利用极小宽度求解广义凸图问题

IF 1.1 3区 计算机科学 Q1 BUSINESS, FINANCE Journal of Computer and System Sciences Pub Date : 2023-11-07 DOI:10.1016/j.jcss.2023.103493
Flavia Bonomo-Braberman , Nick Brettell , Andrea Munaro , Daniël Paulusma
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引用次数: 0

摘要

如果存在一个图H∈H且V(H)=A,使得每个B∈B在A中的邻居都能引出H的连通子图H,那么对于某些图族H,一个二部图G=(A,B,E)是H-凸图,当H是路径集时,H-凸图的许多np完全问题都是多项式时间可解的。潜在的原因是类具有有界的mim-width。我们将这个结果推广到H-凸图的族中,其中H是环的集合,或者H是具有有界最大度和有界顶点数至少为3的树的集合。因此,我们通过一个一般和简短的证明来加强许多已知的结果。我们还证明了H-凸图的最小宽度是无界的,如果H是具有任意大的最大度的树的集合或任意多的顶点的次数至少为3。
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Solving problems on generalized convex graphs via mim-width

A bipartite graph G=(A,B,E) is H-convex for some family of graphs H if there exists a graph HH with V(H)=A such that the neighbours in A of each bB induce a connected subgraph of H. Many NP-complete problems are polynomial-time solvable for H-convex graphs when H is the set of paths. The underlying reason is that the class has bounded mim-width. We extend this result to families of H-convex graphs where H is the set of cycles, or H is the set of trees with bounded maximum degree and a bounded number of vertices of degree at least 3. As a consequence, we strengthen many known results via one general and short proof. We also show that the mim-width of H-convex graphs is unbounded if H is the set of trees with arbitrarily large maximum degree or an arbitrarily large number of vertices of degree at least 3.

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来源期刊
Journal of Computer and System Sciences
Journal of Computer and System Sciences 工程技术-计算机:理论方法
CiteScore
3.70
自引率
0.00%
发文量
58
审稿时长
68 days
期刊介绍: The Journal of Computer and System Sciences publishes original research papers in computer science and related subjects in system science, with attention to the relevant mathematical theory. Applications-oriented papers may also be accepted and they are expected to contain deep analytic evaluation of the proposed solutions. Research areas include traditional subjects such as: • Theory of algorithms and computability • Formal languages • Automata theory Contemporary subjects such as: • Complexity theory • Algorithmic Complexity • Parallel & distributed computing • Computer networks • Neural networks • Computational learning theory • Database theory & practice • Computer modeling of complex systems • Security and Privacy.
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