching technique and used in a wide variety of applications. They sample at least one out of every w consecutive k-mers. As DNA sequencers are getting more accurate, some applications can afford to use a larger w and hence sparser and smaller sketches. And as sketches get smaller, their analysis becomes faster, so the time spent sketching the full-sized input becomes more of a bottleneck.
Methods. Our library simd-minimizers implements a random minimizer algorithm using SIMD instructions. It supports both AVX2 and NEON architectures. Its main novelty is two-fold. First, it splits the input into 8 chunks that are streamed over in parallel through all steps of the algorithm. This is enabled by using the completely deterministic two-stacks sliding window minimum algorithm, which seems not to have been used before for finding minimizers.
Results. Our library is up to 6.8× faster than a scalar implementation of the rescan method when w = 5 is small, and 3.4× faster for larger w = 19. Computing canonical minimizers is less than 50% slower than computing forward minimizers, and over 15× faster than the existing implementation in the minimizer-iter crate. Our library finds all (canonical) minimizers of a 3.2 Gbp human genome in 5.2 (resp. 6.7) seconds.
Cite as
Ragnar Groot Koerkamp and Igor Martayan. SimdMinimizers: Computing Random Minimizers, fast. In 23rd International Symposium on Experimental Algorithms (SEA 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 338, pp. 20:1-20:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)
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@InProceedings{grootkoerkamp_et_al:LIPIcs.SEA.2025.20,
author = {Groot Koerkamp, Ragnar and Martayan, Igor},
title = {{SimdMinimizers: Computing Random Minimizers, fast}},
booktitle = {23rd International Symposium on Experimental Algorithms (SEA 2025)},
pages = {20:1--20:19},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-375-1},
ISSN = {1868-8969},
year = {2025},
volume = {338},
editor = {Mutzel, Petra and Prezza, Nicola},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SEA.2025.20},
URN = {urn:nbn:de:0030-drops-232581},
doi = {10.4230/LIPIcs.SEA.2025.20},
annote = {Keywords: Minimizers, Randomized algorithms, Sketching, Hashing}
}
Document
PtrHash: Minimal Perfect Hashing at RAM Throughput
Abstract
Motivation. Given a set K of n keys, a minimal perfect hash function (MPHF) is a collision-free bijective map H_mphf from K to {0, … , n-1}. These functions have uses in databases, search engines, and are used in bioinformatics indexing tools such as Pufferfish (using BBHash), and Piscem (PTHash). PTHash is also used in SSHash, a data structure on k-mers that supports membership queries. PTHash only takes around 5% of the total space of SSHash, and thus, trading slightly more space for faster queries is beneficial. Thus, this work presents a (minimal) perfect hash function that first prioritizes query throughput, while also allowing efficient construction for 10⁹ or more elements using 2.4 bits of memory per key.
Contributions. Both PTHash and PHOBIC first map all n keys to n/λ < n buckets. Then, each bucket stores a pilot that controls the final hash value of the keys mapping to it. PtrHash builds on this by using 1) fixed-width (uncompressed) 8-bit pilots, 2) a construction algorithm similar to Cuckoo hashing to find suitable pilot values. Further, it partitions the keys, so that keys in each part map to their own set of slots. PtrHash 3) uses the same number of buckets and slots for each part, with 4) a single remap table to map intermediate positions ≥ n to < n, 5) encoded using per-cacheline Elias-Fano coding. Lastly, 6) PtrHash supports streaming queries, where we use prefetching to answer a stream of multiple queries more efficiently than one-by-one processing.
Results. With default parameters, PtrHash takes 2.4 bits per key. On 300 million string keys, PtrHash is as fast or faster to build than other MPHFs at a similar size, and at least 2.1× faster to query. When streaming multiple queries, this improves to 3.3× speedup over the fastest alternative, while also being significantly faster to construct. When using 10⁹ integer keys instead, query times are as low as 12 ns/key when iterating in a for loop, or even down to 8 ns/key when using the streaming approach, just short of the 7.4 ns inverse throughput of random memory accesses.
Cite as
Ragnar Groot Koerkamp. PtrHash: Minimal Perfect Hashing at RAM Throughput. In 23rd International Symposium on Experimental Algorithms (SEA 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 338, pp. 21:1-21:21, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)
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@InProceedings{grootkoerkamp:LIPIcs.SEA.2025.21,
author = {Groot Koerkamp, Ragnar},
title = {{PtrHash: Minimal Perfect Hashing at RAM Throughput}},
booktitle = {23rd International Symposium on Experimental Algorithms (SEA 2025)},
pages = {21:1--21:21},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-375-1},
ISSN = {1868-8969},
year = {2025},
volume = {338},
editor = {Mutzel, Petra and Prezza, Nicola},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SEA.2025.21},
URN = {urn:nbn:de:0030-drops-232597},
doi = {10.4230/LIPIcs.SEA.2025.21},
annote = {Keywords: Minimal perfect hashing, Compressed Data Structures}
}
Document
Concurrent Iterated Local Search for the Maximum Weight Independent Set Problem
Abstract
The Maximum Weight Independent Set problem is a fundamental NP-hard problem in combinatorial optimization with several real-world applications. Given an undirected vertex-weighted graph, the problem is to find a subset of the vertices with the highest possible weight under the constraint that no two vertices in the set can share an edge. This work presents a new iterated local search heuristic called CHILS (Concurrent Hybrid Iterated Local Search). The implementation of CHILS is specifically designed to handle large graphs of varying densities. CHILS outperforms the current state-of-the-art on commonly used benchmark instances, especially on the largest instances. As an added benefit, CHILS can run in parallel to leverage the power of multicore processors. The general technique used in CHILS is a new concurrent metaheuristic called Concurrent Difference-Core Heuristic that can also be applied to other combinatorial problems.
Cite as
Ernestine Großmann, Kenneth Langedal, and Christian Schulz. Concurrent Iterated Local Search for the Maximum Weight Independent Set Problem. In 23rd International Symposium on Experimental Algorithms (SEA 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 338, pp. 22:1-22:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)
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@InProceedings{gromann_et_al:LIPIcs.SEA.2025.22,
author = {Gro{\ss}mann, Ernestine and Langedal, Kenneth and Schulz, Christian},
title = {{Concurrent Iterated Local Search for the Maximum Weight Independent Set Problem}},
booktitle = {23rd International Symposium on Experimental Algorithms (SEA 2025)},
pages = {22:1--22:18},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-375-1},
ISSN = {1868-8969},
year = {2025},
volume = {338},
editor = {Mutzel, Petra and Prezza, Nicola},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SEA.2025.22},
URN = {urn:nbn:de:0030-drops-232600},
doi = {10.4230/LIPIcs.SEA.2025.22},
annote = {Keywords: Randomized Local Search, Heuristics, Maximum Weight Independent Set, Algorithm Engineering, Parallel Computing}
}
Document
Elias-Fano Compression for Space-Efficient Rank and Select Structures
Abstract
Bit vectors are an important component in many data structures. Such data structures are used in a variety of applications and domains including databases, search engines, and computational biology. Many use cases depend on being able to perform rank and/or select queries on the bit vector. No existing rank and select structure enabling these queries is most efficient both for space and for time; there is a tradeoff between the two. In practice, the smallest rank and select data structures, cs-poppy and pasta-flat, impose a space overhead of 3.51%, or 3.125% if only rank needs to be supported. In this paper, we present a new data structure, orzo, which reduces the overhead of the rank component by a further 26.5%. We preserve desirable cache-centric design decisions made in prior work, which allows us to minimize the performance penalty of creating a smaller data structure.
Cite as
Lannie Dalton Hough and Abhinav Bhatele. Elias-Fano Compression for Space-Efficient Rank and Select Structures. In 23rd International Symposium on Experimental Algorithms (SEA 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 338, pp. 23:1-23:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)
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@InProceedings{hough_et_al:LIPIcs.SEA.2025.23,
author = {Hough, Lannie Dalton and Bhatele, Abhinav},
title = {{Elias-Fano Compression for Space-Efficient Rank and Select Structures}},
booktitle = {23rd International Symposium on Experimental Algorithms (SEA 2025)},
pages = {23:1--23:15},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-375-1},
ISSN = {1868-8969},
year = {2025},
volume = {338},
editor = {Mutzel, Petra and Prezza, Nicola},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SEA.2025.23},
URN = {urn:nbn:de:0030-drops-232617},
doi = {10.4230/LIPIcs.SEA.2025.23},
annote = {Keywords: rank and select, cache-aware, succinct data structures, bit vector}
}
Document
A New Relaxation for Tree-Based Problems and Minimum Power-Cost Spanning Trees
Abstract
In this paper, we investigate lower bounds of tree-based optimization problems in order to obtain effective exact algorithms, such as branch-and-bound algorithms. Our new approach inherits the development of dynamic programming algorithms for constrained shortest path problems, as they occur as subproblems in Lagrangian relaxation algorithms and column generation-based algorithms for variants of the Vehicle Routing Problem. In the q-route relaxation, paths must satisfy a capacity constraint while the elementarity constraint is relaxed, that is, paths may contain cycles. An analogue of q-routes for tree optimization problems are q-arbs, a structure that relaxes elementarity for arborescences. We introduce a generalized formulation of q-arbs for a broad class of tree-based problems, and apply the neighborhood restrictions of so-called ng-routes to them to obtain tighter bounds. We apply the new dynamic programming approach to the Minimum Power-Cost Spanning Tree Problem and show empirically that the resulting bounds are often better than traditional LP-based lower bounds of (mixed) integer programming models.
Cite as
Luzie Marianczuk, Ernst Althaus, Stefan Irnich, and Marc E. Pfetsch. A New Relaxation for Tree-Based Problems and Minimum Power-Cost Spanning Trees. In 23rd International Symposium on Experimental Algorithms (SEA 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 338, pp. 24:1-24:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)
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@InProceedings{marianczuk_et_al:LIPIcs.SEA.2025.24,
author = {Marianczuk, Luzie and Althaus, Ernst and Irnich, Stefan and Pfetsch, Marc E.},
title = {{A New Relaxation for Tree-Based Problems and Minimum Power-Cost Spanning Trees}},
booktitle = {23rd International Symposium on Experimental Algorithms (SEA 2025)},
pages = {24:1--24:18},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-375-1},
ISSN = {1868-8969},
year = {2025},
volume = {338},
editor = {Mutzel, Petra and Prezza, Nicola},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SEA.2025.24},
URN = {urn:nbn:de:0030-drops-232620},
doi = {10.4230/LIPIcs.SEA.2025.24},
annote = {Keywords: lower bounds, symmetric connectivity, power range assignment, dynamic programming, optimal substructure}
}
Document
Blocked Bloom Filters with Choices
Abstract
Probabilistic filters are approximate set membership data structures that represent a set of keys in small space, and answer set membership queries without false negative answers, but with a certain allowed false positive probability. Such filters are widely used in database systems, networks, storage systems and in biological sequence analysis because of their fast query times and low space requirements. Starting with Bloom filters in the 1970s, many filter data structures have been developed, each with its own advantages and disadvantages, e.g., Blocked Bloom filters, Cuckoo filters, XOR filters, Ribbon filters, and more.
We introduce Blocked Bloom filters with choices that work similarly to Blocked Bloom filters, except that for each key there are two (or more) alternative choices of blocks where the key’s information may be stored. When inserting a key, we select the block using a cost function which takes into account the current load and the additional number of bits to be set in the candidate blocks. The result is a filter that partially inherits the advantages of a Blocked Bloom filter, such as the ability to insert keys rapidly online or the ability to slightly overload the filter with only a small penalty to the false positive rate. At the same time, it avoids the major disadvantage of a Blocked Bloom filter, namely the larger space consumption. Our new data structure uses less space at the same false positive rate, or has a lower false positive rate at the same space consumption as a Blocked Bloom filter. We discuss the methodology, cost functions for block selection, engineered implementation, a detailed performance evaluation and use cases in bioinformatics of Blocked Bloom filters with choices, showing that they can be of practical value.
The implementation of the evaluated filters and the workflows used are provided via Gitlab at https://gitlab.com/rahmannlab/blowchoc-filters.
Cite as
Johanna Elena Schmitz, Jens Zentgraf, and Sven Rahmann. Blocked Bloom Filters with Choices. In 23rd International Symposium on Experimental Algorithms (SEA 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 338, pp. 25:1-25:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)
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@InProceedings{schmitz_et_al:LIPIcs.SEA.2025.25,
author = {Schmitz, Johanna Elena and Zentgraf, Jens and Rahmann, Sven},
title = {{Blocked Bloom Filters with Choices}},
booktitle = {23rd International Symposium on Experimental Algorithms (SEA 2025)},
pages = {25:1--25:20},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-375-1},
ISSN = {1868-8969},
year = {2025},
volume = {338},
editor = {Mutzel, Petra and Prezza, Nicola},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SEA.2025.25},
URN = {urn:nbn:de:0030-drops-232631},
doi = {10.4230/LIPIcs.SEA.2025.25},
annote = {Keywords: Probabilistic filter, Bloom filter, power of two choices}
}
Document
Mixed-Integer Optimization for Loopless Flux Distributions in Metabolic Networks
Abstract
Constraint-based metabolic models can be used to investigate the intracellular physiology of microorganisms. These models couple genes to reactions, and typically seek to predict metabolite fluxes that optimize some biologically important metric. Classical techniques, like Flux Balance Analysis (FBA), formulate the metabolism of a microbe as an optimization problem where growth rate is maximized. While FBA has found widespread use, it often leads to thermodynamically infeasible solutions that contain internal cycles (loops). To address this shortcoming, Loopless-Flux Balance Analysis (ll-FBA) seeks to predict flux distributions that do not contain these loops. ll-FBA is a disjunctive program, usually reformulated as a mixed-integer program, and is challenging to solve for biological models that often contain thousands of reactions and metabolites. In this paper, we compare various reformulations of ll-FBA and different solution approaches.
Overall, the combinatorial Benders' decomposition is the most promising of the tested approaches with which we could solve most instances. However, the model size and numerical instability pose a challenge to the combinatorial Benders' method.
Cite as
Hannah Troppens, Mathieu Besançon, St. Elmo Wilken, and Sebastian Pokutta. Mixed-Integer Optimization for Loopless Flux Distributions in Metabolic Networks. In 23rd International Symposium on Experimental Algorithms (SEA 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 338, pp. 26:1-26:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)
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@InProceedings{troppens_et_al:LIPIcs.SEA.2025.26,
author = {Troppens, Hannah and Besan\c{c}on, Mathieu and Wilken, St. Elmo and Pokutta, Sebastian},
title = {{Mixed-Integer Optimization for Loopless Flux Distributions in Metabolic Networks}},
booktitle = {23rd International Symposium on Experimental Algorithms (SEA 2025)},
pages = {26:1--26:18},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-375-1},
ISSN = {1868-8969},
year = {2025},
volume = {338},
editor = {Mutzel, Petra and Prezza, Nicola},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SEA.2025.26},
URN = {urn:nbn:de:0030-drops-232646},
doi = {10.4230/LIPIcs.SEA.2025.26},
annote = {Keywords: Systems biology, mixed-integer optimization, disjunctive optimization, flux balance analysis}
}
Document
Sparsity-Driven Aggregation of Mixed Integer Programs
Abstract
Cutting planes are crucial for the performance of branch-and-cut algorithms for solving mixed-integer programming (MIP) problems, and linear row aggregation has been successfully applied to better leverage the potential of several major families of MIP cutting planes. This paper formulates the problem of finding good quality aggregations as an 𝓁₀-norm minimization problem and employs a combination of the lasso method and iterative reweighting to efficiently find sparse solutions corresponding to good aggregations. A comparative analysis of the proposed algorithm and the state-of-the-art greedy heuristic approach is presented, showing that the greedy heuristic implements a stepwise selection algorithm for the 𝓁₀-norm minimization problem. Further, we present an example where our approach succeeds, whereas the standard heuristic fails to find an aggregation with desired properties. The algorithm is implemented within the constraint integer programming solver SCIP, and computational experiments on the MIPLIB 2017 benchmark show that although the algorithm leads to slowdowns on relatively "easier" instances, our aggregation approach decreases the mean running time on a subset of challenging instances and leads to smaller branch-and-bound trees.
Cite as
Liding Xu, Gioni Mexi, and Ksenia Bestuzheva. Sparsity-Driven Aggregation of Mixed Integer Programs. In 23rd International Symposium on Experimental Algorithms (SEA 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 338, pp. 27:1-27:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)
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@InProceedings{xu_et_al:LIPIcs.SEA.2025.27,
author = {Xu, Liding and Mexi, Gioni and Bestuzheva, Ksenia},
title = {{Sparsity-Driven Aggregation of Mixed Integer Programs}},
booktitle = {23rd International Symposium on Experimental Algorithms (SEA 2025)},
pages = {27:1--27:15},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-375-1},
ISSN = {1868-8969},
year = {2025},
volume = {338},
editor = {Mutzel, Petra and Prezza, Nicola},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SEA.2025.27},
URN = {urn:nbn:de:0030-drops-232652},
doi = {10.4230/LIPIcs.SEA.2025.27},
annote = {Keywords: mixed integer linear programming, cutting plane, valid inequality, separation, aggregation, projection, sparse optimization}
}