Using Lower-Bound Estimates in SAT-Based Pseudo-Boolean Optimization
نویسندگان
چکیده
Linear Pseudo-Boolean constraints offer a much more compact formalism to express significant boolean problems in several areas, ranging from Artificial Intelligence to Electronic Design Automation. This paper proposes a new algorithm for the Pseudo-Boolean Optimization Problem (PBO) which integrates features from recent advances in Boolean Satisfiability (SAT) and classical branch and bound algorithms. Moreover, the paper shows that the utilization of lower bound estimates can improve the overall performance of PBO solvers for different classes of instances. In addition, the paper describes how to apply nonchronological backtracking in the presence of conflicts that result from the bounding process. Finally, the paper also shows how the notion of Unique Implication Points (UIP), widely used in modern SAT solvers, can be generalized for PBO.
منابع مشابه
Effective Lower Bounding Techniques for Pseudo-Boolean Optimization
Linear Pseudo-Boolean Optimization (PBO) is a widely used modeling framework in Electronic Design Automation (EDA). Due to significant advances in Boolean Satisfiability (SAT), new algorithms for PBO have emerged, which are effective on highly constrained instances. However, these algorithms fail to handle effectively the information provided by the cost function of PBO. This paper addresses th...
متن کاملEfficient Haplotype Inference with Pseudo-boolean Optimization
Haplotype inference from genotype data is a key computational problem in bioinformatics, since retrieving directly haplotype information from DNA samples is not feasible using existing technology. One of the methods for solving this problem uses the pure parsimony criterion, an approach known as Haplotype Inference by Pure Parsimony (HIPP). Initial work in this area was based on a number of dif...
متن کاملOn Applying Unit Propagation-Based Lower Bounds in Pseudo-Boolean Optimization
Unit propagation-based (UP) lower bounds are used in the vast majority of current Max-SAT solvers. However, lower bounds based on UP have seldom been applied in PseudoBoolean Optimization (PBO) algorithms derived from the DPLL procedure for Propositional Satisfiability (SAT). This paper enhances a DPLL-style PBO algorithm with an UP lower bound, and establishes conditions that enable constraint...
متن کاملParallel Search for Boolean Optimization
The predominance of multicore processors has increased the interest in developing parallel Boolean Satisfiability (SAT) solvers. As a result, more parallel SAT solvers are emerging. Even though parallel approaches are known to boost performance, parallel approaches developed for Boolean optimization are scarce. This paper proposes parallel search algorithms for Boolean optimization and introduc...
متن کاملThe long way from CDClL
Current SAT solvers are powerful enough to be used as engines in real applications. Those applications made the success of a special kind of SAT solvers, namely Conflict Driven Clause Learning SAT solvers (CDClL for short), developed initially by Joao Marques Silva with GRASP [8], and popularized by the SAT solver Chaff [9]. Despite SAT being a NP-complete problem in theory, it might look tract...
متن کامل