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Documents authored by Kalantarzadeh, Sina


Document
Improved Upper Bounds on Multiflow-Multicut Gaps in Cactus Graphs

Authors: Sina Kalantarzadeh and Nikhil Kumar

Published in: LIPIcs, Volume 360, 45th IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science (FSTTCS 2025)


Abstract
Given a set of source-sink pairs, the maximum multiflow problem asks for the largest total amount of flow that can be feasibly routed between them. The minimum multicut problem, which is dual to multiflow, seeks the lowest-cost set of edges whose removal disconnects all source-sink pairs. It is straightforward to see that the value of a minimum multicut is at least that of the corresponding maximum multiflow. The ratio between the two is known as the multiflow-multicut gap. The classical max-flow min-cut theorem tells us that this gap is exactly one when there is only a single source-sink pair. However, for multiple source-sink pairs, the gap can be arbitrarily large. In this work, we investigate the multiflow-multicut gap in cactus graphs, and establish the following results (i) tight upper bound of 1.5 for cycle (ii) an upper bound of 2 + 2/(ln 2) < 3.45 for general cactus graph (iii) tight upper bound of 2 for unicyclic graphs, where the graph contains exactly one cycle (iv) tight upper bound of 2 for path cactus graphs, where cycles are arranged along a single path. We develop novel generalizations of the classical rounding algorithm to establish our results.

Cite as

Sina Kalantarzadeh and Nikhil Kumar. Improved Upper Bounds on Multiflow-Multicut Gaps in Cactus Graphs. In 45th IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science (FSTTCS 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 360, pp. 40:1-40:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)


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@InProceedings{kalantarzadeh_et_al:LIPIcs.FSTTCS.2025.40,
  author =	{Kalantarzadeh, Sina and Kumar, Nikhil},
  title =	{{Improved Upper Bounds on Multiflow-Multicut Gaps in Cactus Graphs}},
  booktitle =	{45th IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science (FSTTCS 2025)},
  pages =	{40:1--40:19},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-406-2},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{360},
  editor =	{Aiswarya, C. and Mehta, Ruta and Roy, Subhajit},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.FSTTCS.2025.40},
  URN =		{urn:nbn:de:0030-drops-251205},
  doi =		{10.4230/LIPIcs.FSTTCS.2025.40},
  annote =	{Keywords: Approximation Algorithms, Randomized Algorithms, Linear Programming, Graph Algorithms, Multicut, Multicommodity flow}
}
Document
APPROX
Improved Lower Bounds on Multiflow-Multicut Gaps

Authors: Sina Kalantarzadeh and Nikhil Kumar

Published in: LIPIcs, Volume 353, Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2025)


Abstract
Given a set of source-sink pairs, the maximum multiflow problem asks for the maximum total amount of flow that can be feasibly routed between them. The minimum multicut, a dual problem to multiflow, seeks the minimum-cost set of edges whose removal disconnects all the source-sink pairs. It is easy to see that the value of the minimum multicut is at least that of the maximum multiflow, and their ratio is called the multiflow-multicut gap. The classical max-flow min-cut theorem states that when there is only one source-sink pair, the gap is exactly one. However, in general, it is well known that this gap can be arbitrarily large. In this paper, we study this gap for classes of planar graphs and establish improved lower bound results. In particular, we show that this gap is at least 20/9 for the class of planar graphs, improving upon the decades-old lower bound of 2. More importantly, we develop new techniques for proving such a lower bound, which may be useful in other settings as well.

Cite as

Sina Kalantarzadeh and Nikhil Kumar. Improved Lower Bounds on Multiflow-Multicut Gaps. In Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 353, pp. 14:1-14:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)


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@InProceedings{kalantarzadeh_et_al:LIPIcs.APPROX/RANDOM.2025.14,
  author =	{Kalantarzadeh, Sina and Kumar, Nikhil},
  title =	{{Improved Lower Bounds on Multiflow-Multicut Gaps}},
  booktitle =	{Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2025)},
  pages =	{14:1--14:18},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-397-3},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{353},
  editor =	{Ene, Alina and Chattopadhyay, Eshan},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.APPROX/RANDOM.2025.14},
  URN =		{urn:nbn:de:0030-drops-243803},
  doi =		{10.4230/LIPIcs.APPROX/RANDOM.2025.14},
  annote =	{Keywords: Approximation Algorithms, Randomized Algorithms, Linear Programming, Graph Algorithms, Scheduling, Multicut, Multiflow}
}
Document
APPROX
A Randomized Rounding Approach for DAG Edge Deletion

Authors: Sina Kalantarzadeh, Nathan Klein, and Victor Reis

Published in: LIPIcs, Volume 353, Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2025)


Abstract
In the DAG Edge Deletion problem, we are given an edge-weighted directed acyclic graph and a parameter k, and the goal is to delete the minimum weight set of edges so that the resulting graph has no paths of length k. This problem, which has applications to scheduling, was introduced in 2015 by Kenkre, Pandit, Purohit, and Saket. They gave a k-approximation and showed that it is UGC-Hard to approximate better than ⌊0.5k⌋ for any constant k ≥ 4 using a work of Svensson from 2012. The approximation ratio was improved to 2/3(k+1) by Klein and Wexler in 2016. In this work, we introduce a randomized rounding framework based on distributions over vertex labels in [0,1]. The most natural distribution is to sample labels independently from the uniform distribution over [0,1]. We show this leads to a (2-√2)(k+1) ≈ 0.585(k+1)-approximation. By using a modified (but still independent) label distribution, we obtain a 0.549(k+1)-approximation for the problem, as well as show that no independent distribution over labels can improve our analysis to below 0.542(k+1). Finally, we show a 0.5(k+1)-approximation for bipartite graphs and for instances with structured LP solutions. Whether this ratio can be obtained in general is open.

Cite as

Sina Kalantarzadeh, Nathan Klein, and Victor Reis. A Randomized Rounding Approach for DAG Edge Deletion. In Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 353, pp. 18:1-18:13, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)


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@InProceedings{kalantarzadeh_et_al:LIPIcs.APPROX/RANDOM.2025.18,
  author =	{Kalantarzadeh, Sina and Klein, Nathan and Reis, Victor},
  title =	{{A Randomized Rounding Approach for DAG Edge Deletion}},
  booktitle =	{Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2025)},
  pages =	{18:1--18:13},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-397-3},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{353},
  editor =	{Ene, Alina and Chattopadhyay, Eshan},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.APPROX/RANDOM.2025.18},
  URN =		{urn:nbn:de:0030-drops-243840},
  doi =		{10.4230/LIPIcs.APPROX/RANDOM.2025.18},
  annote =	{Keywords: Approximation Algorithms, Randomized Algorithms, Linear Programming, Graph Algorithms, Scheduling}
}
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