On decreasing the orders of $$(k,g)$$ -graphs

IF 0.9 4区 数学 Q4 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Geoffrey Exoo, Robert Jajcay, Tom Raiman
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引用次数: 0

Abstract

A \((k,g)\)-graph is a k-regular graph of girth \(g\). Given \(k\ge 2\) and \(g\ge 3\), \((k,g)\)-graphs of infinitely many orders are known to exist and the problem of finding a (kg)-graph of the smallest possible order is known as the Cage Problem. The aim of our paper is to develop systematic (programmable) ways for lowering the orders of existing \((k,g)\)-graphs, while preserving their regularity and girth. Such methods, in analogy with the previously used excision, may have the potential for constructing smaller (kg)-graphs from current smallest examples—record holders—some of which have not been improved in years. In addition, we consider constructions that preserve the regularity, the girth and the order of the considered graphs, but alter the graphs enough to possibly make them suitable for the application of our order decreasing methods. We include a detailed discussion of several specific parameter cases for which several non-isomorphic smallest examples are known to exist, and address the question of the distance between these non-isomorphic examples based on the number of changes required to move from one example to another.

Abstract Image

关于$$(k,g)$$ -图的降阶问题
\((k,g)\) -图是周长为\(g\)的k正则图。给定\(k\ge 2\)和\(g\ge 3\),已知存在无穷多阶的\((k,g)\) -图,并且找到可能最小阶的(k, g)-图的问题称为Cage问题。我们论文的目的是开发系统的(可编程的)方法来降低现有\((k,g)\) -图的阶数,同时保持它们的正则性和周长。这种方法,类似于以前使用的删除,可能有潜力从当前最小的记录保持者中构建更小的(k, g)-图,其中一些多年来没有得到改进。此外,我们还考虑保留所考虑图的正则性、周长和顺序的结构,但对图的改变足以使它们适合于我们的降阶方法的应用。我们详细讨论了几个特定的参数情况,其中已知存在几个非同构最小示例,并根据从一个示例移动到另一个示例所需的变化数量来解决这些非同构示例之间的距离问题。
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来源期刊
Journal of Combinatorial Optimization
Journal of Combinatorial Optimization 数学-计算机:跨学科应用
CiteScore
2.00
自引率
10.00%
发文量
83
审稿时长
6 months
期刊介绍: The objective of Journal of Combinatorial Optimization is to advance and promote the theory and applications of combinatorial optimization, which is an area of research at the intersection of applied mathematics, computer science, and operations research and which overlaps with many other areas such as computation complexity, computational biology, VLSI design, communication networks, and management science. It includes complexity analysis and algorithm design for combinatorial optimization problems, numerical experiments and problem discovery with applications in science and engineering. The Journal of Combinatorial Optimization publishes refereed papers dealing with all theoretical, computational and applied aspects of combinatorial optimization. It also publishes reviews of appropriate books and special issues of journals.
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