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Karol Węgrzycki

Publications and source records attributed to Karol Węgrzycki.

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arXiv2024

Polynomial Time Algorithms for Integer Programming and Unbounded Subset Sum in the Total Regime

The Unbounded Subset Sum (USS) problem is an NP-hard computational problem where the goal is to decide whether there exist non-negative integers $x_1, \ldots, x_n$ such that $x_1 a_1 + \ldots + x_n a_n = b$, where $a_1 < \cdots < a_n < b$ are distinct positive integers with $\text{gcd}(a_1, \ldots, a_n)$ dividing $b$. The problem can be solved in pseudopolynomial time, while specialized cases, such as when $b$ exceeds the Frobenius number of $a_1, \ldots, a_n$ simplify to a total problem where a solution always exists. This paper explores the concept of totality in USS. The challenge in this setting is to actually find a solution, even though we know its existence is guaranteed. We focus on the instances of USS where solutions are guaranteed for large $b$. We show that when $b$ is slightly greater than the Frobenius number, we can find the solution to USS in polynomial time. We then show how our results extend to Integer Programming with Equalities (ILPE), highlighting conditions under which ILPE becomes total. We investigate the diagonal Frobenius number, which is the appropriate generalization of the Frobenius number to this context. In this setting, we give a polynomial-time algorithm to find a solution of ILPE. The bound obtained from our algorithmic procedure for finding a solution almost matches the recent existential bound of Bach, Eisenbrand, Rothvoss, and Weismantel (2024).

cs.DS↗
arXiv2024

Hitting Meets Packing: How Hard Can it Be?

We study a general family of problems that form a common generalization of classic hitting (also referred to as covering or transversal) and packing problems. An instance of X-HitPack asks: Can removing k (deletable) vertices of a graph G prevent us from packing $\ell$ vertex-disjoint objects of type X? This problem captures a spectrum of problems with standard hitting and packing on opposite ends. Our main motivating question is whether the combination X-HitPack can be significantly harder than these two base problems. Already for a particular choice of X, this question can be posed for many different complexity notions, leading to a large, so-far unexplored domain in the intersection of the areas of hitting and packing problems. On a high-level, we present two case studies: (1) X being all cycles, and (2) X being all copies of a fixed graph H. In each, we explore the classical complexity, as well as the parameterized complexity with the natural parameters k+l and treewidth. We observe that the combined problem can be drastically harder than the base problems: for cycles or for H being a connected graph with at least 3 vertices, the problem is Σ_2^P-complete and requires double-exponential dependence on the treewidth of the graph (assuming the Exponential-Time Hypothesis). In contrast, the combined problem admits qualitatively similar running times as the base problems in some cases, although significant novel ideas are required. For example, for X being all cycles, we establish a 2^poly(k+l)n^O(1) algorithm using an involved branching method. Also, for X being all edges (i.e., H = K_2; this combines Vertex Cover and Maximum Matching) the problem can be solved in time 2^\poly(tw)n^O(1) on graphs of treewidth tw. The key step enabling this running time relies on a combinatorial bound obtained from an algebraic (linear delta-matroid) representation of possible matchings.

cs.DS↗
arXiv2023

A Subexponential Time Algorithm for Makespan Scheduling of Unit Jobs with Precedence Constraints

In a classical scheduling problem, we are given a set of $n$ jobs of unit length along with precedence constraints, and the goal is to find a schedule of these jobs on $m$ identical machines that minimizes the makespan. Using the standard 3-field notation, it is known as $Pm|\text{prec}, p_j=1|C_{\max}$. Settling the complexity of $Pm|\text{prec}, p_j=1|C_{\max}$ even for $m=3$ machines is the last open problem from the book of Garey and Johnson [GJ79] for which both upper and lower bounds on the worst-case running times of exact algorithms solving them remain essentially unchanged since the publication of [GJ79]. We present an algorithm for this problem that runs in $(1+\frac{n}{m})^{\mathcal{O}(\sqrt{nm})}$ time. This algorithm is subexponential when $m = o(n)$. In the regime of $m=Θ(n)$ we show an algorithm that runs in$\mathcal{O}(1.997^n)$ time. Before our work, even for $m=3$ machines there were no algorithms known that run in $\mathcal{O}((2-\varepsilon)^n)$ time for some $\varepsilon > 0$.

cs.DS↗
arXiv2023

A polynomial-time $\text{OPT}^ε$-approximation algorithm for maximum independent set of connected subgraphs in a planar graph

In the Maximum Independent Set of Objects problem, we are given an $n$-vertex planar graph $G$ and a family $\mathcal{D}$ of $N$ objects, where each object is a connected subgraph of $G$. The task is to find a subfamily $\mathcal{F} \subseteq \mathcal{D}$ of maximum cardinality that consists of pairwise disjoint objects. This problem is $\mathsf{NP}$-hard and is equivalent to the problem of finding the maximum number of pairwise disjoint polygons in a given family of polygons in the plane. As shown by Adamaszek et al. (J. ACM '19), the problem admits a \emph{quasi-polynomial time approximation scheme} (QPTAS): a $(1-\varepsilon)$-approximation algorithm whose running time is bounded by $2^{\mathrm{poly}(\log(N),1/ε)} \cdot n^{\mathcal{O}(1)}$. Nevertheless, to the best of our knowledge, in the polynomial-time regime only the trivial $\mathcal{O}(N)$-approximation is known for the problem in full generality. In the restricted setting where the objects are pseudolines in the plane, Fox and Pach (SODA '11) gave an $N^{\varepsilon}$-approximation algorithm with running time $N^{2^{\tilde{\mathcal{O}}(1/\varepsilon)}}$, for any $\varepsilon>0$. In this work, we present an $\text{OPT}^{\varepsilon}$-approximation algorithm for the problem that runs in time $N^{\tilde{\mathcal{O}}(1/\varepsilon^2)} n^{\mathcal{O}(1)}$, for any $\varepsilon>0$, thus improving upon the result of Fox and Pach both in terms of generality and in terms of the running time. Our approach combines the methodology of Voronoi separators, introduced by Marx and Pilipczuk (TALG '22), with a new analysis of the approximation factor.

cs.CG↗
arXiv2023

Separator Theorem and Algorithms for Planar Hyperbolic Graphs

The hyperbolicity of a graph, informally, measures how close a graph is (metrically) to a tree. Hence, it is intuitively similar to treewidth, but the measures are formally incomparable. Motivated by the broad study of algorithms and separators on planar graphs and their relation to treewidth, we initiate the study of planar graphs of bounded hyperbolicity. Our main technical contribution is a novel balanced separator theorem for planar $δ$-hyperbolic graphs that is substantially stronger than the classic planar separator theorem. For any fixed $δ\geq 0$, we can find balanced separator that induces either a single geodesic (shortest) path or a single geodesic cycle in the graph. An important advantage of our separator is that the union of our separator (vertex set $Z$) with any subset of the connected components of $G - Z$ induces again a planar $δ$-hyperbolic graph, which would not be guaranteed with an arbitrary separator. Our construction runs in near-linear time and guarantees that size of separator is $\mathrm{poly}(δ) \cdot \log n$. As an application of our separator theorem and its strong properties, we obtain two novel approximation schemes on planar $δ$-hyperbolic graphs. We prove that Maximum Independent Set and the Traveling Salesperson problem have a near-linear time FPTAS for any constant $δ$, running in $n\, \mathrm{polylog}(n) \cdot 2^{\mathcal{O}(δ^2)} \cdot \varepsilon^{-\mathcal{O}(δ)}$ time. We also show that our approximation scheme for Maximum Independent Set has essentially the best possible running time under the Exponential Time Hypothesis (ETH). This immediately follows from our third contribution: we prove that Maximum Independent Set has no $n^{o(δ)}$-time algorithm on planar $δ$-hyperbolic graphs, unless ETH fails.

cs.DS↗
arXiv2023

A Faster Exponential Time Algorithm for Bin Packing With a Constant Number of Bins via Additive Combinatorics

In the Bin Packing problem one is given $n$ items with weights $w_1,\ldots,w_n$ and $m$ bins with capacities $c_1,\ldots,c_m$. The goal is to find a partition of the items into sets $S_1,\ldots,S_m$ such that $w(S_j) \leq c_j$ for every bin $j$, where $w(X)$ denotes $\sum_{i \in X}w_i$. Björklund, Husfeldt and Koivisto (SICOMP 2009) presented an $\mathcal{O}^\star(2^n)$ time algorithm for Bin Packing. In this paper, we show that for every $m \in \mathbf{N}$ there exists a constant $σ_m >0$ such that an instance of Bin Packing with $m$ bins can be solved in $\mathcal{O}(2^{(1-σ_m)n})$ randomized time. Before our work, such improved algorithms were not known even for $m$ equals $4$. A key step in our approach is the following new result in Littlewood-Offord theory on the additive combinatorics of subset sums: For every $δ>0$ there exists an $\varepsilon >0$ such that if $|\{ X\subseteq \{1,\ldots,n \} : w(X)=v \}| \geq 2^{(1-\varepsilon)n}$ for some $v$ then $|\{ w(X): X \subseteq \{1,\ldots,n\} \}|\leq 2^{δn}$.

cs.DS↗
arXiv2023

Coverability in VASS Revisited: Improving Rackoff's Bound to Obtain Conditional Optimality

Seminal results establish that the coverability problem for Vector Addition Systems with States (VASS) is in EXPSPACE (Rackoff, '78) and is EXPSPACE-hard already under unary encodings (Lipton, '76). More precisely, Rosier and Yen later utilise Rackoff's bounding technique to show that if coverability holds then there is a run of length at most $n^{2^{\mathcal{O}(d \log d)}}$, where $d$ is the dimension and $n$ is the size of the given unary VASS. Earlier, Lipton showed that there exist instances of coverability in $d$-dimensional unary VASS that are only witnessed by runs of length at least $n^{2^{Ω(d)}}$. Our first result closes this gap. We improve the upper bound by removing the twice-exponentiated $\log(d)$ factor, thus matching Lipton's lower bound. This closes the corresponding gap for the exact space required to decide coverability. This also yields a deterministic $n^{2^{\mathcal{O}(d)}}$-time algorithm for coverability. Our second result is a matching lower bound, that there does not exist a deterministic $n^{2^{o(d)}}$-time algorithm, conditioned upon the Exponential Time Hypothesis. When analysing coverability, a standard proof technique is to consider VASS with bounded counters. Bounded VASS make for an interesting and popular model due to strong connections with timed automata. Withal, we study a natural setting where the counter bound is linear in the size of the VASS. Here the trivial exhaustive search algorithm runs in $\mathcal{O}(n^{d+1})$-time. We give evidence to this being near-optimal. We prove that in dimension one this trivial algorithm is conditionally optimal, by showing that $n^{2-o(1)}$-time is required under the $k$-cycle hypothesis. In general fixed dimension $d$, we show that $n^{d-2-o(1)}$-time is required under the 3-uniform hyperclique hypothesis.

cs.FL↗
arXiv2023

Improved Distance Queries and Cycle Counting by Frobenius Normal Form

Consider an unweighted, directed graph $G$ with the diameter $D$. In this paper, we introduce the framework for counting cycles and walks of given length in matrix multiplication time $\widetilde{O}(n^ω)$. The framework is based on the fast decomposition into Frobenius normal form and the Hankel matrix-vector multiplication. It allows us to solve the All-Nodes Shortest Cycles, All-Pairs All Walks problems efficiently and also give some improvement upon distance queries in unweighted graphs.

cs.DS↗
arXiv2023

Coverability in 2-VASS with One Unary Counter is in NP

Coverability in Petri nets finds applications in verification of safety properties of reactive systems. We study coverability in the equivalent model: Vector Addition Systems with States (VASS). A k-VASS can be seen as k counters and a finite automaton whose transitions are labelled with k integers. Counter values are updated by adding the respective transition labels. A configuration in this system consists of a state and k counter values. Importantly, the counters are never allowed to take negative values. The coverability problem asks whether one can traverse the k-VASS from the initial configuration to a configuration with at least the counter values of the target. In a well-established line of work on k-VASS, coverability in 2-VASS is already PSPACE-hard when the integer updates are encoded in binary. This lower bound limits the practicality of applications, so it is natural to focus on restrictions. In this paper we initiate the study of 2-VASS with one unary counter. Here, one counter receives binary encoded updates and the other receives unary encoded updates. Our main result is that coverability in 2-VASS with one unary counter is in NP. This improves upon the inherited state-of-the-art PSPACE upper bound. Our main technical contribution is that one only needs to consider runs in a certain compressed linear form.

cs.FL↗
arXiv2023

Computing Generalized Convolutions Faster Than Brute Force

In this paper, we consider a general notion of convolution. Let $D$ be a finite domain and let $D^n$ be the set of $n$-length vectors (tuples) of $D$. Let $f : D \times D \to D$ be a function and let $\oplus_f$ be a coordinate-wise application of $f$. The $f$-Convolution of two functions $g,h : D^n \to \{-M,\ldots,M\}$ is $$(g \otimes_f h)(\textbf{v}) := \sum_{\substack{\textbf{v}_g,\textbf{v}_h \in D^n\\ \text{s.t. } \textbf{v}_g \oplus_f \textbf{v}_h}} g(\textbf{v}_g) \cdot h(\textbf{v}_h)$$ for every $\textbf{v} \in D^n$. This problem generalizes many fundamental convolutions such as Subset Convolution, XOR Product, Covering Product or Packing Product, etc. For arbitrary function $f$ and domain $D$ we can compute $f$-Convolution via brute-force enumeration in $\widetilde{O}(|D|^{2n}\mathrm{polylog}(M))$ time. Our main result is an improvement over this naive algorithm. We show that $f$-Convolution can be computed exactly in $\widetilde{O}((c \cdot |D|^2)^{n}\mathrm{polylog}(M))$ for constant $c := 3/4$ when $D$ has even cardinality. Our main observation is that a \emph{cyclic partition} of a function $f : D \times D \to D$ can be used to speed up the computation of $f$-Convolution, and we show that an appropriate cyclic partition exists for every $f$. Furthermore, we demonstrate that a single entry of the $f$-Convolution can be computed more efficiently. In this variant, we are given two functions $g,h : D^n \to \{-M,\ldots,M\}$ alongside with a vector $\textbf{v} \in D^n$ and the task of the $f$-Query problem is to compute integer $(g \otimes_f h)(\textbf{v})$. This is a generalization of the well-known Orthogonal Vectors problem. We show that $f$-Query can be computed in $\widetilde{O}(|D|^{\fracω{2} n}\mathrm{polylog}(M))$ time, where $ω\in [2,2.372)$ is the exponent of currently fastest matrix multiplication algorithm.

cs.DS↗
arXiv2022

Parameterized Approximation for Maximum Weight Independent Set of Rectangles and Segments

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 by 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 et al. (ESA 2019) gave a $(1-ε)$-approximation algorithm with running time $k^{O(k/ε^8)} n^{O(1/ε^8)}$ 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. Our contribution is a partial answer to the open question of Grandoni et al. (ESA 2019). We give a parameterized approximation algorithm for MWISR that given a parameter $k$, finds a set of non-overlapping rectangles of weight at least $(1-ε) \text{opt}_k$ in $2^{O(k \log(k/ε))} n^{O(1/ε)}$ time, where $\text{opt}_k$ is the maximum weight of a solution of cardinality at most $k$. Note that thus, our algorithm may return a solution consisting of more than $k$ rectangles. To complement this apparent weakness, we also propose a parameterized approximation scheme with running time $2^{O(k^2 \log(k/ε))} n^{O(1)}$ that finds a solution with cardinality at most $k$ and total weight at least $(1-ε)\text{opt}_k$ for the special case of axis-parallel segments.

cs.DS↗
arXiv2022

Gap-ETH-Tight Approximation Schemes for Red-Green-Blue Separation and Bicolored Noncrossing Euclidean Travelling Salesman Tours

In this paper, we study problems of connecting classes of points via noncrossing structures. Given a set of colored terminal points, we want to find a graph for each color that connects all terminals of its color with the restriction that no two graphs cross each other. We consider these problems both on the Euclidean plane and in planar graphs. On the algorithmic side, we give a Gap-ETH-tight EPTAS for the two-colored traveling salesman problem as well as for the red-blue-green separation problem (in which we want to separate terminals of three colors with two noncrossing polygons of minimum length), both on the Euclidean plane. This improves the work of Arora and Chang (ICALP 2003) who gave a slower PTAS for the simpler red-blue separation problem. For the case of unweighted plane graphs, we also show a PTAS for the two-colored traveling salesman problem. All these results are based on our new patching procedure that might be of independent interest. On the negative side, we show that the problem of connecting terminal pairs with noncrossing paths is NP-hard on the Euclidean plane, and that the problem of finding two noncrossing spanning trees is NP-hard in plane graphs.

cs.DS↗
arXiv2022

Makespan Scheduling of Unit Jobs with Precedence Constraints in $O(1.995^n)$ time

In a classical scheduling problem, we are given a set of $n$ jobs of unit length along with precedence constraints and the goal is to find a schedule of these jobs on $m$ identical machines that minimizes the makespan. This problem is well-known to be NP-hard for an unbounded number of machines. Using standard 3-field notation, it is known as $P|\text{prec}, p_j=1|C_{\max}$. We present an algorithm for this problem that runs in $O(1.995^n)$ time. Before our work, even for $m=3$ machines the best known algorithms ran in $O^\ast(2^n)$ time. In contrast, our algorithm works when the number of machines $m$ is unbounded. A crucial ingredient of our approach is an algorithm with a runtime that is only single-exponential in the vertex cover of the comparability graph of the precedence constraint graph. This heavily relies on insights from a classical result by Dolev and Warmuth (Journal of Algorithms 1984) for precedence graphs without long chains.

cs.DS↗
arXiv2022

Independence number of intersection graphs of axis-parallel segments

We prove that for any triangle-free intersection graph of $n$ axis-parallel segments in the plane, the independence number $α$ of this graph is at least $α\ge n/4 + Ω(\sqrt{n})$. We complement this with a construction of a graph in this class satisfying $α\le n/4 + c \sqrt{n}$ for an absolute constant $c$, which demonstrates the optimality of our result.

math.CO↗
arXiv2022

Dynamic data structures for parameterized string problems

We revisit classic string problems considered in the area of parameterized complexity, and study them through the lens of dynamic data structures. That is, instead of asking for a static algorithm that solves the given instance efficiently, our goal is to design a data structure that efficiently maintains a solution, or reports a lack thereof, upon updates in the instance. We first consider the Closest String problem, for which we design randomized dynamic data structures with amortized update times $d^{\mathcal{O}(d)}$ and $|Σ|^{\mathcal{O}(d)}$, respectively, where $Σ$ is the alphabet and $d$ is the assumed bound on the maximum distance. These are obtained by combining known static approaches to Closest String with color-coding. Next, we note that from a result of Frandsen et al.~[J. ACM'97] one can easily infer a meta-theorem that provides dynamic data structures for parameterized string problems with worst-case update time of the form $\mathcal{O}(\log \log n)$, where $k$ is the parameter in question and $n$ is the length of the string. We showcase the utility of this meta-theorem by giving such data structures for problems Disjoint Factors and Edit Distance. We also give explicit data structures for these problems, with worst-case update times $\mathcal{O}(k2^{k}\log \log n)$ and $\mathcal{O}(k^2\log \log n)$, respectively. Finally, we discuss how a lower bound methodology introduced by Amarilli et al.~[ICALP'21] can be used to show that obtaining update time $\mathcal{O}(f(k))$ for Disjoint Factors and Edit Distance is unlikely already for a constant value of the parameter $k$.

cs.DS↗
arXiv2022

Bounding generalized coloring numbers of planar graphs using coin models

We study Koebe orderings of planar graphs: vertex orderings obtained by modelling the graph as the intersection graph of pairwise internally-disjoint discs in the plane, and ordering the vertices by non-increasing radii of the associated discs. We prove that for every $d\in \mathbb{N}$, any such ordering has $d$-admissibility bounded by $O(d/\ln d)$ and weak $d$-coloring number bounded by $O(d^4 \ln d)$. This in particular shows that the $d$-admissibility of planar graphs is bounded by $O(d/\ln d)$, which asymptotically matches a known lower bound due to Dvořák and Siebertz.

math.CO↗
arXiv2021

Knapsack and Subset Sum with Small Items

Knapsack and Subset Sum are fundamental NP-hard problems in combinatorial optimization. Recently there has been a growing interest in understanding the best possible pseudopolynomial running times for these problems with respect to various parameters. In this paper we focus on the maximum item size $s$ and the maximum item value $v$. We give algorithms that run in time $O(n + s^3)$ and $O(n + v^3)$ for the Knapsack problem, and in time $\tilde{O}(n + s^{5/3})$ for the Subset Sum problem. Our algorithms work for the more general problem variants with multiplicities, where each input item comes with a (binary encoded) multiplicity, which succinctly describes how many times the item appears in the instance. In these variants $n$ denotes the (possibly much smaller) number of distinct items. Our results follow from combining and optimizing several diverse lines of research, notably proximity arguments for integer programming due to Eisenbrand and Weismantel (TALG 2019), fast structured $(\min,+)$-convolution by Kellerer and Pferschy (J. Comb. Optim. 2004), and additive combinatorics methods originating from Galil and Margalit (SICOMP 1991).

cs.DS↗
arXiv2021

Isolation schemes for problems on decomposable graphs

The Isolation Lemma of Mulmuley, Vazirani and Vazirani [Combinatorica'87] provides a self-reduction scheme that allows one to assume that a given instance of a problem has a unique solution, provided a solution exists at all. Since its introduction, much effort has been dedicated towards derandomization of the Isolation Lemma for specific classes of problems. So far, the focus was mainly on problems solvable in polynomial time. In this paper, we study a setting that is more typical for $\mathsf{NP}$-complete problems, and obtain partial derandomizations in the form of significantly decreasing the number of required random bits. In particular, motivated by the advances in parameterized algorithms, we focus on problems on decomposable graphs. For example, for the problem of detecting a Hamiltonian cycle, we build upon the rank-based approach from [Bodlaender et al., Inf. Comput.'15] and design isolation schemes that use - $O(t\log n + \log^2{n})$ random bits on graphs of treewidth at most $t$; - $O(\sqrt{n})$ random bits on planar or $H$-minor free graphs; and - $O(n)$-random bits on general graphs. In all these schemes, the weights are bounded exponentially in the number of random bits used. As a corollary, for every fixed $H$ we obtain an algorithm for detecting a Hamiltonian cycle in an $H$-minor-free graph that runs in deterministic time $2^{O(\sqrt{n})}$ and uses polynomial space; this is the first algorithm to achieve such complexity guarantees. For problems of more local nature, such as finding an independent set of maximum size, we obtain isolation schemes on graphs of treedepth at most $d$ that use $O(d)$ random bits and assign polynomially-bounded weights. We also complement our findings with several unconditional and conditional lower bounds, which show that many of the results cannot be significantly improved.

cs.CC↗