更严格的最小广播时间限制

IF 0.9 4区 数学 Q3 MATHEMATICS, APPLIED
Dag Haugland
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引用次数: 0

摘要

给定一个连通图及其称为信息源的顶点子集,最小广播时间问题要求将信息从信息源传送到图中所有其他顶点所需的最短时间。信息交换只能在邻居之间进行,每个顶点一次最多只能向一个邻居传送信息。从早期的复杂性理论著作开始,人们就知道这个问题是 NP-困难的。本文对理解最小广播时间问题有三方面的贡献。通过考虑源和其他顶点之间的最短距离,得出了广播时间的新下限。在几类图的单源实例中给出了该下限的分析表达式。接下来研究了计算上界的快速程序,包括可行解的构建和现有解的改进。最后,以问题的新稳定集解释为重点,研究了整数编程公式,并给出了相关的面定义有效不等式,以激发理论兴趣。新方法的计算性能在应用于标准基准实例和比前人研究的实例更大的实例的数值实验中进行了评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Tighter bounds on the minimum broadcast time

Given a connected graph and a subset of its vertices referred to as the sources, the minimum broadcast time problem asks for the shortest time necessary for communicating a message from the sources to all other vertices in the graph. Information exchange is possible only between neighbors, and each vertex can transmit the message to at most one neighbor at a time. Since early works on complexity theory, the problem has been known to be NP-hard. Contributions from the current text to the understanding of the minimum broadcast time problem are threefold. Through considerations of the shortest distances between sources and other vertices, a new lower bound on the broadcast time is derived. Analytical expressions of this bound are given in the single source instances of several graph classes. Fast procedures for computing upper bounds are studied next, including both the construction of feasible solutions, and the improvement of existing ones. Finally, with a focus on a new stable-set interpretation of the problem, integer programming formulations are studied, and for their theoretical interest, associated facet-defining valid inequalities are given. The computational performance of the novel methodology is evaluated in numerical experiments applied to standard benchmark instances and to instances larger than those studied in preceding recent works.

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来源期刊
Discrete Optimization
Discrete Optimization 管理科学-应用数学
CiteScore
2.10
自引率
9.10%
发文量
30
审稿时长
>12 weeks
期刊介绍: Discrete Optimization publishes research papers on the mathematical, computational and applied aspects of all areas of integer programming and combinatorial optimization. In addition to reports on mathematical results pertinent to discrete optimization, the journal welcomes submissions on algorithmic developments, computational experiments, and novel applications (in particular, large-scale and real-time applications). The journal also publishes clearly labelled surveys, reviews, short notes, and open problems. Manuscripts submitted for possible publication to Discrete Optimization should report on original research, should not have been previously published, and should not be under consideration for publication by any other journal.
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