DeepAI AI Chat
Log In Sign Up

Set Constraint Model and Automated Encoding into SAT: Application to the Social Golfer Problem

06/27/2014
by   Frédéric Lardeux, et al.
Pontificia Universidad Católica de Valparaíso
Université d'Angers
University of Nantes
0

On the one hand, Constraint Satisfaction Problems allow one to declaratively model problems. On the other hand, propositional satisfiability problem (SAT) solvers can handle huge SAT instances. We thus present a technique to declaratively model set constraint problems and to encode them automatically into SAT instances. We apply our technique to the Social Golfer Problem and we also use it to break symmetries of the problem. Our technique is simpler, more declarative, and less error-prone than direct and improved hand modeling. The SAT instances that we automatically generate contain less clauses than improved hand-written instances such as in [20], and with unit propagation they also contain less variables. Moreover, they are well-suited for SAT solvers and they are solved faster as shown when solving difficult instances of the Social Golfer Problem.

READ FULL TEXT

page 1

page 2

page 3

page 4

05/02/2013

Extending Modern SAT Solvers for Enumerating All Models

In this paper, we address the problem of enumerating all models of a Boo...
09/04/2022

Proof-Stitch: Proof Combination for Divide and Conquer SAT Solvers

With the increasing availability of parallel computing power, there is a...
01/18/2014

Local Consistency and SAT-Solvers

Local consistency techniques such as k-consistency are a key component o...
09/27/2019

SAT vs CSP: a commentary

In 2000, I published a relatively comprehensive study of mappings betwee...
03/05/2019

PDP: A General Neural Framework for Learning Constraint Satisfaction Solvers

There have been recent efforts for incorporating Graph Neural Network mo...
11/24/2018

Streamlining Variational Inference for Constraint Satisfaction Problems

Several algorithms for solving constraint satisfaction problems are base...
01/10/2014

Transformation-based Feature Computation for Algorithm Portfolios

Instance-specific algorithm configuration and algorithm portfolios have ...