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35
Parameterized Complexity: A Framework for Systematically Confronting Computational Intractability
 DIMACS Series in Discrete Mathematics and Theoretical Computer Science
, 1997
"... In this paper we give a programmatic overview of parameterized computational complexity in the broad context of the problem of coping with computational intractability. We give some examples of how fixedparameter tractability techniques can deliver practical algorithms in two different ways: (1) by ..."
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Cited by 85 (16 self)
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In this paper we give a programmatic overview of parameterized computational complexity in the broad context of the problem of coping with computational intractability. We give some examples of how fixedparameter tractability techniques can deliver practical algorithms in two different ways: (1) by providing useful exact algorithms for small parameter ranges, and (2) by providing guidance in the design of heuristic algorithms. In particular, we describe an improved FPT kernelization algorithm for Vertex Cover, a practical FPT algorithm for the Maximum Agreement Subtree (MAST) problem parameterized by the number of species to be deleted, and new general heuristics for these problems based on FPT techniques. In the course of making this overview, we also investigate some structural and hardness issues. We prove that an important naturally parameterized problem in artificial intelligence, STRIPS Planning (where the parameter is the size of the plan) is complete for W [1]. As a corollary, this implies that kStep Reachability for Petri Nets is complete for W [1]. We describe how the concept of treewidth can be applied to STRIPS Planning and other problems of logic to obtain FPT results. We describe a surprising structural result concerning the top end of the parameterized complexity hierarchy: the naturally parameterized Graph kColoring problem cannot be resolved with respect to XP either by showing membership in XP, or by showing hardness for XP without settling the P = NP question one way or the other.
Resolution is Not Automatizable Unless W[P] is Tractable
 IN 42ND ANNUAL IEEE SYMPOSIUM ON FOUNDATIONS OF COMPUTER SCIENCE
, 2001
"... We show that neither Resolution nor treelike Resolution is automatizable unless the class W[P] from the hierarchy of parameterized problems is fixedparameter tractable by randomized algorithms with onesided error. ..."
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Cited by 60 (2 self)
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We show that neither Resolution nor treelike Resolution is automatizable unless the class W[P] from the hierarchy of parameterized problems is fixedparameter tractable by randomized algorithms with onesided error.
Parameterized complexity and approximation algorithms
 Comput. J
, 2006
"... Approximation algorithms and parameterized complexity are usually considered to be two separate ways of dealing with hard algorithmic problems. In this paper, our aim is to investigate how these two fields can be combined to achieve better algorithms than what any of the two theories could offer. We ..."
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Cited by 58 (2 self)
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Approximation algorithms and parameterized complexity are usually considered to be two separate ways of dealing with hard algorithmic problems. In this paper, our aim is to investigate how these two fields can be combined to achieve better algorithms than what any of the two theories could offer. We discuss the different ways parameterized complexity can be extended to approximation algorithms, survey results of this type and propose directions for future research. 1.
Bidimensionality: New Connections between FPT Algorithms and PTASs
, 2005
"... We demonstrate a new connection between fixedparametertractability and approximation algorithms for combinatorial optimization problems on planar graphs and their generalizations. Specifically, we extend the theory of socalled "bidimensional " problems to show that essentially ..."
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Cited by 46 (7 self)
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We demonstrate a new connection between fixedparametertractability and approximation algorithms for combinatorial optimization problems on planar graphs and their generalizations. Specifically, we extend the theory of socalled &quot;bidimensional &quot; problems to show that essentially all such problems have both subexponential fixedparameter algorithms and PTASs. Bidimensional problems include e.g. feedbackvertex set, vertex cover, minimum maximal matching, face cover, a series of vertexremoval problems, dominating set,edge dominating set,
Parameterized Complexity: The Main Ideas and Connections to Practical Computing
, 2002
"... The purposes of this paper are two: (1) to give an exposition of the main ideas of parameterized complexity, and (2) to discuss the connections of parameterized complexity to the systematic design of heuristics and approximation algorithms. ..."
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Cited by 25 (6 self)
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The purposes of this paper are two: (1) to give an exposition of the main ideas of parameterized complexity, and (2) to discuss the connections of parameterized complexity to the systematic design of heuristics and approximation algorithms.
On the optimality of planar and geometric approximation schemes
"... We show for several planar and geometric problems that the best known approximation schemes are essentially optimal with respect to the dependence on ǫ. For example, we show that the 2O(1/ǫ) · n time approximation schemes for planar MAXIMUM INDEPENDENT SET and for TSP on a metric defined by a plan ..."
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Cited by 17 (5 self)
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We show for several planar and geometric problems that the best known approximation schemes are essentially optimal with respect to the dependence on ǫ. For example, we show that the 2O(1/ǫ) · n time approximation schemes for planar MAXIMUM INDEPENDENT SET and for TSP on a metric defined by a planar graph are essentially optimal: if there is a δ> 0 such that any of these problems admits a 2O((1/ǫ)1−δ) O(1) n time PTAS, then the Exponential Time Hypothesis (ETH) fails. It is known that MAXIMUM INDEPENDENT SET on unit disk graphs and the planar logic problems MPSAT, TMIN, TMAX admit nO(1/ǫ) time approximation schemes. We show that they are optimal in the sense that if there is a δ> 0 such that any of these problems admits a 2 (1/ǫ)O(1) nO((1/ǫ)1−δ) time PTAS, then ETH fails.
On the Parameterized Intractability of Closest Substring and Related Problems
 In Proc. 19th STACS, volume 2285 of LNCS
, 2002
"... We show that Closest Substring, one of the most important problems in the field of biological sequence analysis, is W[1]hard with respect to the number k of input strings (even over a binary alphabet). This problem is therefore unlikely to be solvable in time O(f(k)n for any function f and constant ..."
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Cited by 15 (4 self)
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We show that Closest Substring, one of the most important problems in the field of biological sequence analysis, is W[1]hard with respect to the number k of input strings (even over a binary alphabet). This problem is therefore unlikely to be solvable in time O(f(k)n for any function f and constant c independent of k  effectively, the problem can be expected to be intractable, in any practical sense, for k 3. Our result supports the intuition that Closest Substring is computationally much harder than the special case of Closest String, although both problems are NPcomplete and both possess polynomial time approximation schemes. We also prove W[1]hardness for other parameterizations in the case of unbounded alphabet size. Our main W[1]hardness result generalizes to Consensus Patterns, a problem of similar significance in computational biology.
Parameterized Complexity of Geometric Problems
, 2007
"... This paper surveys parameterized complexity results for hard geometric algorithmic problems. It includes fixedparameter tractable problems in graph drawing, geometric graphs, geometric covering and several other areas, together with an overview of the algorithmic techniques used. Fixedparameter in ..."
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Cited by 15 (5 self)
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This paper surveys parameterized complexity results for hard geometric algorithmic problems. It includes fixedparameter tractable problems in graph drawing, geometric graphs, geometric covering and several other areas, together with an overview of the algorithmic techniques used. Fixedparameter intractability results are surveyed as well. Finally, we give some directions for future research.
On the parameterized intractability of motif search problems
 Combinatorica
, 2006
"... We show that Closest Substring, one of the most important problems in the field of biological sequence analysis, is W[1]hard when parameterized by the number k of input strings (and remains so, even over a binary alphabet). This problem is therefore unlikely to be solvable in time O(f(k) · n c) fo ..."
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Cited by 14 (3 self)
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We show that Closest Substring, one of the most important problems in the field of biological sequence analysis, is W[1]hard when parameterized by the number k of input strings (and remains so, even over a binary alphabet). This problem is therefore unlikely to be solvable in time O(f(k) · n c) for any function f of k and constant c independent of k. The problem can therefore be expected to be intractable, in any practical sense, for k ≥ 3. Our result supports the intuition that Closest Substring is computationally much harder than the special case of Closest String, although both problems are NPcomplete. We also prove W[1]hardness for other parameterizations in the case of unbounded alphabet size. Our W[1]hardness result for Closest Substring generalizes to Consensus Patterns, a problem of similar significance in computational biology. 1