Azucar: a SAT-based CSP solver using compact order encoding

Authors:
Tomoya Tanjo;Naoyuki Tamura;Mutsunori Banbara
Affiliations:
Transdisciplinary Research Integration Center, Japan;Information Science and Technology Center, Kobe University, Japan;Information Science and Technology Center, Kobe University, Japan
Venue:
SAT'12 Proceedings of the 15th international conference on Theory and Applications of Satisfiability Testing
Year:
2012

Citing 10
Cited 1

On the parallel complexity of discrete relaxation in constraint satisfaction networks

Artificial Intelligence
Handbook of Constraint Programming (Foundations of Artificial Intelligence)

Handbook of Constraint Programming (Foundations of Artificial Intelligence)
Universal Booleanization of Constraint Models

CP '08 Proceedings of the 14th international conference on Principles and Practice of Constraint Programming
Compiling finite linear CSP into SAT

Constraints
A comparison of ATMS and CSP techniques

IJCAI'89 Proceedings of the 11th international joint conference on Artificial intelligence - Volume 1
The log-support encoding of CSP into SAT

CP'07 Proceedings of the 13th international conference on Principles and practice of constraint programming
A SAT-based Method for Solving the Two-dimensional Strip Packing Problem

Fundamenta Informaticae - RCRA 2008 Experimental Evaluation of Algorithms for Solving Problems with Combinatorial Explosion
Generating combinatorial test cases by efficient SAT encodings suitable for CDCL SAT solvers

LPAR'10 Proceedings of the 17th international conference on Logic for programming, artificial intelligence, and reasoning
The order encoding: from tractable CSP to tractable SAT

SAT'11 Proceedings of the 14th international conference on Theory and application of satisfiability testing
A compact and efficient SAT-encoding of finite domain CSP

SAT'11 Proceedings of the 14th international conference on Theory and application of satisfiability testing

Problem transformations and algorithm selection for CSPs

IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper describes a SAT-based CSP solver Azucar. Azucar solves a finite CSP by encoding it into a SAT instance using the compact order encoding and then solving the encoded SAT instance with an external SAT solver. In the compact order encoding, each integer variable is represented by using a numeral system of base B≥2 and each digit is encoded by using the order encoding. Azucar is developed as a new version of an award-winning SAT-based CSP solver Sugar. Through some experiments, we confirmed Azucar can encode and solve very large domain sized CSP instances which Sugar can not encode, and shows better performance for Open-shop scheduling problems and the Cabinet problems of the CSP Solver Competition benchmark.