Edge Matching Puzzles as Hard SAT/CSP Benchmarks

Authors:
Carlos Ansótegui;Ramón Béjar;César Fernàndez;Carles Mateu
Affiliations:
Dept. of Computer Science, Universitat de Lleida, Spain;Dept. of Computer Science, Universitat de Lleida, Spain;Dept. of Computer Science, Universitat de Lleida, Spain;Dept. of Computer Science, Universitat de Lleida, Spain
Venue:
CP '08 Proceedings of the 14th international conference on Principles and Practice of Constraint Programming
Year:
2008

Citing 4
Cited 5

A filtering algorithm for constraints of difference in CSPs

AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
Generating Satisfiable Problem Instances

Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
Jigsaw Puzzles, Edge Matching, and Polyomino Packing: Connections and Complexity

Graphs and Combinatorics
The symmetric alldiff constraint

IJCAI'99 Proceedings of the 16th international joint conference on Artifical intelligence - Volume 1

Approximability of Edge Matching Puzzles

SOFSEM '10 Proceedings of the 36th Conference on Current Trends in Theory and Practice of Computer Science
A Guide-and-Observe Hyper-Heuristic Approach to the Eternity II Puzzle

Journal of Mathematical Modelling and Algorithms
On the hardness of solving edge matching puzzles as SAT or CSP problems

Constraints
A Guide-and-Observe Hyper-Heuristic Approach to the Eternity II Puzzle

Journal of Mathematical Modelling and Algorithms
Automated generation of computationally hard feature models using evolutionary algorithms

Expert Systems with Applications: An International Journal

Quantified Score

Hi-index	0.00

Visualization

Abstract

Recently, edge matching puzzles, an NP-complete problem, have received, thanks to money-prized contests, considerable attention from wide audiences. This paper studies edge matching puzzles focusing on providing generation models of problem instances of variable hardness and on its resolution through the application of SAT and CSP techniques. From the generation side, we also identify the phase transition phenomena for each model. As solving methods, we employ both; SAT solvers through the translation to a SAT formula, and two ad-hoc CSP solvers we have developed, with different levels of consistency, employing generic and specialized heuristics. Finally, we conducted an extensive experimental investigation to identify the hardest generation models and the best performing solving techniques.