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Summary: Dynamic Symmetry-Breaking for Improved Boolean Optimization
Fadi A. Aloul, Arathi Ramani£, Igor L. Markov£ and Karem A. Sakallah£
Department of Computer Engineering, American University of Sharjah, UAE
faloul @ausharjah.edu,
£ Department of EECS, University of Michigan, Ann Arbor, USA
ramania, imarkov, karem @eecs.umich.edu
Abstract
With impressive progress in Boolean Satisfiability (SAT)
solving and several extensions to pseudo-Boolean (PB) con-
straints, many applications that use SAT, such as high-
performance formal verification techniques are still restricted
to checking satisfiability of certain conditions. However,
there is also frequently a need to express a preference for
certain solutions. Extending SAT-solving to Boolean opti-
mization allows the use of objective functions to describe a
desirable solution. Although recent work in 0-1 Integer Lin-
ear Programming (ILP) offers extensions that can optimize a
linear objective function, this is often achieved by solving a
series of SAT or ILP decision problems. Our work articulates
some pitfalls of this approach. An objective function may
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