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Documents authored by Cslovjecsek, Jana

Document
DOI: 10.4230/LIPIcs.ESA.2024.43
Parameterized Approximation for Maximum Weight Independent Set of Rectangles and Segments

Authors: Jana Cslovjecsek, Michał Pilipczuk, and Karol Węgrzycki

Published in: LIPIcs, Volume 308, 32nd Annual European Symposium on Algorithms (ESA 2024)

Abstract
In the Maximum Weight Independent Set of Rectangles problem (MWISR) we are given a weighted set of n axis-parallel rectangles in the plane. The task is to find a subset of pairwise non-overlapping rectangles with the maximum possible total weight. This problem is NP-hard and the best-known polynomial-time approximation algorithm, due to Chalermsook and Walczak [SODA 2021], achieves approximation factor 𝒪(log log n). While in the unweighted setting, constant factor approximation algorithms are known, due to Mitchell [FOCS 2021] and to Gálvez et al. [SODA 2022], it remains open to extend these techniques to the weighted setting. In this paper, we consider MWISR through the lens of parameterized approximation. Grandoni, Kratsch and Wiese [ESA 2019] gave a (1-ε)-approximation algorithm running in k^{𝒪(k/ε⁸)} n^{𝒪(1/ε⁸)} time, where k is the number of rectangles in an optimum solution. Unfortunately, their algorithm works only in the unweighted setting and they left it as an open problem to give a parameterized approximation scheme in the weighted setting. We give a parameterized approximation algorithm for MWISR that given a parameter k ∈ ℕ, finds a set of non-overlapping rectangles of weight at least (1-ε) opt_k in 2^{𝒪(k log(k/ε))} n^{𝒪(1/ε)} time, where opt_k is the maximum weight of a solution of cardinality at most k. We also propose a parameterized approximation scheme with running time 2^{𝒪(k² log(k/ε))} n^{𝒪(1)} that finds a solution with cardinality at most k and total weight at least (1-ε)opt_k for the special case of axis-parallel segments.
Cite as

Jana Cslovjecsek, Michał Pilipczuk, and Karol Węgrzycki. Parameterized Approximation for Maximum Weight Independent Set of Rectangles and Segments. In 32nd Annual European Symposium on Algorithms (ESA 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 308, pp. 43:1-43:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{cslovjecsek_et_al:LIPIcs.ESA.2024.43,
  author =	{Cslovjecsek, Jana and Pilipczuk, Micha{\l} and W\k{e}grzycki, Karol},
  title =	{{Parameterized Approximation for Maximum Weight Independent Set of Rectangles and Segments}},
  booktitle =	{32nd Annual European Symposium on Algorithms (ESA 2024)},
  pages =	{43:1--43:18},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-338-6},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{308},
  editor =	{Chan, Timothy and Fischer, Johannes and Iacono, John and Herman, Grzegorz},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ESA.2024.43},
  URN =		{urn:nbn:de:0030-drops-211146},
  doi =		{10.4230/LIPIcs.ESA.2024.43},
  annote =	{Keywords: parameterized approximation, Maximum Weight Independent Set, rectangles, segments}
}
Document
DOI: 10.4230/LIPIcs.ESA.2021.33
Efficient Sequential and Parallel Algorithms for Multistage Stochastic Integer Programming Using Proximity

Authors: Jana Cslovjecsek, Friedrich Eisenbrand, Michał Pilipczuk, Moritz Venzin, and Robert Weismantel

Published in: LIPIcs, Volume 204, 29th Annual European Symposium on Algorithms (ESA 2021)

Abstract
We consider the problem of solving integer programs of the form min {c^⊺ x : Ax = b, x ∈ ℤ_{⩾ 0}}, where A is a multistage stochastic matrix in the following sense: the primal treedepth of A is bounded by a parameter d, which means that the columns of A can be organized into a rooted forest of depth at most d so that columns not bound by the ancestor/descendant relation do not have non-zero entries in the same row. We give an algorithm that solves this problem in fixed-parameter time f(d,‖A‖_{∞})⋅ nlog^{𝒪(2^d)} n, where f is a computable function and n is the number of rows of A. The algorithm works in the strong model, where the running time only measures unit arithmetic operations on the input numbers and does not depend on their bitlength. This is the first fpt algorithm for multistage stochastic integer programming to achieve almost linear running time in the strong sense. For two-stage stochastic integer programs, our algorithm works in time 2^{((r+s)‖A‖_∞)^{𝒪(r(r+s))}}⋅ nlog^{𝒪(rs)} n, which improves over previous methods both in terms of the polynomial factor and in terms of the dependence on r and s. In fact, for r = 1 the dependence on s is asymptotically almost tight assuming the Exponential Time Hypothesis. Our algorithm can be also parallelized: we give an implementation in the PRAM model that achieves running time f(d,‖A‖_{∞})⋅ log^{𝒪(2^d)} n using n processors. The main conceptual ingredient in our algorithms is a new proximity result for multistage stochastic integer programs. We prove that if we consider an integer program P, say with a constraint matrix A, then for every optimum solution to the linear relaxation of P there exists an optimum (integral) solution to P that lies, in the 𝓁_{∞}-norm, within distance bounded by a function of ‖A‖_{∞} and the primal treedepth of A. On the way to achieve this result, we prove a generalization and considerable improvement of a structural result of Klein for multistage stochastic integer programs. Once the proximity results are established, this allows us to apply a treedepth-based branching strategy guided by an optimum solution to the linear relaxation.
Cite as

Jana Cslovjecsek, Friedrich Eisenbrand, Michał Pilipczuk, Moritz Venzin, and Robert Weismantel. Efficient Sequential and Parallel Algorithms for Multistage Stochastic Integer Programming Using Proximity. In 29th Annual European Symposium on Algorithms (ESA 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 204, pp. 33:1-33:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)

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@InProceedings{cslovjecsek_et_al:LIPIcs.ESA.2021.33,
  author =	{Cslovjecsek, Jana and Eisenbrand, Friedrich and Pilipczuk, Micha{\l} and Venzin, Moritz and Weismantel, Robert},
  title =	{{Efficient Sequential and Parallel Algorithms for Multistage Stochastic Integer Programming Using Proximity}},
  booktitle =	{29th Annual European Symposium on Algorithms (ESA 2021)},
  pages =	{33:1--33:14},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-204-4},
  ISSN =	{1868-8969},
  year =	{2021},
  volume =	{204},
  editor =	{Mutzel, Petra and Pagh, Rasmus and Herman, Grzegorz},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ESA.2021.33},
  URN =		{urn:nbn:de:0030-drops-146146},
  doi =		{10.4230/LIPIcs.ESA.2021.33},
  annote =	{Keywords: parameterized algorithm, multistage stochastic programming, proximity}
}
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