给出多少条线索?最小数独线索问题的双层表述

IF 0.8 4区 管理学 Q4 OPERATIONS RESEARCH & MANAGEMENT SCIENCE
Gennesaret Tjusila , Mathieu Besançon , Mark Turner , Thorsten Koch
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引用次数: 0

摘要

有研究表明,任何一道9乘9的数独谜题必须包含至少17条线索才有唯一解。本文研究了一个更为具体的问题:给定一个特定的完整数独网格,那么以给定网格为唯一解的谜题中线索的最少数量是多少?我们称这个问题为最小数独线索问题(MSCP)。我们将 MSCP 表述为二元双级线性程序,提出了一类全局有效的不等式,并对 50 个 9×9 数独网格的 MSCP 实例进行了计算研究。我们使用通用的双级求解器,求解了 95% 的实例,并表明求解过程得益于添加了适量的不等式。最后,我们将所提出的模型扩展到其他组合问题,在这些问题中,解的唯一性非常重要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
How many clues to give? A bilevel formulation for the minimum Sudoku clue problem

It has been shown that any 9 by 9 Sudoku puzzle must contain at least 17 clues to have a unique solution. This paper investigates the more specific question: given a particular completed Sudoku grid, what is the minimum number of clues in any puzzle whose unique solution is the given grid? We call this problem the Minimum Sudoku Clue Problem (MSCP). We formulate MSCP as a binary bilevel linear program, present a class of globally valid inequalities, and provide a computational study on 50 MSCP instances of 9 by 9 Sudoku grids. Using a general bilevel solver, we solve 95% of instances to optimality, and show that the solution process benefits from the addition of a moderate amount of inequalities. Finally, we extend the proposed model to other combinatorial problems in which uniqueness of the solution is of interest.

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来源期刊
Operations Research Letters
Operations Research Letters 管理科学-运筹学与管理科学
CiteScore
2.10
自引率
9.10%
发文量
111
审稿时长
83 days
期刊介绍: Operations Research Letters is committed to the rapid review and fast publication of short articles on all aspects of operations research and analytics. Apart from a limitation to eight journal pages, quality, originality, relevance and clarity are the only criteria for selecting the papers to be published. ORL covers the broad field of optimization, stochastic models and game theory. Specific areas of interest include networks, routing, location, queueing, scheduling, inventory, reliability, and financial engineering. We wish to explore interfaces with other fields such as life sciences and health care, artificial intelligence and machine learning, energy distribution, and computational social sciences and humanities. Our traditional strength is in methodology, including theory, modelling, algorithms and computational studies. We also welcome novel applications and concise literature reviews.
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