Maximum Exact Satisfiability: NP-completeness Proofs and Exact Algorithms
TL;DR: An exact algorithm is presented for Maximum Exact Satisfiability where each clause contains at most two literals with time complexity O(poly(L) .
Abstract: Inspired by the Maximum Satisfiability and Exact Satisfiability problems we present two Maximum Exact Satisfiability problems. The first problem called Maximum Exact Satisfiability is: given a formula in conjunctive normal form and an integer k, is there an assignment to all variables in the formula such that at least k clauses have exactly one true literal. The second problem called Restricted Maximum Exact Satisfiability has the further restriction that no clause is allowed to have more than one true literal. Both problems are proved NP-complete restricted to the versions where each clause contains at most two literals. In fact Maximum Exact Satisfiability is a generalisation of the well-known NP-complete problem MaxCut. We present an exact algorithm for Maximum Exact Satisfiability where each clause contains at most two literals with time complexity O(poly(L) . 2^{m/4}), where m is the number of clauses and L is the length of the formula. For the second version we give an algorithm with time complexity O(poly(L) . 1.324718^n) , where n is the number of variables. We note that when restricted to the versions where each clause contains exactly two literals and there are no negations both problems are fixed parameter tractable. It is an open question if this is also the case for the general problems.
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TL;DR: The construction of a refocus function shows how to mechanically obtain an abstract machine out of a reduction semantics, which was done previously on a case-by-case basis.
Abstract: The evaluation function of a reduction semantics (i.e., a small-step operational semantics with an explicit representation of the reduction context) is canonically defined as the transitive closure of (1) decomposing a term into a reduction context and a redex, (2) contracting this redex, and (3) plugging the contractum in the context. Directly implementing this evaluation function therefore yields an interpreter with a worst-case overhead, for each step, that is linear in the size of the input term. We present sufficient conditions over the constituents of a reduction semantics to circumvent this overhead, by replacing the composition of (3) plugging and (1) decomposing by a single ``refocus'' function mapping a contractum and a context into a new context and a new redex, if any. We also show how to construct such a refocus function, we prove the correctness of this construction, and we analyze the complexity of the resulting refocus function. The refocused evaluation function of a reduction semantics implements the transitive closure of the refocus function, i.e., a ``pre-abstract machine.'' Fusing the refocus function with the trampoline function computing the transitive closure gives a state-transition function, i.e., an abstract machine. This abstract machine clearly separates between the transitions implementing the congruence rules of the reduction semantics and the transitions implementing its reduction rules. The construction of a refocus function therefore shows how to mechanically obtain an abstract machine out of a reduction semantics, which was done previously on a case-by-case basis. We illustrate refocusing by mechanically constructing Felleisen et al.'s CK machine from a call-by-value reduction semantics of the lambda-calculus, and by constructing a substitution-based version of Krivine's machine from a call-by-name reduction semantics of the lambda-calculus. We also mechanically construct three one-pass CPS transformers from three quadratic context-based CPS transformers for the lambda-calculus.
124 citations
TL;DR: It is proved that a colimit preserving functor between presheaf categories (corresponding to a profunctor) preserves open maps and open map bisimulation, which provides a mathematical framework for extending domain theory and denotational semantics of programming languages to the more intricate models, languages and equivalences found in concurrent computation.
Abstract: This paper studies fundamental connections between profunctors (that is, distributors, or bimodules), open maps and bisimulation. In particular, it proves that a colimit preserving functor between presheaf categories (corresponding to a profunctor) preserves open maps and open map bisimulation. Consequently, the composition of profunctors preserves open maps as 2-cells. A guiding idea is the view that profunctors, and colimit preserving functors, are linear maps in a model of classical linear logic. But profunctors, and colimit preserving functors, as linear maps, are too restrictive for many applications. This leads to a study of a range of pseudo-comonads and of how non-linear maps in their co-Kleisli bicategories preserve open maps and bisimulation. The pseudo-comonads considered are based on finite colimit completion, ‘lifting’, and indexed families. The paper includes an appendix summarising the key results on coends, left Kan extensions and the preservation of colimits. One motivation for this work is that it provides a mathematical framework for extending domain theory and denotational semantics of programming languages to the more intricate models, languages and equivalences found in concurrent computation, but the results are likely to have more general applicability because of the ubiquitous nature of profunctors.
74 citations
23 Jun 2005
TL;DR: It is proved that given a graph, one can efficiently find a set of no more than m/5.217 + 1 nodes whose removal yields a partial two-tree, leading to algorithms for several problems, including Max-Cut, Max-2-SAT and Max- 2-XSAT that take O*(2m/ 5.769) time.
Abstract: We prove that given a graph, one can efficiently find a set of no more than m/5217 + 1 nodes whose removal yields a partial two-tree As an application, we immediately get simple algorithms for several problems, including Max-Cut, Max-2-SAT and Max-2-XSAT All of these take a record-breaking time of O*(2m/5217), where m is the number of clauses or edges, while only using polynomial space Moreover, the existence of the aforementioned node sets implies an upper bound of m/5217 + 3 on the treewidth of a graph with m edges Letting go of polynomial space restrictions, this can be improved to a bound of m/5769 + O(log n) on the pathwidth, leading to algorithms for the above problems that take O*(2m/5769) time
47 citations
01 Jan 2005
TL;DR: An upper bound of m/5.217 + 3 on the treewidth of a graph with m edges is proved, which implies a record-breaking time complexity of O(2), where t is the number of distinct clause types.
Abstract: We prove an upper bound of m/5.217 + 3 on the treewidth of a graph with m edges. Moreover, we can always find efficiently a set of no more than m/5.217 + 1 nodes whose removal yields a partial 2-tree. As an application, we immediately get simple algorithms for several problems, including Max-Cut, Max-2-SAT and Max-2-XSAT. The resulting algorithms have running times of O(2), where t is the number of distinct clause types. In particular, this implies a record-breaking time complexity of O(2).
45 citations
01 Jan 2006
TL;DR: This thesis presents exact means to solve a family of NP-hard problems, starting with the well-studied Exact Satisfiability problem (XSAT), from which parents, siblings and daughters are derived and studied, each with interesting practical and theoretical properties.
Abstract: This thesis presents exact means to solve a family of NP-hard problems. Starting with the well-studied Exact Satisfiability problem (XSAT) parents, siblings and daughters are derived and studied, each with interesting practical and theoretical properties. While developing exact algorithms to solve the problems, we gain new insights into their structure and mutual similarities and differences. Given a Boolean formula in CNF, the XSAT problem asks for an assignment to the variables such that each clause contains exactly one true literal. For this problem we present an O(1.1730n) time algorithm, where n is the number of variables. XSAT is a special case of the General Exact Satisfiability problem which asks for an assignment such that in each clause exactly i literals be true. For this problem we present an algorithm which runs in O(2(1-e) n) time, with 0 < e < 1 for every fixed i; for i=2, 3 and 4 we have running times in O(1.4511n), O(1.6214n) and O(1.6848n) respectively. For the counting problems we present an O(1.2190n) time algorithm which counts the number of models for an XSAT instance. We also present algorithms for #2SATw and #3SATw, two well studied Boolean problems. The algorithms have running times in O(1.2561n) and O(1.6737n) respectively. Finally we study optimisation problems: As a variant of the Maximum Exact Satisfiability problem, consider the problem of finding an assignment exactly satisfying a maximum number of clauses while the rest are left with no true literal. This problem is reducible to #2SATw without the addition of new variables and thus is solvable in time O(1.2561n). Another interesting optimisation problem is to find two XSAT models which differ in as many variables as possible. This problem is shown to be solvable in O(1.8348n) time.
35 citations
References
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01 Jan 1972
TL;DR: Throughout the 1960s I worked on combinatorial optimization problems including logic circuit design with Paul Roth and assembly line balancing and the traveling salesman problem with Mike Held, which made me aware of the importance of distinction between polynomial-time and superpolynomial-time solvability.
Abstract: Throughout the 1960s I worked on combinatorial optimization problems including logic circuit design with Paul Roth and assembly line balancing and the traveling salesman problem with Mike Held. These experiences made me aware that seemingly simple discrete optimization problems could hold the seeds of combinatorial explosions. The work of Dantzig, Fulkerson, Hoffman, Edmonds, Lawler and other pioneers on network flows, matching and matroids acquainted me with the elegant and efficient algorithms that were sometimes possible. Jack Edmonds’ papers and a few key discussions with him drew my attention to the crucial distinction between polynomial-time and superpolynomial-time solvability. I was also influenced by Jack’s emphasis on min-max theorems as a tool for fast verification of optimal solutions, which foreshadowed Steve Cook’s definition of the complexity class NP. Another influence was George Dantzig’s suggestion that integer programming could serve as a universal format for combinatorial optimization problems.
7,714 citations
TL;DR: This paper shows that a number of NP - complete problems remain NP -complete even when their domains are substantially restricted, and determines essentially the lowest possible upper bounds on node degree for which the problems remainNP -complete.
2,200 citations
01 May 1978
TL;DR: An infinite class of satisfiability problems is considered which contains these two particular problems as special cases, and it is shown that every member of this class is either polynomial-time decidable or NP-complete.
Abstract: The problem of deciding whether a given propositional formula in conjunctive normal form is satisfiable has been widely studied. I t is known that, when restricted to formulas having only two literals per clause, this problem has an efficient (polynomial-time) solution. But the same problem on formulas having three literals per clause is NP-complete, and hence probably does not have any efficient solution. In this paper, we consider an infinite class of satisfiability problems which contains these two particular problems as special cases, and show that every member of this class is either polynomial-time decidable or NP-complete. The infinite collection of new NP-complete problems so obtained may prove very useful in finding other new NP-complete problems. The classification of the polynomial-time decidable cases yields new problems that are complete in polynomial time and in nondeterministic log space. We also consider an analogous class of problems, involving quantified formulas, which has the property that every member is either polynomial time decidable or complete in polynomial space.
2,108 citations
TL;DR: It follows that such a complete problem has a polynomial-time approximation scheme iff the whole class does, and that a number of common optimization problems are complete for MAX SNP under a kind of careful transformation that preserves approximability.
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TL;DR: This work shows that INDEPENDENT SET is complete for W, and the W Hierarchy of parameterized problems was defined, and complete problems were identified for the classes W [ t ] for t ⩾ 2.
659 citations