On Applying Cutting Planes in DLL-Based Algorithms for Pseudo-Boolean Optimization

Manquinho, Vasco; Marques-Silva, João

doi:10.1007/11499107_38

Cited by 10 publications

(6 citation statements)

References 17 publications

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“…They have been found to be very efficient in expressing "counting constraints" [18]. Furthermore, PB extends SAT solvers, such as PBS [19], Bsolo [20], Pueblo [21] and MiniSAT+ [22], to handle optimization problems as opposed to only decision problems. This feature has introduced many new applications to the SAT domain.…”

Section: Boolean Satisfiabilitymentioning

confidence: 99%

A SAT-based approach to solve the faculty course scheduling problem

2013

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The faculty course scheduling problem is concerned with assigning time slots to courses while taking into consideration some departmental and university constraints and instructor preferences. The problem also aims at optimizing the performance criteria and distributing the courses evenly among the available time slots. The problem is a classic scheduling problem and has received some research during the past few years due to its wide use in academic institutions. Most of the proposed solutions were based on local search techniques. In this paper, we present a complete approach to solving the course scheduling problem using Boolean Satisfiability (SAT). Experimental results show the effectiveness of the proposed approach.

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Section: Boolean Satisfiabilitymentioning

confidence: 99%

A SAT-based approach to solve the faculty course scheduling problem

2013

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“…[31] gives an overview of branch-and-bound techniques for PBO. Motivated by recent advances in SAT solvers, the most effective SAT techniques, including clause learning, lazy data structures and conflict-driven branching heuristics, have been extended to PBO [32]. In this work, we use the PBO solver MINISAT+ [22] which translates pseudoBoolean constraints to SAT and runs a state-of-the-art SAT solver [20] on the produced SAT instance.…”

Section: B Pseudo-boolean Satisfiabilitymentioning

confidence: 99%

Maximum Circuit Activity Estimation Using Pseudo-Boolean Satisfiability

Mangassarian

Veneris

Najm

2012

IEEE Trans. Comput.-Aided Des. Integr. Circuits Syst.

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Abstract-With lower supply voltages, increased integration densities and higher operating frequencies, power grid verification has become a crucial step in the VLSI design cycle. The accurate estimation of maximum instantaneous power dissipation aims at finding the worst-case scenario where excessive simultaneous switching could impose extreme current demands on the power grid. This problem is highly input-pattern dependent and is proven to be NP-hard. In this work, we capitalize on the compelling advancements in satisfiability solvers to propose a pseudo-Boolean satisfiability-based framework that reports the input patterns maximizing circuit activity, and consequently peak dynamic power, in combinational and sequential circuits. The proposed framework is enhanced to handle unit gate delays and output glitches. In order to disallow unrealistic input transitions, we show how to integrate input constraints in the formulation. Finally, a number of optimization techniques, such as the use of gate switching equivalence classes, are described to improve the scalability of the proposed method. An extensive suite of experiments on ISCAS85 and ISCAS89 circuits confirms the robustness of the approach compared to simulation-based techniques and encourages further research for low-power solutions using Boolean satisfiability.

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“…Learning techniques are also used in CP under the name of no-good recording techniques, see for instance [62,97]. Note also that resolution in SAT is a particular case of the Cutting Plane generation techniques used in the Operations Research literature for linear constraints [51,71,72]. Heuristics in SAT rely on the idea of giving higher priority to the variables that are involved in conflicts; such heuristics are called activity-based.…”

Section: Execution Tracing and Analysismentioning

confidence: 99%

Connections and Integration with SAT Solvers: A Survey and a Case Study in Computational Biology

Corblin

Bordeaux²,

Fanchon³

et al. 2010

Hybrid Optimization

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Boolean constraints play a fundamental rôle in optimization and constraint satisfaction. The resolution of these constraints has been the subject of intense and successful work during the past decade, and SAT solvers have reached a spectacular maturity. This chapter gives a brief overview of the relevant literature on modern SAT solvers and on the recent efforts to better integrate Boolean reasoning with other constraint satisfaction techniques. As a case study that illustrates the use of SAT and CP, we consider an application in computational biology: the task to build gene regulatory networks (GRNs). We report on experiments made on this problem with a combined SAT/CP approach.F. Corblin ( )

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On Applying Cutting Planes in DLL-Based Algorithms for Pseudo-Boolean Optimization

Cited by 10 publications

References 17 publications

A SAT-based approach to solve the faculty course scheduling problem

A SAT-based approach to solve the faculty course scheduling problem

Maximum Circuit Activity Estimation Using Pseudo-Boolean Satisfiability

Connections and Integration with SAT Solvers: A Survey and a Case Study in Computational Biology

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