Abstract
Unate and binate covering problems are a special class ofgeneral integer linear programming problems with which several problemsin logic synthesis, such as two-level logic minimization and technologymapping, are formulated. Previous branch-and-bound methodsfor exactly solving these problems use lower-bounding techniques basedon finding maximal independent sets. In this paper we examine lower-boundingtechniques based on linear programming relaxation (LPR) forthe binate covering problem. We show that a combination of traditionalreductions (essentiality and dominance) and incremental computation ofLPR-based lower bounds can exactly solve difficult covering problemsorders of magnitude faster than traditional methods.
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