A Warm Restart Strategy for Solving Sudoku by Sparse Optimization Methods
Optimization and Control
2018-03-16 v3 Distributed, Parallel, and Cluster Computing
Abstract
This paper is concerned with the popular Sudoku problem. We proposed a warm restart strategy for solving Sudoku puzzles, based on the sparse optimization technique. Furthermore, we defined a new difficulty level for Sudoku puzzles. The efficiency of the proposed method is tested using a dataset of Sudoku puzzles, and the numerical results show that the accurate recovery rate can be enhanced from 84%+ to 99%+ using the L1 sparse optimization method.
Cite
@article{arxiv.1507.05995,
title = {A Warm Restart Strategy for Solving Sudoku by Sparse Optimization Methods},
author = {Yuchao Tang and Zhenggang Wu and Chuanxi Zhu},
journal= {arXiv preprint arXiv:1507.05995},
year = {2018}
}
Comments
11 pages,5 figures