EconPapers    
Economics at your fingertips  
 

Global Offensive Alliances and Groupies in Heterogeneous Random Graphs

Yilun Shang ()
Additional contact information
Yilun Shang: Northumbria University

Methodology and Computing in Applied Probability, 2025, vol. 27, issue 1, 1-14

Abstract: Abstract A vertex subset S of a graph G is a global offensive alliance if every non-member v of S has at least as many neighbors inside S as outside S in the closed neighborhood of v. The global offensive alliance number $$\gamma _G$$ γ G is the cardinality of a minimal global offensive alliance. A vertex is a groupie if its degree is not less than the mean of the degrees of its neighbors. The number of groupies in G is denoted by $$\eta _G$$ η G . In this paper, we study these two sort of orthogonal concepts over a heterogenous random graph G obtained by including each edge e from a complete graph $$K_n$$ K n of order n with an individual probability $$p_n(e)$$ p n ( e ) independently. For a complete t-ary tree T with height 2, $$\gamma _T=\eta _T=t$$ γ T = η T = t . In the random graph setting, it is found that $$\gamma _G\asymp \eta _G\asymp n/2$$ γ G ≍ η G ≍ n / 2 under some neighborhood density conditions of the edge probabilities, where $$a_n\asymp b_n$$ a n ≍ b n means $$a_n/b_n\rightarrow 1$$ a n / b n → 1 as $$n\rightarrow \infty $$ n → ∞ .

Keywords: Global offensive alliance; Random graph; Groupie; Neighbor; Probabilistic combinatorics; 05C80; 05C69; 60C05 (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s11009-025-10151-z Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:metcap:v:27:y:2025:i:1:d:10.1007_s11009-025-10151-z

Ordering information: This journal article can be ordered from
https://www.springer.com/journal/11009

DOI: 10.1007/s11009-025-10151-z

Access Statistics for this article

Methodology and Computing in Applied Probability is currently edited by Joseph Glaz

More articles in Methodology and Computing in Applied Probability from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2025-04-02
Handle: RePEc:spr:metcap:v:27:y:2025:i:1:d:10.1007_s11009-025-10151-z