We describe exact algorithms that provide new upper bounds for the Maximum Satisfiability problem (MaxSat). We prove that MaxSat can be solved in time O(|F | · 1.3972 K), where |F | is the length of a formula F in conjunctive normal form and K is the number of clauses in F. We also prove the time bounds O(|F | · 1.3995 k), where k is the maximum number of satisfiable clauses, and O((1.1279) |F | ) for the same problem. For Max2Sat this implies a bound of O(1.2722 K). An exponential time approximation algorithm by Dantsin et al. uses an exact algorithm for MaxSat as a building block and is therefore also improved.

In this paper we present improved exact and parameterized algorithms for the maximum satisfiability problem. In particular, we give an algorithm that computes a truth assignment for a boolean formula F satisfying the maximum number of clauses in time O(1.3247 m |F |), where m is the number of clauses in F, and |F | is the sum of the number of literals appearing in each clause in F. Moreover, given a parameter k, we give an O(1.3695 k + |F |) parameterized algorithm that decides whether a truth assignment for F satisfying at least k clauses exists. Both algorithms improve the previous best algorithms by Bansal and Raman for the problem. Key words. maximum satisfiability, exact algorithms, parameterized algorithms. 1

We describe a point of view about the parameterized computational complexity framework in the broad context of one of the central issues of theoretical computer science as a field: the problem of systematically coping with computational intractability. Those already familiar with the basic ideas of parameterized complexity will nevertheless find here something new: the emerging systematic connections between fixed-parameter tractability techniques and the design of useful heuristic algorithms, and also perhaps the philosophical maturation of the parameterized complexity program.

This paper surveys parameterized complexity results for hard geometric algorithmic problems. It includes fixed-parameter tractable problems in graph drawing, geometric graphs, geometric covering and several other areas, together with an overview of the algorithmic techniques used. Fixed-parameter intractability results are surveyed as well. Finally, we give some directions for future research.

This document is mainly based on "A Compendium of Parameterized Complexity Results", version 2.0 (May 22, 1996), by Michael T. Hallett and H. Todd Wareham, and on Downey and Fellows' book [53]. However, this document includes several new results that have been published in the last few years

Abstract. The notion of fixed-parameter approximation is introduced to investigate the approximability of optimization problems within the framework of fixed-parameter computation. This work partially aims at enhancing the world of fixed-parameter computation in parallel with the conventional theory of computation that includes both exact and approximate computations. In particular, it is proved that fixed-parameter approximability is closely related to the approximation of small-cost solutions in polynomial time. It is also demonstrated that many fixedparameter intractable problems are not fixed-parameter approximable. On the other hand, fixed-parameter approximation appears to be a viable approach to solving some inapproximable yet important optimization problems. For instance, all problems in the class MAX SNP admit fixed-parameter approximation schemes in time O(2 O((1−ɛ/O(1))k) p(n)) for any small ɛ>0. 1

Abstract not found

Recent time has seen quite some progress in the development of exponential time algorithms for NP-hard problems, where the base of the exponential term is fairly small. These developments are also tightly related to the theory of fixed parameter tractability. In this incomplete survey, we explain some basic techniques in the design of efficient fixed parameter algorithms, discuss deficiencies of parameterized complexity theory, and try to point out some future research challenges. The focus of this paper is on the design of efficient algorithms and not on a structural theory of parameterized complexity. Moreover, our emphasis will be laid on two exemplifying issues: Vertex Cover and MaxSat problems. A shorter version of this paper appears as an invited talk in the proceedings of the 25th Conference on Current Trends in Theory and Practice of Informatics (SOFSEM'98), Springer, LNCS , held in Jasna, Slovakia, November 21--27, 1998. y Supported by a Feodor Lynen fellowship of the Alex...

We survey recent results on the complexity of several versions of the H-coloring and the list-H-coloring problems that are amenable to parameterization.

The inapproximability of non NP-hard optimization problems is investigated. Techniques are given to show that problems Log Dominating Set and Log Hypergraph Vertex Cover cannot be approximated to a constant ratio in polynomial time unless the corresponding NP-hard versions are also approximable in deterministic subexponential time. A direct connection is established between non NP-hard problems and a PCP characterization of NP. Reductions from the PCP characterization show that Log Clique is not approximable in polynomial time and Max Sparse SAT does not have a PTAS under the assumption that NP 6 DTIME(2 O(log n p n) ). A number of non-trivial approximation-preserving reductions are also presented, making it possible to extend inapproximability results to more natural non NP-hard problems such as Tournament Dominating Set and Rich Hypergraph Vertex Cover. 1 Introduction Recent work on the approximability of NP-hard optimization problems has shown that the task of comput...