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Fifth International Symposium on Theory and Applications of Satisfiability Testing, May 6-9, 2000, Cincinnati, Ohio Optimized solvers for the Boolean Satisfiability (SAT)
 

Summary: 346
Fifth International Symposium on Theory and Applications of Satisfiability Testing, May 6-9, 2000, Cincinnati, Ohio
Abstract
Optimized solvers for the Boolean Satisfiability (SAT)
problem [5, 14, 15, 17, 19, 23, 24] found many applications
in areas such as hardware and software verification, FPGA
routing, planning in AI, etc. Further uses are complicated by
the need to express "counting constraints" in conjunctive
normal form (CNF). Expressing such constraints by pure
CNF leads to more complex SAT instances. Alternatively,
those constraints can be handled by Integer Linear Pro-
gramming (ILP), but off-the-shelf ILP solvers tend to ignore
the Boolean nature of 0-1 variables.
This work attempts to generalize recent highly successful
SAT techniques to new applications. First, we extend the
basic Davis-Putnam framework to handle counting con-
straints and apply it to solve routing problems. Our imple-
mentation outperforms previously reported solvers for the
satisfiability with "pseudo-Boolean" constraints and shows
significant speed-up over best SAT solvers when such con-

  

Source: Aloul, Fadi - Department of Computer Engineering, American University of Sharjah
Markov, Igor - Department of Electrical Engineering and Computer Science, University of Michigan

 

Collections: Computer Technologies and Information Sciences; Engineering