Fractional Perfect Matching Research Articles

Signless Laplacian spectral radius and fractional matchings in graphs

A fractional matching of a graph G is a function f giving each edge a number in [0,1] so that ∑e∈Γ(v)f(e)≤1 for each vertex v∈V(G), where Γ(v) is the set of edges incident to v. The fractional matching number of G, written α∗′(G), is the maximum value of ∑e∈E(G)f(e) over all fractional matchings. In this paper, we investigate the relations between the fractional matching number and the signless Laplacian spectral radius of a graph. Moreover, we give some sufficient conditions for the existence of a fractional perfect matching of a graph in terms of the signless Laplacian spectral radius of the graph and its complement.

Fractional Matching Preclusion for Data Center Networks

An edge subset [Formula: see text] of [Formula: see text] is a fractional matching preclusion set (FMP set for short) if [Formula: see text] has no fractional perfect matchings. The fractional matching preclusion number (FMP number for short) of [Formula: see text], denoted by [Formula: see text], is the minimum size of FMP sets of [Formula: see text]. A set [Formula: see text] of edges and vertices of [Formula: see text] is a fractional strong matching preclusion set (FSMP set for short) if [Formula: see text] has no fractional perfect matchings. The fractional strong matching preclusion number (FSMP number for short) of [Formula: see text], denoted by [Formula: see text], is the minimum size of FSMP sets of [Formula: see text]. Data center networks have been proposed for data centers as a server-centric interconnection network structure, which can support millions of servers with high network capacity by only using commodity switches. In this paper, we obtain the FMP number and the FSMP number for data center networks [Formula: see text], and show that [Formula: see text] for [Formula: see text], [Formula: see text] and [Formula: see text] for [Formula: see text], [Formula: see text]. In addition, all the optimal fractional strong matching preclusion sets of these graphs are categorized.

Fractional Matching Preclusion for Möbius Cubes

Let F be an edge subset and F′ a subset of vertices and edges of a graph G. If G − F and G − F′ have no fractional perfect matchings, then F is a fractional matching preclusion (FMP) set and F′ is a fractional strong matching preclusion (FSMP) set of G. The FMP (FSMP) number of G is the minimum size of FMP (FSMP) sets of G. In this paper, we study the fractional matching preclusion number and the fractional strong matching preclusion number for the Möbius cube MQn. In adddition, all the optimal fractional strong preclusion sets of these graphs are categorized.

Fractional Matching Preclusion for Restricted Hypercube-Like Graphs

The restricted hypercube-like graphs, variants of the hypercube, were proposed as desired interconnection networks of parallel systems. The matching preclusion number of a graph is the minimum number of edges whose deletion results in the graph with neither perfect matchings nor almost perfect matchings. The fractional perfect matching preclusion and fractional strong perfect matching preclusion are generalizations of the matching preclusion. In this paper, we obtain fractional matching preclusion number and fractional strong matching preclusion number of restricted hypercube-like graphs, which extend some known results.

Fractional matching preclusion for arrangement graphs

The matching preclusion number of a graph is the minimum number of edges whose deletion results in a graph that has neither perfect matchings nor almost perfect matchings. As a generalization, Liu and Liu (2017) recently introduced the concept of fractional matching preclusion number. The fractional matching preclusion number (FMP number) of G is the minimum number of edges whose deletion leaves the resulting graph without a fractional perfect matching. The fractional strong matching preclusion number (FSMP number) of G is the minimum number of vertices and edges whose deletion leaves the resulting graph without a fractional perfect matching. In this paper, we obtain the FMP number and the FSMP number for arrangement graphs. In addition, all the optimal fractional strong matching preclusion sets of these graphs are categorized.

Fractional matching preclusion for radix triangular mesh

The matching preclusion number of a graph is the minimum number of edges whose deletion results in a graph that has neither perfect matchings nor almost perfect matchings. As a generalization, Liu and Liu recently introduced the concept of fractional matching preclusion number. The fractional matching preclusion number (FMP number) of [Formula: see text], denoted by [Formula: see text], is the minimum number of edges whose deletion leaves the resulting graph without a fractional perfect matching. The fractional strong matching preclusion number (FSMP number) of [Formula: see text], denoted by [Formula: see text], is the minimum number of vertices and edges whose deletion leaves the resulting graph without a fractional perfect matching. In this paper, we study the fractional matching preclusion number and the fractional strong matching preclusion number for the radix triangular mesh [Formula: see text], and all the optimal fractional matching preclusion sets and fractional strong matching preclusion sets of these graphs are categorized.

Fractional matching preclusion of the restricted HL-graphs

The fractional matching preclusion number of a graph is the minimum number of edges whose deletion results in a graph that has no fractional perfect matchings, and the fractional strong matching preclusion number of a graph is the minimum number of edges and/or vertices whose deletion leaves a resulting graph with no fractional perfect matchings. In this paper, we determine these two numbers for the restricted HL-graphs.

Fractional Matching Preclusion for (n,k)-Star Graphs

The matching preclusion number of a graph is the minimum number of edges whose deletion results in a graph that has neither perfect matchings nor almost perfect matchings. As a generalization, Liu and Liu introduced the concept of fractional matching preclusion number in 2017. The Fractional Matching Preclusion Number (FMP number) of G is the minimum number of edges whose deletion leaves the resulting graph without a fractional perfect matching. The Fractional Strong Matching Preclusion Number (FSMP number) of G is the minimum number of vertices and/or edges whose deletion leaves the resulting graph without a fractional perfect matching. In this paper, we obtain the FMP number and the FSMP number for (n, k)-star graphs. In addition, all the optimal fractional strong matching preclusion sets of these graphs are categorized.

Fractional matching number and eigenvalues of a graph

ABSTRACTA fractional matching of a graph G is a function f giving each edge a number in so that for each , where is the set of edges incident to v. The fractional matching number of G, written , is the maximum of over all fractional matchings. In this paper, we study the connections between the fractional matching number and the Laplacian spectral radius of a graph. We also give some sufficient spectral conditions for the existence of a fractional perfect matching.

Fractional matching preclusion of graphs

Let F be an edge subset and \(F^{\prime }\) a subset of edges and vertices of a graph G. If \(G-F\) and \(G-F^{\prime }\) have no fractional perfect matchings, then F is a fractional matching preclusion (FMP) set and \(F^{\prime }\) is a fractional strong MP (FSMP) set of G. The FMP (FSMP) number of G is the minimum size of FMP (FSMP) sets of G. In this paper, the FMP number and the FSMP number of Petersen graph, complete graphs and twisted cubes are obtained, respectively.

Some results on binding number and fractional perfect matching

The relationships between binding number and fractional edge (vertex)-deletability or fractional k-extendability of graphs are studied. Furthermore, we show that the result about fractional vertex-deletability are best possible.

Some results on fractionaln-factor-critical graphs

A simple graphG is said to be fractionaln-factor-critical if after deleting anyn vertices the remaining subgraph still has a fractional perfect matching. For fractionaln-factor-criticality, in this paper, one necessary and sufficient condition, and three sufficient conditions related to maximum matching, complete closure are given.

Perfect matchings in uniform hypergraphs with large minimum degree

A perfect matching in a k -uniform hypergraph on n vertices, n divisible by k , is a set of n / k disjoint edges. In this paper we give a sufficient condition for the existence of a perfect matching in terms of a variant of the minimum degree. We prove that for every k ≥ 3 and sufficiently large n , a perfect matching exists in every n -vertex k -uniform hypergraph in which each set of k − 1 vertices is contained in n / 2 + Ω ( log n ) edges. Owing to a construction in [D. Kühn, D. Osthus, Matchings in hypergraphs of large minimum degree, J. Graph Theory 51 (1) (2006) 269–280], this is nearly optimal. For almost perfect and fractional perfect matchings we show that analogous thresholds are close to n / k rather than n / 2 .

Random Lifts Of Graphs: Perfect Matchings

We study random lifts of a graph G as defined in [1]. We prove a 0-1 law which states that for every graph G either almost every lift of G has a perfect matching, or almost none of its lifts has a perfect matching. We provide a precise description of this dichotomy. Roughly speaking, the a.s. existence of a perfect matching in the lift depends on the existence of a fractional perfect matching in G. The precise statement appears in Theorem 1.

A new rounding procedure for the assignment problem with applications to dense graph arrangement problems

We present a randomized procedure for rounding fractional perfect matchings to (integral) matchings. If the original fractional matching satisfies any linear inequality, then with high probability, the new matching satisfies that linear inequality in an approximate sense. This extends the well-known LP rounding procedure of Raghavan and Thompson, which is usually used to round fractional solutions of linear programs.¶We use our rounding procedure to design an additive approximation algorithm to the Quadratic Assignment Problem. The approximation error of the algorithm is en 2 and it runs in n O (log n /e2) time.¶We also describe Polynomial Time Approximation Schemes (PTASs) for dense subcases of many well-known NP-hard arrangement problems, including MINIMUM LINEAR ARRANGEMENT, MINIMUM CUT LINEAR ARRANGEMENT, MAXIMUM ACYCLIC SUBGRAPH, and BETWEENNESS.