arXiv subjects

Łukasz Kowalik

Publications and source records attributed to Łukasz Kowalik.

At least 19 recordsLinked to original sources

arXiv2026

The planar edge-coloring theorem of Vizing in $O(n\log n)$ time

In 1965, Vizing [Diskret. Analiz, 1965] showed that every planar graph of maximum degree $Δ\ge 8$ can be edge-colored using $Δ$ colors. The direct implementation of the Vizing's proof gives an algorithm that finds the coloring in $O(n^2)$ time for an $n$-vertex input graph. Chrobak and Nishizeki [J. Algorithms, 1990] have shown a more careful algorithm, which improves the time to $O(n\log n)$ time, though only for $Δ\ge 9$. In this paper, we extend their ideas to get an algorithm also for the missing case $Δ=8$. To this end, we modify the original recoloring procedure of Vizing. This generalizes to bounded genus graphs.

cs.DS↗

arXiv2023

Detecting Points in Integer Cones of Polytopes is Double-Exponentially Hard

Let $d$ be a positive integer. For a finite set $X \subseteq \mathbb{R}^d$, we define its integer cone as the set $\mathsf{IntCone}(X) := \{ \sum_{x \in X} λ_x \cdot x \mid λ_x \in \mathbb{Z}_{\geq 0} \} \subseteq \mathbb{R}^d$. Goemans and Rothvoss showed that, given two polytopes $\mathcal{P}, \mathcal{Q} \subseteq \mathbb{R}^d$ with $\mathcal{P}$ being bounded, one can decide whether $\mathsf{IntCone}(\mathcal{P} \cap \mathbb{Z}^d)$ intersects $\mathcal{Q}$ in time $\mathsf{enc}(\mathcal{P})^{2^{\mathcal{O}(d)}} \cdot \mathsf{enc}(\mathcal{Q})^{\mathcal{O}(1)}$ [J. ACM 2020], where $\mathsf{enc}(\cdot)$ denotes the number of bits required to encode a polytope through a system of linear inequalities. This result is the cornerstone of their XP algorithm for BIN PACKING parameterized by the number of different item sizes. We complement their result by providing a conditional lower bound. In particular, we prove that, unless the ETH fails, there is no algorithm which, given a bounded polytope $\mathcal{P} \subseteq \mathbb{R}^d$ and a point $q \in \mathbb{Z}^d$, decides whether $q \in \mathsf{IntCone}(\mathcal{P} \cap \mathbb{Z}^d)$ in time $\mathsf{enc}(\mathcal{P}, q)^{2^{o(d)}}$. Note that this does not rule out the existence of a fixed-parameter tractable algorithm for the problem, but shows that dependence of the running time on the parameter $d$ must be at least doubly-exponential.

cs.DS↗

arXiv2023

Partitioning edges of a planar graph into linear forests and a matching

We show that the edges of any planar graph of maximum degree at most $9$ can be partitioned into $4$ linear forests and a matching. Combined with known results, this implies that the edges of any planar graph $G$ of odd maximum degree $Δ\ge 9$ can be partitioned into $\tfrac{Δ-1}{2}$ linear forests and one matching. This strengthens well-known results stating that graphs in this class have chromatic index $Δ$ [Vizing, 1965] and linear arboricity at most $\lceil(Δ+1)/2\rceil$ [Wu, 1999].

math.CO↗

arXiv2020

The Asymmetric Travelling Salesman Problem in Sparse Digraphs

Asymmetric Travelling Salesman Problem (ATSP) and its special case Directed Hamiltonicity are among the most fundamental problems in computer science. The dynamic programming algorithm running in time $O^*(2^n)$ developed almost 60 years ago by Bellman, Held and Karp, is still the state of the art for both of these problems. In this work we focus on sparse digraphs. First, we recall known approaches for Undirected Hamiltonicity and TSP in sparse graphs and we analyse their consequences for Directed Hamiltonicity and ATSP in sparse digraphs, either by adapting the algorithm, or by using reductions. In this way, we get a number of running time upper bounds for a few classes of sparse digraphs, including $O^*(2^{n/3})$ for digraphs with both out- and indegree bounded by 2, and $O^*(3^{n/2})$ for digraphs with outdegree bounded by 3. Our main results are focused on digraphs of bounded average outdegree $d$. The baseline for ATSP here is a simple enumeration of cycle covers which can be done in time bounded by $O^*(μ(d)^n)$ for a function $μ(d)\le(\lceil{d}\rceil!)^{1/{\lceil{d}\rceil}}$. One can also observe that Directed Hamiltonicity can be solved in randomized time $O^*((2-2^{-d})^n)$ and polynomial space, by adapting a recent result of Björklund [ISAAC 2018] stated originally for Undirected Hamiltonicity in sparse bipartite graphs. We present two new deterministic algorithms for ATSP: the first running in time $O(2^{0.441(d-1)n})$ and polynomial space, and the second in exponential space with running time of $O^*(τ(d)^{n/2})$ for a function $τ(d)\le d$.

cs.DS↗

arXiv2020

Many visits TSP revisited

We study the Many Visits TSP problem, where given a number $k(v)$ for each of $n$ cities and pairwise (possibly asymmetric) integer distances, one has to find an optimal tour that visits each city $v$ exactly $k(v)$ times. The currently fastest algorithm is due to Berger, Kozma, Mnich and Vincze [SODA 2019, TALG 2020] and runs in time and space $\mathcal{O}^*(5^n)$. They also show a polynomial space algorithm running in time $\mathcal{O}^*(16^{n+o(n)})$. In this work, we show three main results: (i) A randomized polynomial space algorithm in time $\mathcal{O}^*(2^nD)$, where $D$ is the maximum distance between two cities. By using standard methods, this results in $(1+ε)$-approximation in time $\mathcal{O}^*(2^nε^{-1})$. Improving the constant $2$ in these results would be a major breakthrough, as it would result in improving the $\mathcal{O}^*(2^n)$-time algorithm for Directed Hamiltonian Cycle, which is a 50 years old open problem. (ii) A tight analysis of Berger et al.'s exponential space algorithm, resulting in $\mathcal{O}^*(4^n)$ running time bound. (iii) A new polynomial space algorithm, running in time $\mathcal{O}(7.88^n)$.

cs.DS↗

arXiv2019

Fine-Grained Complexity of k-OPT in Bounded-Degree Graphs for Solving TSP

Local search is a widely-employed strategy for finding good solutions to Traveling Salesman Problem. We analyze the problem of determining whether the weight of a given cycle can be decreased by a popular $k$-opt move. Earlier work has shown that (i) assuming the Exponential Time Hypothesis, there is no algorithm to find an improving $k$-opt move in time $f(k)n^{o(k/\log k)}$ for any function $f$, while (ii) it is possible to improve on the brute-force running time of $O(n^k)$ and save linear factors in the exponent. Modern TSP heuristics show that very good global solutions can already be reached using only the top-$O(1)$ most promising edges incident to each vertex. Motivated by this, we study the problem of finding an improving $k$-move in bounded degree graphs, presenting new algorithms and conditional lower bounds. We show that the aforementioned ETH lower bound also holds for graphs of maximum degree three, but that in bounded-degree graphs the best improving $k$-move can be found in time $O(n^{23k/135+o(k)})$. This improves upon the best-known bounds for general graphs. Due to its practical importance, we devote special attention to the range of $k$ in which improving $k$-moves in bounded-degree graphs can be found in quasi-linear time. For $k\le 7$, we give quasi-linear time algorithms for general weights. For $k=8$ we obtain a quasi-linear time algorithm for polylogarithmic weights. On the other hand, based on established fine-grained complexity hypotheses, we prove that the $k=9$ case does not admit quasi-linear time algorithms. Hence we fully characterize the values of $k$ for which quasi-linear time algorithms exist for polylogarithmic weights on bounded-degree graphs. As a byproduct, we show a new bound on pathwidth of even graphs which results in improved running time bounds for counting $k$-vertex paths and cycles.

cs.DS↗

arXiv2018

Tight Lower Bounds for List Edge Coloring

The fastest algorithms for edge coloring run in time $2^m n^{O(1)}$, where $m$ and $n$ are the number of edges and vertices of the input graph, respectively. For dense graphs, this bound becomes $2^{Θ(n^2)}$. This is a somewhat unique situation, since most of the studied graph problems admit algorithms running in time $2^{O(n\log n)}$. It is a notorious open problem to either show an algorithm for edge coloring running in time $2^{o(n^2)}$ or to refute it, assuming Exponential Time Hypothesis (ETH) or other well established assumption. We notice that the same question can be asked for list edge coloring, a well-studied generalization of edge coloring where every edge comes with a set (often called a list) of allowed colors. Our main result states that list edge coloring for simple graphs does not admit an algorithm running in time $2^{o(n^2)}$, unless ETH fails. Interestingly, the algorithm for edge coloring running in time $2^m n^{O(1)}$ generalizes to the list version without any asymptotic slow-down. Thus, our lower bound is essentially tight. This also means that in order to design an algorithm running in time $2^{o(n^2)}$ for edge coloring, one has to exploit its special features compared to the list version.

cs.DS↗

arXiv2017

On Directed Feedback Vertex Set parameterized by treewidth

We study the Directed Feedback Vertex Set problem parameterized by the treewidth of the input graph. We prove that unless the Exponential Time Hypothesis fails, the problem cannot be solved in time $2^{o(t\log t)}\cdot n^{\mathcal{O}(1)}$ on general directed graphs, where $t$ is the treewidth of the underlying undirected graph. This is matched by a dynamic programming algorithm with running time $2^{\mathcal{O}(t\log t)}\cdot n^{\mathcal{O}(1)}$. On the other hand, we show that if the input digraph is planar, then the running time can be improved to $2^{\mathcal{O}(t)}\cdot n^{\mathcal{O}(1)}$.

cs.DS↗

arXiv2017

Tight lower bounds for the complexity of multicoloring

In the multicoloring problem, also known as ($a$:$b$)-coloring or $b$-fold coloring, we are given a graph G and a set of $a$ colors, and the task is to assign a subset of $b$ colors to each vertex of G so that adjacent vertices receive disjoint color subsets. This natural generalization of the classic coloring problem (the $b=1$ case) is equivalent to finding a homomorphism to the Kneser graph $KG_{a,b}$, and gives relaxations approaching the fractional chromatic number. We study the complexity of determining whether a graph has an ($a$:$b$)-coloring. Our main result is that this problem does not admit an algorithm with running time $f(b)\cdot 2^{o(\log b)\cdot n}$, for any computable $f(b)$, unless the Exponential Time Hypothesis (ETH) fails. A $(b+1)^n\cdot \text{poly}(n)$-time algorithm due to Nederlof [2008] shows that this is tight. A direct corollary of our result is that the graph homomorphism problem does not admit a $2^{O(n+h)}$ algorithm unless ETH fails, even if the target graph is required to be a Kneser graph. This refines the understanding given by the recent lower bound of Cygan et al. [SODA 2016]. The crucial ingredient in our hardness reduction is the usage of detecting matrices of Lindström [Canad. Math. Bull., 1965], which is a combinatorial tool that, to the best of our knowledge, has not yet been used for proving complexity lower bounds. As a side result, we prove that the running time of the algorithms of Abasi et al. [MFCS 2014] and of Gabizon et al. [ESA 2015] for the r-monomial detection problem are optimal under ETH.

cs.DS↗

arXiv2016

Approximation and Parameterized Complexity of Minimax Approval Voting

We present three results on the complexity of Minimax Approval Voting. First, we study Minimax Approval Voting parameterized by the Hamming distance $d$ from the solution to the votes. We show Minimax Approval Voting admits no algorithm running in time $\mathcal{O}^\star(2^{o(d\log d)})$, unless the Exponential Time Hypothesis (ETH) fails. This means that the $\mathcal{O}^\star(d^{2d})$ algorithm of Misra et al. [AAMAS 2015] is essentially optimal. Motivated by this, we then show a parameterized approximation scheme, running in time $\mathcal{O}^\star(\left({3}/ε\right)^{2d})$, which is essentially tight assuming ETH. Finally, we get a new polynomial-time randomized approximation scheme for Minimax Approval Voting, which runs in time $n^{\mathcal{O}(1/ε^2 \cdot \log(1/ε))} \cdot \mathrm{poly}(m)$, almost matching the running time of the fastest known PTAS for Closest String due to Ma and Sun [SIAM J. Comp. 2009].

cs.DS↗

arXiv2016

On the fine-grained complexity of rainbow coloring

The Rainbow k-Coloring problem asks whether the edges of a given graph can be colored in $k$ colors so that every pair of vertices is connected by a rainbow path, i.e., a path with all edges of different colors. Our main result states that for any $k\ge 2$, there is no algorithm for Rainbow k-Coloring running in time $2^{o(n^{3/2})}$, unless ETH fails. Motivated by this negative result we consider two parameterized variants of the problem. In Subset Rainbow k-Coloring problem, introduced by Chakraborty et al. [STACS 2009, J. Comb. Opt. 2009], we are additionally given a set $S$ of pairs of vertices and we ask if there is a coloring in which all the pairs in $S$ are connected by rainbow paths. We show that Subset Rainbow k-Coloring is FPT when parameterized by $|S|$. We also study Maximum Rainbow k-Coloring problem, where we are additionally given an integer $q$ and we ask if there is a coloring in which at least $q$ anti-edges are connected by rainbow paths. We show that the problem is FPT when parameterized by $q$ and has a kernel of size $O(q)$ for every $k\ge 2$ (thus proving that the problem is FPT), extending the result of Ananth et al. [FSTTCS 2011].

cs.DS↗

arXiv2015

Linear kernels for outbranching problems in sparse digraphs

In the $k$-Leaf Out-Branching and $k$-Internal Out-Branching problems we are given a directed graph $D$ with a designated root $r$ and a nonnegative integer $k$. The question is to determine the existence of an outbranching rooted at $r$ that has at least $k$ leaves, or at least $k$ internal vertices, respectively. Both these problems were intensively studied from the points of view of parameterized complexity and kernelization, and in particular for both of them kernels with $O(k^2)$ vertices are known on general graphs. In this work we show that $k$-Leaf Out-Branching admits a kernel with $O(k)$ vertices on $\mathcal{H}$-minor-free graphs, for any fixed family of graphs $\mathcal{H}$, whereas $k$-Internal Out-Branching admits a kernel with $O(k)$ vertices on any graph class of bounded expansion.

cs.DS↗

arXiv2015

Counting thin subgraphs via packings faster than meet-in-the-middle time

Vassilevska and Williams (STOC 2009) showed how to count simple paths on $k$ vertices and matchings on $k/2$ edges in an $n$-vertex graph in time $n^{k/2+O(1)}$. In the same year, two different algorithms with the same runtime were given by Koutis and Williams~(ICALP 2009), and Björklund \emph{et al.} (ESA 2009), via $n^{st/2+O(1)}$-time algorithms for counting $t$-tuples of pairwise disjoint sets drawn from a given family of $s$-sized subsets of an $n$-element universe. Shortly afterwards, Alon and Gutner (TALG 2010) showed that these problems have $Ω(n^{\lfloor st/2\rfloor})$ and $Ω(n^{\lfloor k/2\rfloor})$ lower bounds when counting by color coding. Here we show that one can do better, namely, we show that the "meet-in-the-middle" exponent $st/2$ can be beaten and give an algorithm that counts in time $n^{0.45470382 st + O(1)}$ for $t$ a multiple of three. This implies algorithms for counting occurrences of a fixed subgraph on $k$ vertices and pathwidth $p\ll k$ in an $n$-vertex graph in $n^{0.45470382k+2p+O(1)}$ time, improving on the three mentioned algorithms for paths and matchings, and circumventing the color-coding lower bound. We also give improved bounds for counting $t$-tuples of disjoint $s$-sets for $s=2,3,4$. Our algorithms use fast matrix multiplication. We show an argument that this is necessary to go below the meet-in-the-middle barrier.

cs.DS↗

arXiv2015

Fast Witness Extraction Using a Decision Oracle

The gist of many (NP-)hard combinatorial problems is to decide whether a universe of $n$ elements contains a witness consisting of $k$ elements that match some prescribed pattern. For some of these problems there are known advanced algebra-based FPT algorithms which solve the decision problem but do not return the witness. We investigate techniques for turning such a YES/NO-decision oracle into an algorithm for extracting a single witness, with an objective to obtain practical scalability for large values of $n$. By relying on techniques from combinatorial group testing, we demonstrate that a witness may be extracted with $O(k\log n)$ queries to either a deterministic or a randomized set inclusion oracle with one-sided probability of error. Furthermore, we demonstrate through implementation and experiments that the algebra-based FPT algorithms are practical, in particular in the setting of the $k$-path problem. Also discussed are engineering issues such as optimizing finite field arithmetic.

cs.DS↗

arXiv2015

Spotting Trees with Few Leaves

We show two results related to the Hamiltonicity and $k$-Path algorithms in undirected graphs by Björklund [FOCS'10], and Björklund et al., [arXiv'10]. First, we demonstrate that the technique used can be generalized to finding some $k$-vertex tree with $l$ leaves in an $n$-vertex undirected graph in $O^*(1.657^k2^{l/2})$ time. It can be applied as a subroutine to solve the $k$-Internal Spanning Tree ($k$-IST) problem in $O^*(\min(3.455^k, 1.946^n))$ time using polynomial space, improving upon previous algorithms for this problem. In particular, for the first time we break the natural barrier of $O^*(2^n)$. Second, we show that the iterated random bipartition employed by the algorithm can be improved whenever the host graph admits a vertex coloring with few colors; it can be an ordinary proper vertex coloring, a fractional vertex coloring, or a vector coloring. In effect, we show improved bounds for $k$-Path and Hamiltonicity in any graph of maximum degree $Δ=4,\ldots,12$ or with vector chromatic number at most 8.

cs.DS↗

arXiv2014

Assigning channels via the meet-in-the-middle approach

We study the complexity of the Channel Assignment problem. By applying the meet-in-the-middle approach we get an algorithm for the $\ell$-bounded Channel Assignment (when the edge weights are bounded by $\ell$) running in time $O^*((2\sqrt{\ell+1})^n)$. This is the first algorithm which breaks the $(O(\ell))^n$ barrier. We extend this algorithm to the counting variant, at the cost of slightly higher polynomial factor. A major open problem asks whether Channel Assignment admits a $O(c^n)$-time algorithm, for a constant $c$ independent of $\ell$. We consider a similar question for Generalized T-Coloring, a CSP problem that generalizes \CA. We show that Generalized T-Coloring does not admit a $2^{2^{o\left(\sqrt{n}\right)}} {\rm poly}(r)$-time algorithm, where $r$ is the size of the instance.

cs.DS↗

arXiv2014

Beyond the Vizing's bound for at most seven colors

Let $G=(V,E)$ be a simple graph of maximum degree $Δ$. The edges of $G$ can be colored with at most $Δ+1$ colors by Vizing's theorem. We study lower bounds on the size of subgraphs of $G$ that can be colored with $Δ$ colors. Vizing's Theorem gives a bound of $\fracΔ{Δ+1}|E|$. This is known to be tight for cliques $K_{Δ+1}$ when $Δ$ is even. However, for $Δ=3$ it was improved to $26/31|E|$ by Albertson and Haas [Parsimonious edge colorings, Disc. Math. 148, 1996] and later to $6/7|E|$ by Rizzi [Approximating the maximum 3-edge-colorable subgraph problem, Disc. Math. 309, 2009]. It is tight for $B_3$, the graph isomorphic to a $K_4$ with one edge subdivided. We improve previously known bounds for $Δ\in{3,...,7}$, under the assumption that for $Δ=3,4,6$ graph $G$ is not isomorphic to $B_3$, $K_5$ and $K_7$, respectively. For $Δ\geq 4$ these are the first results which improve over the Vizing's bound. We also show a new bound for subcubic multigraphs not isomorphic to $K_3$ with one edge doubled. In the second part, we give approximation algorithms for the Maximum k-Edge-Colorable Subgraph problem, where given a graph G (without any bound on its maximum degree or other restrictions) one has to find a k-edge-colorable subgraph with maximum number of edges. In particular, when G is simple for k=3,4,5,6,7 we obtain approximation ratios of 13/15, 9/11, 19/22, 23/27 and 22/25, respectively. We also present a 7/9-approximation for k=3 when G is a multigraph. The approximation algorithms follow from a new general framework that can be used for any value of k.

cs.DS↗

arXiv2013

Beyond the Shannon's Bound

Let $G=(V,E)$ be a multigraph of maximum degree $Δ$. The edges of $G$ can be colored with at most $\frac{3}{2}Δ$ colors by Shannon's theorem. We study lower bounds on the size of subgraphs of $G$ that can be colored with $Δ$ colors. Shannon's Theorem gives a bound of $\fracΔ{\lfloor\frac{3}{2}Δ\rfloor}|E|$. However, for $Δ=3$, Kamiński and Kowalik [SWAT'10] showed that there is a 3-edge-colorable subgraph of size at least $\frac{7}{9}|E|$, unless $G$ has a connected component isomorphic to $K_3+e$ (a $K_3$ with an arbitrary edge doubled). Here we extend this line of research by showing that $G$ has a $Δ$-edge colorable subgraph with at least $\fracΔ{\lfloor\frac{3}{2}Δ\rfloor-1}|E|$ edges, unless $Δ$ is even and $G$ contains $\fracΔ{2}K_3$ or $Δ$ is odd and $G$ contains $\frac{Δ-1}{2}K_3+e$. Moreover, the subgraph and its coloring can be found in polynomial time. Our results have applications in approximation algorithms for the Maximum $k$-Edge-Colorable Subgraph problem, where given a graph $G$ (without any bound on its maximum degree or other restrictions) one has to find a $k$-edge-colorable subgraph with maximum number of edges. In particular, for every even $k \ge 4$ we obtain a $\frac{2k+2}{3k+2}$-approximation and for every odd $k\ge 5$ we get a $\frac{2k+1}{3k}$-approximation. When $4\le k \le 13$ this improves over earlier algorithms due to Feige et al. [APPROX'02]

cs.DS↗