Measuring Sudoku Difficulty: Formulation, Propagation and Uniqueness Certification
Aled Williams
Abstract
Finding a Sudoku completion and proving that the completion is unique are different computational tasks. Despite both concerning the same puzzle, their computational effort need not be closely related. In this paper, we investigate how this relationship depends on the mathematical formulation, solver and measure of computational effort. Using 32,000 uniquely solvable puzzles and 64 harder instances, we compare integer programming formulations and CP-SAT. Further, we prove that the raw natural formulation has an extremely weak linear programming relaxation, even with uniqueness exclusions. Computational experiments show that the relationship between completion and certification effort depends on the formulation, puzzle population, solver and effort measure, rather than on the puzzle alone.
Create a lesson
Related papers
Lower- and upper-C2 integrands: a structured class of functions for stochastic nonconvex optimization
Felipe Atenas, Alejandro Jofré, Pedro Pérez-Aros et al.
Linear-quadratic mean field games with Volterra dynamics
Niccolò Fontana, Mattia Martini, Huyên Pham
No closed-form formula for Stiefel geodesics
Rongbiao Thomas Wang, Lek-Heng Lim
Constructing Data-Driven Budgeted Uncertainty Sets for Robust Optimization
Jamie Fairbrother, Marc Goerigk, Qiongyan Zeng
DREAM: Delay-Resistant Acceleration with Momentum
Mert Gürbüzbalaban, M. Hamza Rafi, Necdet Serhat Aybat et al.
A switching proximal gradient method for constrained difference-of-convex optimization problems
Yuncheng Liu, Chuangliang Zhang, Bo Yang