Congruency-Constrained TU Problems Beyond the Bimodular Case

IF 1.9 3区 数学 Q2 MATHEMATICS, APPLIED
Martin Nägele, Richard Santiago, Rico Zenklusen
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引用次数: 0

Abstract

A long-standing open question in integer programming is whether integer programs with constraint matrices with bounded subdeterminants are efficiently solvable. An important special case thereof are congruency-constrained integer programs [Formula: see text] with a totally unimodular constraint matrix T. Such problems are shown to be polynomial-time solvable for m = 2, which led to an efficient algorithm for integer programs with bimodular constraint matrices, that is, full-rank matrices whose n × n subdeterminants are bounded by two in absolute value. Whereas these advances heavily rely on existing results on well-known combinatorial problems with parity constraints, new approaches are needed beyond the bimodular case, that is, for m > 2. We make first progress in this direction through several new techniques. In particular, we show how to efficiently decide feasibility of congruency-constrained integer programs with a totally unimodular constraint matrix for m = 3 using a randomized algorithm. Furthermore, for general m, our techniques also allow for identifying flat directions of infeasible problems and deducing bounds on the proximity between solutions of the problem and its relaxation. Funding: This project received funding from the Swiss National Science Foundation [Grants 200021_184622 and P500PT_206742], the European Research Council under the European Union’s Horizon 2020 research and innovation program [Grant 817750], and the Deutsche Forschungsgemeinschaft (German Research Foundation) under Germany’s Excellence Strategy–GZ 2047/1 [Grant 390685813].
双模情况下的同余约束TU问题
整数规划中一个长期存在的开放性问题是具有有界子行列式的约束矩阵的整数规划是否有效可解。其中一个重要的特例是具有完全单模约束矩阵t的同余约束整数规划[公式:见文],这类问题对于m = 2是多项式时间可解的,从而得到了具有双模约束矩阵的整数规划的有效算法,即n × n个子行列式的绝对值以2为界的全秩矩阵。尽管这些进展严重依赖于已知的具有宇称约束的组合问题的现有结果,但需要新的方法来超越双模情况,即m >2. 我们通过几种新技术在这个方向上取得了初步进展。特别地,我们展示了如何使用随机算法有效地确定具有完全单模约束矩阵的同余约束整数规划的可行性。此外,对于一般的m,我们的技术还允许识别不可行问题的平面方向,并推导出问题的解与其松弛之间的接近界。本项目获得了瑞士国家科学基金会[赠款200021_184622和P500PT_206742],欧盟地平线2020研究与创新计划[赠款817750]欧洲研究理事会,德国卓越战略- gz 2047/1[赠款390685813]德国研究基金会的资助。
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来源期刊
Mathematics of Operations Research
Mathematics of Operations Research 管理科学-应用数学
CiteScore
3.40
自引率
5.90%
发文量
178
审稿时长
15.0 months
期刊介绍: Mathematics of Operations Research is an international journal of the Institute for Operations Research and the Management Sciences (INFORMS). The journal invites articles concerned with the mathematical and computational foundations in the areas of continuous, discrete, and stochastic optimization; mathematical programming; dynamic programming; stochastic processes; stochastic models; simulation methodology; control and adaptation; networks; game theory; and decision theory. Also sought are contributions to learning theory and machine learning that have special relevance to decision making, operations research, and management science. The emphasis is on originality, quality, and importance; correctness alone is not sufficient. Significant developments in operations research and management science not having substantial mathematical interest should be directed to other journals such as Management Science or Operations Research.
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