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Proceeding of the First International Conference on Modeling, Simulation and Applied Optimization, Sharjah, U.A.E. February 1-3, 2005 ICMSAO/05-1
 

Summary: Proceeding of the First International Conference on Modeling, Simulation and Applied Optimization, Sharjah, U.A.E. February 1-3, 2005
ICMSAO/05-1
ABSTRACT
The last few years have seen significant advances in Boolean sat-
isfiability (SAT) solving. This has lead to the successful deploy-
ment of SAT solvers in a wide range of problems in Engineering
and Computer Science. In general, most SAT solvers are applied to
Boolean decision problems that are expressed in conjunctive nor-
mal form (CNF). While this input format is applicable to some en-
gineering tasks, it poses a significant obstacle to others. One of the
main advances in SAT is generalizing SAT solvers to handle stron-
ger representation of constraints. Specifically, pseudo-Boolean
(PB) constraints which are efficient in representing counting con-
straints and can replace an exponential number of CNF constraints.
Another significant advantage of PB constraints is its ability to ex-
press Boolean optimization problems. This allows for new applica-
tions that were never handled by SAT solvers before. In this paper,
we describe two methods to solve Boolean optimization problems
using SAT solvers. Both methods are implemented and evaluated
using the SAT solver PBS. We develop an adaptive flow that ana-

  

Source: Aloul, Fadi - Department of Computer Engineering, American University of Sharjah

 

Collections: Engineering