140 research outputs found
Multidimensional Binary Vector Assignment problem: standard, structural and above guarantee parameterizations
In this article we focus on the parameterized complexity of the
Multidimensional Binary Vector Assignment problem (called \BVA). An input of
this problem is defined by disjoint sets , each
composed of binary vectors of size . An output is a set of disjoint
-tuples of vectors, where each -tuple is obtained by picking one vector
from each set . To each -tuple we associate a dimensional vector by
applying the bit-wise AND operation on the vectors of the tuple. The
objective is to minimize the total number of zeros in these vectors. mBVA
can be seen as a variant of multidimensional matching where hyperedges are
implicitly locally encoded via labels attached to vertices, but was originally
introduced in the context of integrated circuit manufacturing.
We provide for this problem FPT algorithms and negative results (-based
results, [2]-hardness and a kernel lower bound) according to several
parameters: the standard parameter i.e. the total number of zeros), as well
as two parameters above some guaranteed values.Comment: 16 pages, 6 figure
Uniform kernelization complexity of hitting forbidden minors
The F-MINOR-FREE DELETION problem asks, for a fixed set F and an input consisting of a graph G and integer k, whether κ vertices can be removed from G such that the resulting graph does not contain any member of F as a minor. At FOCS 2012, Fomin et al. showed that the special case when F contains at least one planar graph has a kernel of size f (F) · κg(F) for some functions f and g. They left open whether this PLANAR F-MINOR-FREE DELETION problem has kernels whose size is uniformly polynomial, of the form f (F) · κc for some universal constant c. We prove that some PLANAR F-MINOR-FREE DELETION problems do not have uniformly polynomial kernels (unless NP ⊆ coNP/poly), not even when parameterized by the vertex cover number. On the positive side, we consider the problem of determining whether κ vertices can be removed to obtain a graph of treedepth at most η. We prove that this problem admits uniformly polynomial kernels with O(κ6) vertices for every fixed η.</p
Streaming Kernelization
Kernelization is a formalization of preprocessing for combinatorially hard
problems. We modify the standard definition for kernelization, which allows any
polynomial-time algorithm for the preprocessing, by requiring instead that the
preprocessing runs in a streaming setting and uses
bits of memory on instances . We obtain
several results in this new setting, depending on the number of passes over the
input that such a streaming kernelization is allowed to make. Edge Dominating
Set turns out as an interesting example because it has no single-pass
kernelization but two passes over the input suffice to match the bounds of the
best standard kernelization
Efficient FPT algorithms for (strict) compatibility of unrooted phylogenetic trees
In phylogenetics, a central problem is to infer the evolutionary
relationships between a set of species ; these relationships are often
depicted via a phylogenetic tree -- a tree having its leaves univocally labeled
by elements of and without degree-2 nodes -- called the "species tree". One
common approach for reconstructing a species tree consists in first
constructing several phylogenetic trees from primary data (e.g. DNA sequences
originating from some species in ), and then constructing a single
phylogenetic tree maximizing the "concordance" with the input trees. The
so-obtained tree is our estimation of the species tree and, when the input
trees are defined on overlapping -- but not identical -- sets of labels, is
called "supertree". In this paper, we focus on two problems that are central
when combining phylogenetic trees into a supertree: the compatibility and the
strict compatibility problems for unrooted phylogenetic trees. These problems
are strongly related, respectively, to the notions of "containing as a minor"
and "containing as a topological minor" in the graph community. Both problems
are known to be fixed-parameter tractable in the number of input trees , by
using their expressibility in Monadic Second Order Logic and a reduction to
graphs of bounded treewidth. Motivated by the fact that the dependency on
of these algorithms is prohibitively large, we give the first explicit dynamic
programming algorithms for solving these problems, both running in time
, where is the total size of the input.Comment: 18 pages, 1 figur
Upper and Lower Bounds for Weak Backdoor Set Detection
We obtain upper and lower bounds for running times of exponential time
algorithms for the detection of weak backdoor sets of 3CNF formulas,
considering various base classes. These results include (omitting polynomial
factors), (i) a 4.54^k algorithm to detect whether there is a weak backdoor set
of at most k variables into the class of Horn formulas; (ii) a 2.27^k algorithm
to detect whether there is a weak backdoor set of at most k variables into the
class of Krom formulas. These bounds improve an earlier known bound of 6^k. We
also prove a 2^k lower bound for these problems, subject to the Strong
Exponential Time Hypothesis.Comment: A short version will appear in the proceedings of the 16th
International Conference on Theory and Applications of Satisfiability Testin
Slightly Superexponential Parameterized Problems
A central problem in parameterized algorithms is to obtain algorithms with running time f(k) center dot n(O(1)) such that f is as slow growing a function of the parameter k as possible. In particular, a large number of basic parameterized problems admit parameterized algorithms where f (k) is single-exponential, that is, c(k) for some constant c, which makes aiming for such a running time a natural goal for other problems as well. However, there are still plenty of problems where the f(k) appearing in the best-known running time is worse than single-exponential and it remained "slightly superexponential" even after serious attempts to bring it down. A natural question to ask is whether the f (k) appearing in the running time of the best-known algorithms is optimal for any of _ these problems. In this paper, we examine parameterized problems where f(k) is k(O(k)) = 2(O(k log k)) in the best-known running time, and for a number of such problems we show that the dependence on k in the running time cannot be improved to single-exponential. More precisely we prove the following tight lower bounds, for four natural problems, arising from three different domains: (1) In the CLOSEST STRING problem, given strings S-1,..., s(t) over an alphabet Sigma of length L each, and an integer d, the question is whether there exists a string s over E of length L, such that its hamming distance from each of the strings s,, 1 <= i <= t, is at most d. The pattern matching problem CLOSEST STRING is known to be solvable in times 2(O(d log d)) center dot n(O(1)) and 2(O(d log vertical bar Sigma vertical bar)) center dot n(O(1)). We show that there are no 2(O(d log d)) center dot n(O(1)) or 2(O(d log vertical bar Sigma vertical bar)) time algorithms, unless the Exponential Time Hypothesis (ETH) fails. (2) The graph embedding problem DISTORTION, that is, deciding whether a graph G has a metric embedding into the integers with distortion at most d can be solved in time 2(O(d log d)) center dot n(O(1)). We show that there is no 2(O(w log w)) center dot n(O(1)) time algorithm, unless the ETH fails. (3) The DISJOINT PATHS problem can be solved in time 2(O(w log w)) center dot n(O(1)) on graphs of treewidth at most w. We show that there is no 2(O(w log w)) center dot n(O(1)) time algorithm, unless the ETH fails. (4) The CHROMATIC NUMBER problem can be solved in time 2(O(w log w)) center dot n(O(1)) on graphs of treewidth at most w. We show that there is no 2(O(w log w)) center dot n(O(1)) time algorithm, unless the ETH fails. To obtain our results, we first prove the lower bound for variants of basic problems: finding cliques, independent sets, and hitting sets. These artificially constrained variants form a good starting point for proving lower bounds on natural problems without any technical restrictions and could be of independent interest. Several follow-up works have already obtained tight lower bounds by using our framework, and we believe it will prove useful in obtaining even more lower bounds in the future
Relating the Time Complexity of Optimization Problems in Light of the Exponential-Time Hypothesis
Obtaining lower bounds for NP-hard problems has for a long time been an
active area of research. Recent algebraic techniques introduced by Jonsson et
al. (SODA 2013) show that the time complexity of the parameterized SAT()
problem correlates to the lattice of strong partial clones. With this ordering
they isolated a relation such that SAT() can be solved at least as fast
as any other NP-hard SAT() problem. In this paper we extend this method
and show that such languages also exist for the max ones problem
(MaxOnes()) and the Boolean valued constraint satisfaction problem over
finite-valued constraint languages (VCSP()). With the help of these
languages we relate MaxOnes and VCSP to the exponential time hypothesis in
several different ways.Comment: This is an extended version of Relating the Time Complexity of
Optimization Problems in Light of the Exponential-Time Hypothesis, appearing
in Proceedings of the 39th International Symposium on Mathematical
Foundations of Computer Science MFCS 2014 Budapest, August 25-29, 201
Known Algorithms on Graphs of Bounded Treewidth Are Probably Optimal
We obtain a number of lower bounds on the running time of algoritluns solving problems on graphs of bounded treewidth. We prove the results under the Strong Exponential Time Hypothesis of Impagliazzo and Paturi. In particular, assuming that n-variable m-clause SAT cannot be solved in time (2 - epsilon)(n) m(O(1)), we show that for any epsilon > 0: INDEPENDENT SET cannot be solved ill time (2 - epsilon)(tw(G))vertical bar V(G)vertical bar(O(1)), DOMINATING SET cannot be solved in time (3 - epsilon)(tw(G))vertical bar V(G)vertical bar(O(1)), MAX CUT cannot be solved in time (2 - epsilon)(tw(G))vertical bar V(G)vertical bar(O(1)), ODD CYCLE TRANSVERSAL cannot be solved in lime (3 - epsilon)(tw(G))vertical bar V(G)vertical bar(O(1)) For ally fixed q >= 3, q-COLORING cannot be solved in time (q - epsilon)(tw(G)) vertical bar V(G)vertical bar(O(1)), PARTITION INTO TRIANGLES cannot be solved in time (2 - epsilon)(tw(G))vertical bar V(G)vertical bar(O(1)). Our lower bounds match the running times for the best known algoritluns for the problems, up to the epsilon in the base
Hitting forbidden subgraphs in graphs of bounded treewidth
We study the complexity of a generic hitting problem H-Subgraph Hitting,
where given a fixed pattern graph and an input graph , the task is to
find a set of minimum size that hits all subgraphs of
isomorphic to . In the colorful variant of the problem, each vertex of
is precolored with some color from and we require to hit only
-subgraphs with matching colors. Standard techniques shows that for every
fixed , the problem is fixed-parameter tractable parameterized by the
treewidth of ; however, it is not clear how exactly the running time should
depend on treewidth. For the colorful variant, we demonstrate matching upper
and lower bounds showing that the dependence of the running time on treewidth
of is tightly governed by , the maximum size of a minimal vertex
separator in . That is, we show for every fixed that, on a graph of
treewidth , the colorful problem can be solved in time
, but cannot be solved in time
, assuming the Exponential Time
Hypothesis (ETH). Furthermore, we give some preliminary results showing that,
in the absence of colors, the parameterized complexity landscape of H-Subgraph
Hitting is much richer.Comment: A full version of a paper presented at MFCS 201
Covering Problems for Partial Words and for Indeterminate Strings
We consider the problem of computing a shortest solid cover of an
indeterminate string. An indeterminate string may contain non-solid symbols,
each of which specifies a subset of the alphabet that could be present at the
corresponding position. We also consider covering partial words, which are a
special case of indeterminate strings where each non-solid symbol is a don't
care symbol. We prove that indeterminate string covering problem and partial
word covering problem are NP-complete for binary alphabet and show that both
problems are fixed-parameter tractable with respect to , the number of
non-solid symbols. For the indeterminate string covering problem we obtain a
-time algorithm. For the partial word covering
problem we obtain a -time algorithm. We
prove that, unless the Exponential Time Hypothesis is false, no
-time solution exists for either problem, which shows
that our algorithm for this case is close to optimal. We also present an
algorithm for both problems which is feasible in practice.Comment: full version (simplified and corrected); preliminary version appeared
at ISAAC 2014; 14 pages, 4 figure
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