For a given parameterized problem, pi, a kernelization algorithm is a polynomial-time pre-processing procedure that transforms an arbitrary instance of pi into an equivalent one whose size depends only on the input pa...
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For a given parameterized problem, pi, a kernelization algorithm is a polynomial-time pre-processing procedure that transforms an arbitrary instance of pi into an equivalent one whose size depends only on the input parameter(s). The resulting instance is called a problem kernel. In this paper, a kernelization algorithm for the 3-Hitting Set problem is presented along with a general kernelization for d-Hitting Set. For 3-Hitting Set, an arbitrary instance is reduced into an equivalent one that contains at most 5k(2) + k elements. This kernelization is an improvement over previously known methods that guarantee cubic-order kernels. Our method is used also to obtain quadratic kernels for several other problems. For a constant d >= 3, a kernelization of d-Hitting Set is achieved by a non-trivial generalization of the 3-Hitting Set method, and guarantees a kernel whose order does not exceed (2d - 1)k(d-1) + k. (C) 2009 Elsevier Inc. All rights reserved.
We consider the SHORTEST ODD PATH problem, where given an undirected graph G, a weight function on its edges, and two vertices s and t in G, the aim is to find an (s, t)-path with odd length and, among all such paths,...
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We consider the SHORTEST ODD PATH problem, where given an undirected graph G, a weight function on its edges, and two vertices s and t in G, the aim is to find an (s, t)-path with odd length and, among all such paths, of minimum weight. For the case when the weight function is conservative, i.e., when every cycle has non-negative total weight, the complexity of the SHORTEST ODD PATH problem had been open for 20 years, and was recently shown to be NP-hard. We give a polynomial-time algorithm for the special case when the weight function is conservative and the set E- of negative-weight edges forms a single tree. Our algorithm exploits the strong connection between SHORTEST ODD PATH and the problem of finding two internally vertex-disjoint paths between two terminals in an undirected edgeweighted graph. It also relies on solving an intermediary problem variant called SHORTEST PARITY-CONSTRAINED ODD PATH where for certain edges we have parity constraints on their position along the path. Also, we exhibit two FPT algorithms for solving SHORTEST ODD PATH. The first FPT algorithm is parameterized by |E-|, the number of negative edges, or more generally, by the maximum size of a matching in the subgraph of G spanned by E-, when the weight function is conservative. Our second FPT algorithm is parameterized by the treewidth of G, and the algorithm does not rely on conservativeness. (c) 2024 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC license (http://***/licenses/by- nc/4.0/).
A graph is 2K(2)-partitionable if its vertex set can be partitioned into four nonempty parts A, B, C, D such that each vertex of A is adjacent to each vertex of B, and each vertex of C is adjacent to each vertex of D....
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A graph is 2K(2)-partitionable if its vertex set can be partitioned into four nonempty parts A, B, C, D such that each vertex of A is adjacent to each vertex of B, and each vertex of C is adjacent to each vertex of D. Determining whether an arbitrary graph is 2K(2)-partitionable is the only vertex-set partition problem into four nonempty parts according to external constraints whose computational complexity is open. We establish that the 2K(2)-partition problem parameterized by minimum degree is fixed-parameter tractable. We also show that for C-4-free graphs, circular-arc graphs, spiders, P-4-sparse graphs, and bipartite graphs the 2K(2)-partition problem can be solved in polynomial time. (C) 2009 Elsevier B.V. All rights reserved.
The parameterized complexity of the FACE COVER problem is considered. The input to this problem is a plane graph G with n vertices. The question asked is whether, for a given parameter value k, there exists a set of k...
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The parameterized complexity of the FACE COVER problem is considered. The input to this problem is a plane graph G with n vertices. The question asked is whether, for a given parameter value k, there exists a set of k or fewer faces whose boundaries collectively cover (contain) every vertex in G. Early attempts achieved run times of O*(12(k)) or worse, by reducing the problem into a special form of DOMINATING SET, namely RED-BLUE DOMINATING SET, restricted to planar graphs. Here, we consider a direct approach, where some surgical operation is performed on the graph at each branching decision. This paper builds on previous work of the authors and employs a structure theorem of Aksionov et al., with a detailed case analysis, to produce a FACE COVER algorithm that runs in O(4.6056(k) + n(2)) time. We also point to the tight connections with RED-BLUE DOMINATING SET on planar graphs via the annotated version of FACE COVER that we consider in our search tree algorithm. Hence, we get both a O(4.6056(k) + n(2)) time algorithm for solving RED-BLUE dominating SET on planar graphs and a polynomial time algorithm for producing a linear kernel for annotated face cover. (C) 2008 Elsevier B.V. All rights reserved.
Shortest common supersequence and longest common subsequence are two widely used measures to compare sequences in different fields, from AI planning to Bioinformatics. Inspired by recently proposed variants of these t...
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Shortest common supersequence and longest common subsequence are two widely used measures to compare sequences in different fields, from AI planning to Bioinformatics. Inspired by recently proposed variants of these two measures, we introduce a new version of the shortest common supersequence problem, where the solution is required to satisfy a given constraint on the number of occurrences of each symbol. First, we investigate the computational and approximation complexity of the problem, then we give a 3/2-approximation algorithm. Finally, we investigate the parameterized complexity of the problem, and we present a fixed-parameter algorithm. (C) 2013 Elsevier B.V. All rights reserved.
We prove that any H-minor-free graph, for a fixed graph H, of treewidth w has ail Omega(w) x Omega(w) grid graph as a minor. Thus grid ininors suffice to certify that H-minor-free graphs have large treewidth, up to co...
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We prove that any H-minor-free graph, for a fixed graph H, of treewidth w has ail Omega(w) x Omega(w) grid graph as a minor. Thus grid ininors suffice to certify that H-minor-free graphs have large treewidth, up to constant factors. This strong relationship was previously known for the special cases of planar graphs and bounded-genus graphs, and is known not to hold for general graphs. The approach of this paper can be viewed more generally as a framework for extending combinatorial results on planar graphs to hold on H-minor-free graphs for any fixed H. Our result has many combinatorial consequences on bidimensionality theory, parameter-treewidth bounds, separator theorems, and bounded local treewidth;each of these combinatorial results has several algorithmic consequences including subexponential fixed-parameter algorithms and approximation algorithms.
The problem of finding the maximum number of vertex-disjoint uni-color paths in an edge-colored graph has been recently introduced in literature, motivated by applications in social network analysis. In this paper we ...
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The problem of finding the maximum number of vertex-disjoint uni-color paths in an edge-colored graph has been recently introduced in literature, motivated by applications in social network analysis. In this paper we investigate the approximation and parameterized complexity of the problem. First, we show that, for any constant epsilon > 0, the problem is not approximable within factor c(1-epsilon), where c is the number of colors, and that the corresponding decision problem is W[1]-hard when parametrized by the number of disjoint paths. Then, we present a fixed-parameter algorithm for the problem parameterized by the number and the length of the disjoint paths.
Given a set of n strings of length L and a radius d, the closest string problem (CSP for short) asks for a string t(sol) that is within a Hamming distance of d to each of the given strings. It is known that the proble...
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Given a set of n strings of length L and a radius d, the closest string problem (CSP for short) asks for a string t(sol) that is within a Hamming distance of d to each of the given strings. It is known that the problem is NP-hard and its optimization version admits a polynomial time approximation scheme (PTAS). parameterized algorithms have been then developed to solve the problem when d is small. In this paper, with a new approach (called the 3-string approach), we first design a parameterized algorithm for binary strings that runs in O (nL + nd(3).6.731(d)) time, while the previous best runs in O (nL + nd.8(d)) time. We then extend the algorithm to arbitrary alphabet sizes, obtaining an algorithm that runs in time O(nL + nd.(1.612(vertical bar Sigma vertical bar + beta(2) + beta - 2))(d)), where vertical bar Sigma vertical bar is the alphabet size and beta = alpha(2) + 1 - 2 alpha(-1) + alpha(2) with alpha = 3 root root vertical bar Sigma vertical bar - 1 + 1. This new time bound is better than the previous best for small alphabets, including the very important case where vertical bar Sigma vertical bar = 4 (i.e., the case of DNA strings). (C) 2011 Elsevier Inc. All rights reserved.
The connected dominating set (CDS) problem is a well studied NP-hard problem with many important applications. Dorn et al. [ESA2005, LNCS3669,pp95-106] introduce a new technique to generate 2(O)(root n) time and fixed...
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ISBN:
(纸本)9783642174605
The connected dominating set (CDS) problem is a well studied NP-hard problem with many important applications. Dorn et al. [ESA2005, LNCS3669,pp95-106] introduce a new technique to generate 2(O)(root n) time and fixed-parameter algorithms for a number of non-local hard problems, including the CDS problem in planar graphs. The practical performance of this algorithm is yet to be evaluated. We perform a computational study for such an evaluation. The results show that the size of instances can be solved by the algorithm mainly depends on the branchwidth of the instances, coinciding with the theoretical result. For graphs with small or moderate branchwidth, the CDS problem instances with size up to a few thousands edges can be solved in a practical time and memory space. This suggests that the branch-decomposition based algorithms can be practical for the planar CDS problem.
We present a reduction procedure that takes an arbitrary instance of the 3-Set Packing problem and produces ail equivalent instance whose number of elements is bounded by a quadratic function of the input parameter. S...
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ISBN:
(纸本)9783642020162
We present a reduction procedure that takes an arbitrary instance of the 3-Set Packing problem and produces ail equivalent instance whose number of elements is bounded by a quadratic function of the input parameter. Such parameterized reductions are known as kernelization algorithms, and each reduced instance is called a problem kernel. Our result improves oil previously known kernelizations and call be generalized to produce improved kernels for the r-Set Packing problem whenever r is a fixed constant. Improved kernelization for r-Dimensional-Matching can also be inferred.
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