Graph realization of distance sets

IF 0.9 4区 计算机科学 Q3 COMPUTER SCIENCE, THEORY & METHODS Theoretical Computer Science Pub Date : 2024-08-30 DOI:10.1016/j.tcs.2024.114810
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引用次数: 0

Abstract

The Distance Realization problem is defined as follows. Given an n×n matrix D of nonnegative integers, interpreted as inter-vertex distances, find an n-vertex weighted or unweighted graph G realizing D, i.e., whose inter-vertex distances satisfy distG(i,j)=Di,j for every 1i<jn, or decide that no such realizing graph exists. The problem was studied for general weighted and unweighted graphs, as well as for cases where the realizing graph is restricted to a specific family of graphs (e.g., trees or bipartite graphs). An extension of Distance Realization that was studied in the past is where each entry in the matrix D may contain a range of consecutive permissible values. We refer to this extension as Range Distance Realization (or Range-DR). Restricting each range to at most k values yields the problem k-Range Distance Realization (or k-Range-DR). The current paper introduces a new extension of Distance Realization, in which each entry Di,j of the matrix may contain an arbitrary set of acceptable values for the distance between i and j, for every 1i<jn. We refer to this extension as Set Distance Realization (Set-DR), and to the restricted problem where each entry may contain at most k values as k-Set Distance Realization (or k-Set-DR).

We first show that 2-Range-DR is NP-hard for unweighted graphs (implying the same for 2-Set-DR). Next we prove that 2-Set-DR is NP-hard for unweighted and weighted trees.

Finally, we explore Set-DR where the realization is restricted to the families of stars, paths, cycles, or caterpillars. For the weighted case, our positive results are that there exist polynomial time algorithms for the 2-Set-DR problem on stars, paths and cycles, and for the 1-Set-DR problem on caterpillars. On the hardness side, we prove that 6-Set-DR is NP-hard for stars and 5-Set-DR is NP-hard for paths, cycles and caterpillars. For the unweighted case, our results are the same, except for the case of unweighted stars, for which k-Set-DR is polynomially solvable for any k.

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距离集的图形实现
距离实现问题定义如下。给定一个由非负整数组成的 n×n 矩阵 D(解释为顶点间距离),找出一个实现 D 的 n 个顶点的加权或非加权图 G,即对于每 1≤i<j≤n 来说,其顶点间距离满足 distG(i,j)=Di,j ,或者判定不存在这样的实现图。我们研究了一般加权图和非加权图,以及实现图仅限于特定图族(如树或二叉图)的情况。过去研究过的距离实现的一个扩展是矩阵 D 中的每个条目可能包含一个连续的允许值范围。我们将这种扩展称为范围距离变现(或 Range-DR)。将每个范围限制为最多 k 个值,就产生了 k 范围距离实现(或 k-Range-DR)问题。本文介绍了距离实现的新扩展,其中矩阵的每个条目 Di,j 可以包含 i 和 j 之间距离的任意可接受值集,每 1≤i<j≤n 个值。我们把这种扩展称为集合距离实现(Set-DR),把每个条目最多可以包含 k 个值的受限问题称为 k 集合距离实现(或 k-Set-DR)。我们首先证明 2-Range-DR 对于无权重图来说是 NP-hard(意味着 2-Set-DR 也是 NP-hard)。接下来,我们证明了 2-Set-DR 对于无权重树和有权重树来说是 NP-hard。最后,我们探讨了 Set-DR,在这种情况下,实现被限制为星族、路径族、循环族或毛毛虫族。对于有权重的情况,我们的积极结果是,对于星、路径和循环的 2-Set-DR 问题,以及对于毛毛虫的 1-Set-DR 问题,都存在多项式时间算法。在难度方面,我们证明了 6-Set-DR 对于恒星是 NP-hard,5-Set-DR 对于路径、循环和毛毛虫是 NP-hard。对于无权重的情况,我们的结果是一样的,除了无权重星形的情况,对于任意 k,k-Set-DR 都是多项式可解的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Theoretical Computer Science
Theoretical Computer Science 工程技术-计算机:理论方法
CiteScore
2.60
自引率
18.20%
发文量
471
审稿时长
12.6 months
期刊介绍: Theoretical Computer Science is mathematical and abstract in spirit, but it derives its motivation from practical and everyday computation. Its aim is to understand the nature of computation and, as a consequence of this understanding, provide more efficient methodologies. All papers introducing or studying mathematical, logic and formal concepts and methods are welcome, provided that their motivation is clearly drawn from the field of computing.
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