arXiv subjects

Marek Cygan

Publications and source records attributed to Marek Cygan.

81 records · Page 5Linked to original sources

arXiv2011

Solving connectivity problems parameterized by treewidth in single exponential time

For the vast majority of local graph problems standard dynamic programming techniques give c^tw V^O(1) algorithms, where tw is the treewidth of the input graph. On the other hand, for problems with a global requirement (usually connectivity) the best-known algorithms were naive dynamic programming schemes running in tw^O(tw) V^O(1) time. We breach this gap by introducing a technique we dubbed Cut&Count that allows to produce c^tw V^O(1) Monte Carlo algorithms for most connectivity-type problems, including Hamiltonian Path, Feedback Vertex Set and Connected Dominating Set, consequently answering the question raised by Lokshtanov, Marx and Saurabh [SODA'11] in a surprising way. We also show that (under reasonable complexity assumptions) the gap cannot be breached for some problems for which Cut&Count does not work, like CYCLE PACKING. The constant c we obtain is in all cases small (at most 4 for undirected problems and at most 6 for directed ones), and in several cases we are able to show that improving those constants would cause the Strong Exponential Time Hypothesis to fail. Our results have numerous consequences in various fields, like FPT algorithms, exact and approximate algorithms on planar and H-minor-free graphs and algorithms on graphs of bounded degree. In all these fields we are able to improve the best-known results for some problems.

cs.DS↗

arXiv2011

Approximation Algorithms for Union and Intersection Covering Problems

In a classical covering problem, we are given a set of requests that we need to satisfy (fully or partially), by buying a subset of items at minimum cost. For example, in the k-MST problem we want to find the cheapest tree spanning at least k nodes of an edge-weighted graph. Here nodes and edges represent requests and items, respectively. In this paper, we initiate the study of a new family of multi-layer covering problems. Each such problem consists of a collection of h distinct instances of a standard covering problem (layers), with the constraint that all layers share the same set of requests. We identify two main subfamilies of these problems: - in a union multi-layer problem, a request is satisfied if it is satisfied in at least one layer; - in an intersection multi-layer problem, a request is satisfied if it is satisfied in all layers. To see some natural applications, consider both generalizations of k-MST. Union k-MST can model a problem where we are asked to connect a set of users to at least one of two communication networks, e.g., a wireless and a wired network. On the other hand, intersection k-MST can formalize the problem of connecting a subset of users to both electricity and water. We present a number of hardness and approximation results for union and intersection versions of several standard optimization problems: MST, Steiner tree, set cover, facility location, TSP, and their partial covering variants.

cs.DS↗

arXiv2010

The stubborn problem is stubborn no more (a polynomial algorithm for 3-compatible colouring and the stubborn list partition problem)

One of the driving problems in the CSP area is the Dichotomy Conjecture, formulated in 1993 by Feder and Vardi [STOC'93], stating that for any fixed relational structure G the Constraint Satisfaction Problem CSP(G) is either NP--complete or polynomial time solvable. A large amount of research has gone into checking various specific cases of this conjecture. One such variant which attracted a lot of attention in the recent years is the LIST MATRIX PARTITION problem. In 2004 Cameron et al. [SODA'04] classified almost all LIST MATRIX PARTITION variants for matrices of size at most four. The only case which resisted the classification became known as the STUBBORN PROBLEM. In this paper we show a result which enables us to finish the classification - thus solving a problem which resisted attacks for the last six years. Our approach is based on a combinatorial problem known to be at least as hard as the STUBBORN PROBLEM - the 3-COMPATIBLE COLOURING problem. In this problem we are given a complete graph with each edge assigned one of 3 possible colours and we want to assign one of those 3 colours to each vertex in such a way that no edge has the same colour as both of its endpoints. The tractability of the 3-COMPATIBLE COLOURING problem has been open for several years and the best known algorithm prior to this paper is due to Feder et al. [SODA'05] - a quasipolynomial algorithm with a n^O(log n / log log n) time complexity. In this paper we present a polynomial-time algorithm for the 3-COMPATIBLE COLOURING problem and consequently we prove a dichotomy for the k-COMPATIBLE COLOURING problem.

cs.DS↗

arXiv2010

Fast Approximation in Subspaces by Doubling Metric Decomposition

In this paper we propose and study a new complexity model for approximation algorithms. The main motivation are practical problems over large data sets that need to be solved many times for different scenarios, e.g., many multicast trees that need to be constructed for different groups of users. In our model we allow a preprocessing phase, when some information of the input graph $G=(V,E)$ is stored in a limited size data structure. Next, the data structure enables processing queries of the form ``solve problem A for an input $S\subseteq V$''. We consider problems like {\sc Steiner Forest}, {\sc Facility Location}, {\sc $k$-Median}, {\sc $k$-Center} and {\sc TSP} in the case when the graph induces a doubling metric. Our main results are data structures of near-linear size that are able to answer queries in time close to linear in $|S|$. This improves over typical worst case reuniting time of approximation algorithms in the classical setting which is $Ω(|E|)$ independently of the query size. In most cases, our approximation guarantees are arbitrarily close to those in the classical setting. Additionally, we present the first fully dynamic algorithm for the Steiner tree problem.

cs.DS↗

arXiv2010

Bandwidth and Distortion Revisited

In this paper we merge recent developments on exact algorithms for finding an ordering of vertices of a given graph that minimizes bandwidth (the BANDWIDTH problem) and for finding an embedding of a given graph into a line that minimizes distortion (the DISTORTION problem). For both problems we develop algorithms that work in O(9.363^n) time and polynomial space. For BANDWIDTH, this improves O^*(10^n) algorithm by Feige and Kilian from 2000, for DISTORTION this is the first polynomial space exact algorithm that works in O(c^n) time we are aware of. As a byproduct, we enhance the O(5^{n+o(n)})-time and O^*(2^n)-space algorithm for DISTORTION by Fomin et al. to an algorithm working in O(4.383^n) time and space.

cs.DS↗

arXiv2009

A Planar Linear Arboricity Conjecture

The linear arboricity la(G) of a graph G is the minimum number of linear forests that partition the edges of G. In 1984, Akiyama et al. stated the Linear Arboricity Conjecture (LAC), that the linear arboricity of any simple graph of maximum degree $Δ$ is either $\lceil \tfracΔ{2} \rceil$ or $\lceil \tfrac{Δ+1}{2} \rceil$. In [J. L. Wu. On the linear arboricity of planar graphs. J. Graph Theory, 31:129-134, 1999] and [J. L. Wu and Y. W. Wu. The linear arboricity of planar graphs of maximum degree seven is four. J. Graph Theory, 58(3):210-220, 2008.] it was proven that LAC holds for all planar graphs. LAC implies that for $Δ$ odd, ${\rm la}(G)=\big \lceil \tfracΔ{2} \big \rceil$. We conjecture that for planar graphs this equality is true also for any even $Δ\ge 6$. In this paper we show that it is true for any even $Δ\ge 10$, leaving open only the cases $Δ=6, 8$. We present also an O(n log n)-time algorithm for partitioning a planar graph into max{la(G),5} linear forests, which is optimal when $Δ\ge 9$.

math.CO↗

arXiv2009

Beyond O*(2^n) in domination-type problems

In this paper we provide algorithms faster than O*(2^n) for several NP-complete domination-type problems. More precisely, we provide: an algorithm for CAPACITATED DOMINATING SET that solves it in O(1.89^n), a branch-and-reduce algorithm solving LARGEST IRREDUNDANT SET in O(1.9657^n) time and a simple iterative-DFS algorithm for SMALLEST INCLUSION-MAXIMAL IRREDUNDANT SET that solves it in O(1.999956^n) time. We also provide an exponential approximation scheme for CAPACITATED DOMINATING SET. All algorithms require polynomial space. Despite the fact that the discussed problems are quite similar to the DOMINATING SET problem, we are not aware of any published algorithms solving these problems faster than the obvious O*(2^n) solution prior to this paper.

cs.DS↗

arXiv2009

Even Faster Exact Bandwidth

We deal with exact algorithms for Bandwidth, a long studied NP-hard problem. For a long time nothing better than the trivial O*(n!) exhaustive search was known. In 2000, Feige an Kilian came up with a O*(10^n)-time algorithm. Recently we presented algorithm that runs in O*(5^n) time and O*(2^n) space.. In this paper we present a major modification to our algorithm which makes it run in O(4.83^n) time with the cost of O*(4^n) space complexity. This modification allowed us to perform Measure & Conquer analysis for the time complexity which was not used for such types of problems before.

cs.CC↗

arXiv2008

Exponential-Time Approximation of Hard Problems

We study optimization problems that are neither approximable in polynomial time (at least with a constant factor) nor fixed parameter tractable, under widely believed complexity assumptions. Specifically, we focus on Maximum Independent Set, Vertex Coloring, Set Cover, and Bandwidth. In recent years, many researchers design exact exponential-time algorithms for these and other hard problems. The goal is getting the time complexity still of order $O(c^n)$, but with the constant $c$ as small as possible. In this work we extend this line of research and we investigate whether the constant $c$ can be made even smaller when one allows constant factor approximation. In fact, we describe a kind of approximation schemes -- trade-offs between approximation factor and the time complexity. We study two natural approaches. The first approach consists of designing a backtracking algorithm with a small search tree. We present one result of that kind: a $(4r-1)$-approximation of Bandwidth in time $O^*(2^{n/r})$, for any positive integer $r$. The second approach uses general transformations from exponential-time exact algorithms to approximations that are faster but still exponential-time. For example, we show that for any reduction rate $r$, one can transform any $O^*(c^n)$-time algorithm for Set Cover into a $(1+\ln r)$-approximation algorithm running in time $O^*(c^{n/r})$. We believe that results of that kind extend the applicability of exact algorithms for NP-hard problems.

cs.DS↗