Relational Constraint Solving in SMT

2017 ◽  
pp. 148-165 ◽  
Author(s):  
Baoluo Meng ◽  
Andrew Reynolds ◽  
Cesare Tinelli ◽  
Clark Barrett
Keyword(s):  
Constraint Solving

CSS Minification via Constraint Solving

2019 ◽  
Vol 41 (2) ◽  
pp. 1-76
Author(s):  
Matthew Hague ◽  
Anthony W. Lin ◽  
Chih-Duo Hong
Keyword(s):  
Constraint Solving

Constraint Solving for Term Orderings Compatible with Abelian Semigroups, Monoids and Groups

Constraints ◽  
2004 ◽  
Vol 9 (3) ◽  
pp. 167-192
Author(s):  
Guillem Godoy ◽  
Robert Nieuwenhuis
Keyword(s):  
Constraint Solving

Backpropagation networks for logic constraint solving

1994 ◽  
Vol 6 (1) ◽  
pp. 67-98 ◽  
Author(s):  
Angelo Monfroglio
Keyword(s):  
Constraint Solving

Adaptive and Multilevel Approach for Constraint Solving

2013 ◽  
pp. 650-654 ◽  
Author(s):  
Claudio León de la Barra ◽  
Broderick Crawford ◽  
Ricardo Soto ◽  
Eric Monfroy
Keyword(s):  
Constraint Solving ◽  
Multilevel Approach

scholarly journals A Value Set Analysis Refinement Approach Based on Conditional Merging and Lazy Constraint Solving

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 114593-114606 ◽  
Author(s):  
Jian Lin ◽  
Liehui Jiang ◽  
Yisen Wang ◽  
Weiyu Dong
Keyword(s):  
Constraint Solving ◽  
Value Set ◽  
A Value

scholarly journals CLP-based protein fragment assembly

2010 ◽  
Vol 10 (4-6) ◽  
pp. 709-724 ◽  
Author(s):  
ALESSANDRO DAL PALÙ ◽  
AGOSTINO DOVIER ◽  
FEDERICO FOGOLARI ◽  
ENRICO PONTELLI
Keyword(s):  
Search Strategy ◽  
Protein Structures ◽  
Constraint Solving ◽  
Side Chain ◽  
Space Filling ◽  
Protein Fragment ◽  
Fragment Assembly ◽  
Energy Models ◽  
Novel Approach ◽  
Protein Model

AbstractThe paper investigates a novel approach, based on Constraint Logic Programming (CLP), to predict the 3D conformation of a protein via fragments assembly. The fragments are extracted by a preprocessor—also developed for this work—from a database of known protein structures that clusters and classifies the fragments according to similarity and frequency. The problem of assembling fragments into a complete conformation is mapped to a constraint solving problem and solved using CLP. The constraint-based model uses a medium discretization degree Cα-side chain centroid protein model that offers efficiency and a good approximation for space filling. The approach and adapts existing energy models to the protein representation used and applies a large neighboring search strategy. The results shows the feasibility and efficiency of the method. The declarative nature of the solution allows to include future extensions, e.g., different size fragments for better accuracy.

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