5 Search Results for "Zoppis, Italo"

Document
DOI: 10.4230/LIPIcs.IPEC.2025.12
Timeline Problems in Temporal Graphs: Vertex Cover vs. Dominating Set

Authors: Anton Herrmann, Christian Komusiewicz, Nils Morawietz, and Frank Sommer

Published in: LIPIcs, Volume 358, 20th International Symposium on Parameterized and Exact Computation (IPEC 2025)

Abstract
A temporal graph is a finite sequence of graphs, called snapshots, over the same vertex set. Many temporal graph problems turn out to be much more difficult than their static counterparts. One such problem is Timeline Vertex Cover (also known as MinTimeline_∞), a temporal analogue to the classical Vertex Cover problem. In this problem, one is given a temporal graph 𝒢 and two integers k and 𝓁, and the goal is to cover each edge of each snapshot by selecting for each vertex at most k activity intervals of length at most 𝓁 each. Here, an edge uv in the ith snapshot is covered, if an activity interval of u or v is active at time i. In this work, we continue the algorithmic study of Timeline Vertex Cover and introduce the Timeline Dominating Set problem where we want to dominate all vertices in each snapshot by the selected activity intervals. We analyze both problems from a classical and parameterized point of view and also consider partial problem versions, where the goal is to cover (dominate) at least t edges (vertices) of the snapshots. With respect to the parameterized complexity, we consider the temporal graph parameters vertex-interval-membership-width (vimw) and interval-membership-width (imw). We show that all considered problems admit FPT-algorithms when parameterized by vimw+k+𝓁. This provides a smaller parameter combination than the ones used for previously known FPT-algorithms for Timeline Vertex Cover. Surprisingly, for imw+k+𝓁, Timeline Dominating Set turns out to be easier than Timeline Vertex Cover, by also admitting an FPT-algorithm, whereas the vertex cover version is NP-hard even if imw+k+𝓁 is constant. We also consider parameterization by combinations of n, the vertex set size, with k or 𝓁 and parameterization by t. Here, we show for example that both partial problems are fixed-parameter tractable for t which significantly improves and generalizes a previous result for a special case of Partial Timeline Vertex Cover with k = 1.
Cite as

Anton Herrmann, Christian Komusiewicz, Nils Morawietz, and Frank Sommer. Timeline Problems in Temporal Graphs: Vertex Cover vs. Dominating Set. In 20th International Symposium on Parameterized and Exact Computation (IPEC 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 358, pp. 12:1-12:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{herrmann_et_al:LIPIcs.IPEC.2025.12,
  author =	{Herrmann, Anton and Komusiewicz, Christian and Morawietz, Nils and Sommer, Frank},
  title =	{{Timeline Problems in Temporal Graphs: Vertex Cover vs. Dominating Set}},
  booktitle =	{20th International Symposium on Parameterized and Exact Computation (IPEC 2025)},
  pages =	{12:1--12:18},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-407-9},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{358},
  editor =	{Agrawal, Akanksha and van Leeuwen, Erik Jan},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.IPEC.2025.12},
  URN =		{urn:nbn:de:0030-drops-251446},
  doi =		{10.4230/LIPIcs.IPEC.2025.12},
  annote =	{Keywords: NP-hard problem, FPT-algorithm, interval-membership-width, Color coding}
}
Document
DOI: 10.4230/LIPIcs.TIME.2025.8
Heuristics for Covering the Timeline in Temporal Graphs

Authors: Riccardo Dondi, Rares-Ioan Mateiu, and Alexandru Popa

Published in: LIPIcs, Volume 355, 32nd International Symposium on Temporal Representation and Reasoning (TIME 2025)

Abstract
We consider a variant of the Vertex Cover problem on temporal graphs, called Minimum Timeline Cover (k-MinTimelineCover). Temporal graphs are used to model complex systems, describing how edges (relations) change in a discrete time domain. The k-MinTimelineCover problem has been introduced in complex data summarization and synthesis jobs. Given a temporal graph G, k-MinTimelineCover asks to define k activity intervals for each vertex, such that each temporal edge is covered by at least one active interval. The objective function is the minimization of the sum of interval lengths. k-MinTimelineCover is NP-hard and even hard to approximate within any factor for k > 1. While the literature has mainly focused on the cases k = 1, in this contribution we consider the case k > 1. We first present an ILP formulation that is able to solve the problem on moderate size instances. Then we develop an efficient heuristic, based on local search which is built on top of the solution of an existing literature method. Finally, we present an experimental evaluation of our algorithms on synthetic data sets, that shows in particular that our heuristic has a consistent improvement on the state-of-the art method.
Cite as

Riccardo Dondi, Rares-Ioan Mateiu, and Alexandru Popa. Heuristics for Covering the Timeline in Temporal Graphs. In 32nd International Symposium on Temporal Representation and Reasoning (TIME 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 355, pp. 8:1-8:13, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{dondi_et_al:LIPIcs.TIME.2025.8,
  author =	{Dondi, Riccardo and Mateiu, Rares-Ioan and Popa, Alexandru},
  title =	{{Heuristics for Covering the Timeline in Temporal Graphs}},
  booktitle =	{32nd International Symposium on Temporal Representation and Reasoning (TIME 2025)},
  pages =	{8:1--8:13},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-401-7},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{355},
  editor =	{Vidal, Thierry and Wa{\l}\k{e}ga, Przemys{\l}aw Andrzej},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.TIME.2025.8},
  URN =		{urn:nbn:de:0030-drops-244542},
  doi =		{10.4230/LIPIcs.TIME.2025.8},
  annote =	{Keywords: Temporal Networks, Activity Timeline, Vertex Cover, Heuristic, Dynamic Programming}
}
Document
DOI: 10.4230/LIPIcs.CPM.2025.1
Representing Paths in Digraphs

Authors: Riccardo Dondi and Alexandru Popa

Published in: LIPIcs, Volume 331, 36th Annual Symposium on Combinatorial Pattern Matching (CPM 2025)

Abstract
In this contribution we consider two combinatorial problems related to graph string matching, motivated by recent approaches in computational genomics. Given a DAG where each node is labeled by a symbol, the problems aim to find a path in the DAG whose nodes contain all (or the maximum number of) symbols of the alphabet. We introduce a decision problem, Σ-Representing Path, that asks whether there exists a path that contains all the symbols of the alphabet, and an optimization problem, called Maximum Representing Path, that asks for a path that contains the maximum number of symbols. We analyze the complexity of the problems, showing the NP-completeness of {Σ-Representing Path} when each symbol labels at most three nodes in the DAG, and showing the APX-hardness of Maximum Representing Path when each symbol labels at most two nodes in the DAG. We complement the first result by giving a polynomial-time algorithm for Σ-Representing Path when each symbol labels at most two nodes in the DAG. Then we investigate the parameterized complexity of the two problems when the DAG has a limited distance from a set of disjoint paths and we show that both problems are W[1]-hard for this parameter. We consider the approximation of Maximum Representing Path, giving an approximation algorithm of factor √OPT, where OPT is the value of an optimal solution of the problem. We also show that Maximum Representing Path cannot be approximated within factor e/(e-1) - α, for any constant α > 0, unless NP ⊆ DTIME(|V|^{O(log log |V|)}) (V is the set of nodes of the DAG).
Cite as

Riccardo Dondi and Alexandru Popa. Representing Paths in Digraphs. In 36th Annual Symposium on Combinatorial Pattern Matching (CPM 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 331, pp. 1:1-1:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{dondi_et_al:LIPIcs.CPM.2025.1,
  author =	{Dondi, Riccardo and Popa, Alexandru},
  title =	{{Representing Paths in Digraphs}},
  booktitle =	{36th Annual Symposium on Combinatorial Pattern Matching (CPM 2025)},
  pages =	{1:1--1:15},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-369-0},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{331},
  editor =	{Bonizzoni, Paola and M\"{a}kinen, Veli},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CPM.2025.1},
  URN =		{urn:nbn:de:0030-drops-230954},
  doi =		{10.4230/LIPIcs.CPM.2025.1},
  annote =	{Keywords: Graph String Matching, Computational Complexity, Parameterized Complexity, Algorithms}
}
Document
DOI: 10.4230/LIPIcs.TIME.2024.20
FastMinTC+: A Fast and Effective Heuristic for Minimum Timeline Cover on Temporal Networks

Authors: Giorgio Lazzarinetti, Sara Manzoni, Italo Zoppis, and Riccardo Dondi

Published in: LIPIcs, Volume 318, 31st International Symposium on Temporal Representation and Reasoning (TIME 2024)

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.
Cite as

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)

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@InProceedings{lazzarinetti_et_al:LIPIcs.TIME.2024.20,
  author =	{Lazzarinetti, Giorgio and Manzoni, Sara and Zoppis, Italo and Dondi, Riccardo},
  title =	{{FastMinTC+: A Fast and Effective Heuristic for Minimum Timeline Cover on Temporal Networks}},
  booktitle =	{31st International Symposium on Temporal Representation and Reasoning (TIME 2024)},
  pages =	{20:1--20:18},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-349-2},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{318},
  editor =	{Sala, Pietro and Sioutis, Michael and Wang, Fusheng},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.TIME.2024.20},
  URN =		{urn:nbn:de:0030-drops-212275},
  doi =		{10.4230/LIPIcs.TIME.2024.20},
  annote =	{Keywords: Temporal Networks, Activity Timeline, Timeline Cover, Vertex Cover, Optimization, Heuristic}
}
Document
DOI: 10.4230/LIPIcs.CPM.2017.14
The Longest Filled Common Subsequence Problem

Authors: Mauro Castelli, Riccardo Dondi, Giancarlo Mauri, and Italo Zoppis

Published in: LIPIcs, Volume 78, 28th Annual Symposium on Combinatorial Pattern Matching (CPM 2017)

Abstract
Inspired by a recent approach for genome reconstruction from incomplete data, we consider a variant of the longest common subsequence problem for the comparison of two sequences, one of which is incomplete, i.e. it has some missing elements. The new combinatorial problem, called Longest Filled Common Subsequence, given two sequences A and B, and a multiset M of symbols missing in B, asks for a sequence B* obtained by inserting the symbols of M into B so that B* induces a common subsequence with A of maximum length. First, we investigate the computational and approximation complexity of the problem and we show that it is NP-hard and APX-hard when A contains at most two occurrences of each symbol. Then, we give a 3/5 approximation algorithm for the problem. Finally, we present a fixed-parameter algorithm, when the problem is parameterized by the number of symbols inserted in B that "match" symbols of A.
Cite as

Mauro Castelli, Riccardo Dondi, Giancarlo Mauri, and Italo Zoppis. The Longest Filled Common Subsequence Problem. In 28th Annual Symposium on Combinatorial Pattern Matching (CPM 2017). Leibniz International Proceedings in Informatics (LIPIcs), Volume 78, pp. 14:1-14:13, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2017)

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@InProceedings{castelli_et_al:LIPIcs.CPM.2017.14,
  author =	{Castelli, Mauro and Dondi, Riccardo and Mauri, Giancarlo and Zoppis, Italo},
  title =	{{The Longest Filled Common Subsequence Problem}},
  booktitle =	{28th Annual Symposium on Combinatorial Pattern Matching (CPM 2017)},
  pages =	{14:1--14:13},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-039-2},
  ISSN =	{1868-8969},
  year =	{2017},
  volume =	{78},
  editor =	{K\"{a}rkk\"{a}inen, Juha and Radoszewski, Jakub and Rytter, Wojciech},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CPM.2017.14},
  URN =		{urn:nbn:de:0030-drops-73293},
  doi =		{10.4230/LIPIcs.CPM.2017.14},
  annote =	{Keywords: longest common subsequence, approximation algorithms, computational complexity, fixed-parameter algorithms}
}
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