Uniformly resolvable decompositions of λ-fold complete multipartite graph into 4-star

Let ?Ku [1] be the ?-fold complete multipartite graph with u parts of size 1. A (K1,n, ?)-resolvable group divisible design (RGDD) of type gu is a K1,n-decomposition of the graph ?Ku [g] into parallel classes each of which is a partition of the vertex set. A (K1,n, ?)-frame of type gu is a K1,n-decomposition of ?Ku [g] into partial parallel classes each of which is a partition of the vertex set except for those vertices in one of the u parts. In this paper, we completely solve the existence of a (K1,4, ?)-frame and a (K1,4, ?)-RGDD of type gu for any admissible parameters g, u and ?.

Authors

Institutions

Publication Details

Journal
Filomat
Published
2025-01-01
DOI
https://doi.org/10.2298/fil2505717w
Primary Topic
graph theory and CDMA systems
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Uniformly resolvable decompositions of λ-fold complete multipartite graph into 4-star

Wang Li
Filomat
graph theory and CDMA systems
article

Uniformly resolvable decompositions of λ-fold complete multipartite graph into 4-star

Wang Li
article en

Abstract

Let ?Ku [1] be the ?-fold complete multipartite graph with u parts of size 1. A (K1,n, ?)-resolvable group divisible design (RGDD) of type gu is a K1,n-decomposition of the graph ?Ku [g] into parallel classes each of which is a partition of the vertex set. A (K1,n, ?)-frame of type gu is a K1,n-decomposition of ?Ku [g] into partial parallel classes each of which is a partition of the vertex set except for those vertices in one of the u parts. In this paper, we completely solve the existence of a (K1,4, ?)-frame and a (K1,4, ?)-RGDD of type gu for any admissible parameters g, u and ?.

FilomatVol. 39(5)
Xidian University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 83%
graph theory and CDMA systems
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.