Article ID Journal Published Year Pages File Type
421479 Discrete Applied Mathematics 2006 23 Pages PDF
Abstract

Given a finite set VV, and a hypergraph H⊆2VH⊆2V, the hypergraph transversal problem calls for enumerating all minimal hitting sets (transversals) for HH. This problem plays an important role in practical applications as many other problems were shown to be polynomially equivalent to it. Fredman and Khachiyan [On the complexity of dualization of monotone disjunctive normal forms, J. Algorithms 21 (1996) 618–628] gave an incremental quasi-polynomial-time algorithm for solving the hypergraph transversal problem. In this paper, we present an efficient implementation of this algorithm. While we show that our implementation achieves the same theoretical worst-case bound, practical experience with this implementation shows that it can be substantially faster. We also show that a slight modification of the original algorithm can be used to obtain a stronger bound on the running time.More generally, we consider a monotone property ππ over a bounded n  -dimensional integral box. As an important application of the above hypergraph transversal problem, pioneered by Bioch and Ibaraki [Complexity of identification and dualization of positive Boolean functions, Inform. and Comput. 123 (1995) 50–63], we consider the problem of incrementally generating simultaneously all minimal subsets satisfying ππ and all maximal subsets not satisfying ππ, for properties given by a polynomial-time satisfiability oracle. Problems of this type arise in many practical applications. It is known that the above joint generation problem can be solved in incremental quasi-polynomial time via a polynomial-time reduction to a generalization of the hypergraph transversal problem on integer boxes. In this paper we present an efficient implementation of this procedure, and present experimental results to evaluate our implementation for a number of interesting monotone properties ππ.

Related Topics
Physical Sciences and Engineering Computer Science Computational Theory and Mathematics
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