MINIMAXSAT: An efficient weighted Max-SAT solver

被引:0
|
作者
Heras, Federico [1 ]
Larrosa, Javier [1 ]
Oliveras, Albert [1 ]
机构
[1] Tech Univ Catalonia, LSI Dept, Barcelona, Spain
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中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper we introduce MINIMAXSAT, a new Max-SAT solver that is built on top of MINISAT+. It incorporates the best current SAT and Max-SAT techniques. It can handle hard clauses (clauses of mandatory satisfaction as in SAT), soft clauses (clauses whose falsification is penalized by a cost as in Max-SAT) as well as pseudo-boolean objective functions and constraints. Its main features are: learning and backjumping on hard clauses; resolution-based and substraction-based lower bounding; and lazy propagation with the two-watched literal scheme. Our empirical evaluation comparing a wide set of solving alternatives on a broad set of optimization benchmarks indicates that the performance of MINIMAXSAT is usually close to the best specialized alternative and, in some cases, even better.
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页码:1 / 32
页数:32
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