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The First Evaluation of Pseudo-Boolean Solvers (PB'05)

Vasco M. Manquinho, Olivier Roussel, Daniel Le Berre, Laurent Simon
2006 Journal on Satisfiability, Boolean Modeling and Computation  
The first goal of this event is to take a snapshot of the current state of the art in the field of pseudo-boolean constraints.  ...  The first evaluation of pseudo-boolean solvers was organized as a subtrack of the SAT 2005 competition.  ...  Acknowledgements The authors are greatly indebted to Daniel LE BERRE and Laurent SIMON for providing the scripts of the SAT competition, to the LINC Lab, Department of ECECS, University of Cincinnati for  ... 
doi:10.3233/sat190018 fatcat:w5gxdkngrrgljh45dlqgipibyy

Learn to relax: Integrating 0-1 integer linear programming with pseudo-Boolean conflict-driven search

Jo Devriendt, Ambros Gleixner, Jakob Nordström
2021 Constraints  
Inspired by mixed integer programming (MIP), we address this problem by interleaving incremental LP solving with cut generation within the conflict-driven pseudo-Boolean search.  ...  Conflict-driven pseudo-Boolean solvers optimize 0-1 integer linear programs by extending the conflict-driven clause learning (CDCL) paradigm from SAT solving.  ...  By a pseudo-Boolean formula ϕ we mean a set of PB constraints, or, in other words, a (decision version of a) 0-1 integer linear program (ILP).  ... 
doi:10.1007/s10601-020-09318-x fatcat:pbjdf3fzrvcovgzuchxy44b7yq

Solving Intensional Weighted CSPs by Incremental Optimization with BDDs [chapter]

Miquel Bofill, Miquel Palahí, Josep Suy, Mateu Villaret
2014 Lecture Notes in Computer Science  
The novelty of the method herewith described lies in representing the bound constraint as a shared Binary Decision Diagram, which in turn is translated into SAT.  ...  of the objective function.  ...  By reifying a soft constraint C i we mean adding a hard constraint x i ↔ C i , where x i is a new pseudo-Boolean variable.  ... 
doi:10.1007/978-3-319-10428-7_17 fatcat:tmjwrahztzbcdau7u3j6gqsgbu

Griffin: A Tool for Symbolic Inference of Synchronous Boolean Molecular Networks

Stalin Muñoz, Miguel Carrillo, Eugenio Azpeitia, David A. Rosenblueth
2018 Frontiers in Genetics  
Next, Boolean networks are inferred by using biological constraints to narrow the search space, such as a desired set of (fixed-point or cyclic) attractors.  ...  A number of Boolean gene networks have been inferred following essentially the same method. Such a method first considers experimental data for a typically underdetermined "regulation" graph.  ...  We greatly appreciate the feedback provided by all participants of the course Griffin, una herramienta de model checking para el análisis de redes booleanas.  ... 
doi:10.3389/fgene.2018.00039 pmid:29559993 pmcid:PMC5845696 fatcat:27lyuw3ravfahnkvhzt4auhrau

Migrating Techniques from Search-based Multi-Agent Path Finding Solvers to SAT-based Approach

Pavel Surynek, Roni Stern, Eli Boyarski, Ariel Felner
2022 The Journal of Artificial Intelligence Research  
Using both a lower bound on the sum-of-costs and an upper bound on the makespan, MDD-SAT is able to generate a reasonable number of Boolean variables in our SAT encoding.  ...  We then further improve the encoding by borrowing ideas from ICTS, a search-based solver.  ...  Acknowledgments This research was supported by the Czech Science Foundation (GA ČR), the grant registration number 19-17966S.  ... 
doi:10.1613/jair.1.13318 fatcat:mmkybuihwnbwjgmbszq443yldq

Smoothed analysis

Daniel A. Spielman, Shang-Hua Teng
2009 Communications of the ACM  
Smoothed analysis [36] is a step towards a theory that explains the behavior of algorithms in practice.  ...  A concrete example of such a smoothed analysis is a proof that the simplex algorithm for linear programming usually runs in polynomial time, when its input is subject to modeling or measurement noise.  ...  Remark: Usually by saying Π has a pseudo-polynomial time algorithm, one means Πu ∈ P. So Πu ∈ ZPP means that Π is solvable by a randomized pseudo-polynomial time algorithm.  ... 
doi:10.1145/1562764.1562785 fatcat:7ohrugpymnffdcybqntslgtkom

Configuration landscape analysis and backbone guided local search

Weixiong Zhang
2004 Artificial Intelligence  
In this paper, we first investigate the configuration landscapes of local minima reached by the WalkSAT local search algorithm, one of the most effective algorithms for SAT.  ...  Boolean satisfiability (SAT) and maximum satisfiability (Max-SAT) are difficult combinatorial problems that have many important real-world applications.  ...  Acknowledgements This research was supported in part by NSF grants IIS-0196057 and EIA-0113618 under the ITR program, and in part by DARPA Cooperative Agreements F30602-00-2-0531 and F33615-01-C-1897.  ... 
doi:10.1016/j.artint.2004.04.001 fatcat:d4asotzy3vdjlm7rh6clpffiny

Semantic Boolean Arabic Information Retrieval [article]

Emad Elabd, Eissa Alshari, Hatem Abdulkader
2015 arXiv   pre-print
We conclude that AIR frameworks have a weakness to deal with semantic in term of indexing, Boolean model, Latent Semantic Analysis (LSA), Latent Semantic Index (LSI) and semantic ranking.  ...  Arabic language is one of the most widely spoken languages. This language has a complex morphological structure and is considered as one of the most prolific languages in terms of article linguistic.  ...  From the table, there is a big gap between the classic IR approaches and the SW technologies. One of these problems is the lack of Boolean semantic IR model.  ... 
arXiv:1512.03167v1 fatcat:bydhpdrs65f4tkmwbadqrstac4

Logic, Optimization, and Constraint Programming

John N. Hooker
2002 INFORMS journal on computing  
It traces the history of logic-based methods in optimization and the development of constraint programming in artificial intelligence.  ...  This paper summarizes and contrasts the characteristics of the two fields; in particular, how they use logical inference in different ways, and how these ways can be combined.  ...  This method is readily applied to pseudo-boolean optimization.  ... 
doi:10.1287/ijoc.14.4.295.2828 fatcat:22kiqfcqqvfcppogsgbd5xqj2y

Integrated logic synthesis using simulated annealing

Petra Färm, Elena Dubrova, Andreas Kuehlmann
2011 Proceedings of the 21st edition of the great lakes symposium on Great lakes symposium on VLSI - GLSVLSI '11  
The results show that, on average, the presented advanced annealing approach can improve the area and delay of circuits optimized using the Boolean optimization technique provided by SIS with 11.2% and  ...  Dynamic weighting reflects the sensitivity of the local graph structures with respect to the actual technology parameters such as gate sizes, delays, and power levels.  ...  Implication is denoted by ⇒ and co-implication by ⇔. The symbol ":" means "such that". The set of real numbers is denoted by ℜ. The set of binary values 0, 1 is denoted by B.  ... 
doi:10.1145/1973009.1973095 dblp:conf/glvlsi/FarmDK11 fatcat:dlju72re25ae7jgninv5kuntia

Minimizing energy below the glass thresholds

Demian Battaglia, Michal Kolář, Riccardo Zecchina
2004 Physical Review E  
Focusing on the optimization version of the random K-satisfiability problem, the MAX-K-SAT problem, we study the performance of the finite energy version of the Survey Propagation (SP) algorithm.  ...  A comparative numerical study on one of the most efficient local search procedures is also given.  ...  It is very easy to state: Given N Boolean variables and M constraints taking the form of clauses, K-SAT consists in asking whether it exists an assignment of the variables that satisfies all constraints  ... 
doi:10.1103/physreve.70.036107 pmid:15524587 fatcat:65cpccctynfztm62ie3rzyktfy

Consistency and Random Constraint Satisfaction Models

Y. Gao, J. Culberson
2007 The Journal of Artificial Intelligence Research  
levels of constraint consistency.  ...  In this paper, we study the possibility of designing non-trivial random CSP models by exploiting the intrinsic connection between structures and typical-case hardness.  ...  Acknowledgments A preliminary version of this paper appeared in the Proceedings of the Tenth International Conference on Principles and Practice of Constraint Programming (CP-2004).  ... 
doi:10.1613/jair.2155 fatcat:uagiecj7kfctjlyuerwvi44264

Künstliche Intelligenz und Operations Research [chapter]

A. Bockmayr, F. J. Radermacher
1993 Grundlagen und Anwendungen der Künstlichen Intelligenz  
Acknowledgement I like to thank Alexander Bockmayr for pointing out the possible relevance of [8) in the context of constraint logic programming and for his valuable comments and fruitful discussions.  ...  Pseudo-Boolean constraints are equations and inequalities between pseudo-Boolean functions.  ...  The integration of pseudo-Boolean constraints into logic programming was first introduced in [4] .  ... 
doi:10.1007/978-3-642-78545-0_22 fatcat:24pvv4xowba7xn2wxdrdwo3j3u

Consistency and Random Constraint Satisfaction Models with a High Constraint Tightness [chapter]

Yong Gao, Joseph Culberson
2004 Lecture Notes in Computer Science  
levels of constraint consistency.  ...  In this paper, we study the possibility of designing non-trivial random CSP models by exploiting the intrinsic connection between structures and typical-case hardness.  ...  Acknowledgments A preliminary version of this paper appeared in the Proceedings of the Tenth International Conference on Principles and Practice of Constraint Programming (CP-2004).  ... 
doi:10.1007/978-3-540-30201-8_5 fatcat:bo4bmddgg5erfiakajzmf2uioi

A unified approach to mixed-integer optimization problems with logical constraints [article]

Dimitris Bertsimas, Ryan Cory-Wright, Jean Pauphilet
2021 arXiv   pre-print
In this work, we challenge this longstanding modeling practice and express the logical constraints in a non-linear way.  ...  These problems exhibit logical relationships between continuous and discrete variables, which are usually reformulated linearly using a big-M formulation.  ...  facility location, network design or sparse portfolio problems with big-M constraints by default, although they are actually reformulations of logical constraints.  ... 
arXiv:1907.02109v3 fatcat:hkipriyxhrgrxfpgnlypgpw47e
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