r-一致D-超图的最大边数
The Maximum Number of Hyperedges of An r-Uniform D-Hypergraph
DOI: 10.12677/AAM.2020.91013, PDF,   
作者: 朱义坪, 熊亚萍:山东师范大学数学与统计学院,山东 济南
关键词: 混合超图r-一致D-超图最大超边数Mixed Hypergraph r-Uniform D-Hypergraph The Maximum Number of Hyperedges
摘要:

混合超图H=(X,C,D)是一个三元组,其中X为H的顶点集。C为X的子集族,记作C-边。D为X的子集族,记作D-边。C=∅的混合超图称为D-超图,D=∅的混合超图称为C-超图。H=(X,C,D)是一混合超图,r是不小于2的正整数,若满足对任意的C-超边和D-超边,都有|C|=r|D|=r,则称混合超图H为r-一致混合超图。特别地,若又有C=∅,则称混合超图H为r-一致D超图。在本文中,我们解决当χ(H)=k时,r-一致D-超图H的最大边数这一问题。

Abstract: A mixed hypergraph on a finite set X is a triple H=(X,C,D), where C and D are families of subset of X. The member of C is called C-edge and the member of D is called D-edge. A mixed hypergraph is called C-hypergraph when D=∅, a mixed hypergraph is called D-hypergraph when C=∅. Let H=(X,C,D) be a mixed hypergraph, r is a positive integer not less than 2. For an arbitrary C-edge and D-edge, if we have |C|=r|D|=r, then the mixed hypergraph H is called r-uniform mixed hypergraph. In particular, if , the mixed hypergraph H is called r-uniform mixed D-hypergraph. In this paper, we solve the problem about the maximum number of hyperedges of an r-uniform D-hypergraph when χ(H)=k.
文章引用:朱义坪, 熊亚萍. r-一致D-超图的最大边数[J]. 应用数学进展, 2020, 9(1): 105-108. https://doi.org/10.12677/AAM.2020.91013

参考文献

[1] Voloshin, V.I. (2002) Coloring Mixed Hypergraphs: Theory, Algorithms and Applications, AMS, Providence.
[2] Bujt´as, C. and Tuza, Z. (2008) Uniform Mixed Hypergraphs: The Possible Numbers of Colors. Graphs and Combinatorics, 24, 1-12.
[Google Scholar] [CrossRef
[3] Diao, K., Zhao, P. and Wang, K. (2014) The Smallest One-Realization of a Given Set III. Graphs and Combinatorics, 30, 875-885.
[Google Scholar] [CrossRef
[4] Voloshin, V.I. (1992) On the Upper Chromatic Number of a Hypergraph. Scientific Research Conference of the Moldova State University, Theses of Resports, Kishinev, Vol. 1, 42.
[5] Cai, J., Xiong, Y. and Yang, D. (2020) A Note on the Maximum Number of Hyperedge so f C-Hypergraph. Submitted for Publication.
[6] Alon, N. and Spencer, J.H. (2008) The Probablistic Method. 3rd Edition, John Wiley and Sons, New York.