The Complexity of All $(g,f)$-Factor Problem
Hongliang Lu

TL;DR
This paper proves that determining whether a graph has all $(g,f)$-factors is NP-hard, answering a longstanding open question and showing the problem's computational complexity.
Contribution
It establishes the NP-hardness of testing for all $(g,f)$-factors in graphs, providing a negative answer to Niessen's 1998 open problem.
Findings
Proves the problem is NP-hard.
Answers Niessen's open question negatively.
Highlights computational difficulty of all $(g,f)$-factor problem.
Abstract
Let be a graph with vertex set and let be two functions such that . We say that has all -factors if has an -factor for every such that for every and . Two decades ago, Niessen derived from Tutte's -factor theorem a similar characterization for the property of graphs having all -factors and asked whether there is a polynomial time algorithm for testing whether a graph has all -factors (A characterization of graphs having all -Factors, \emph{J. Combin. Theory, Ser. B}, \textbf{72} (1998), 152--156). In this paper, we show that it is NP-hard to determine whether a graph has all -factors, which gives a negative answer to the question of Niessen.
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Taxonomy
TopicsAdvanced Graph Theory Research · Limits and Structures in Graph Theory · Complexity and Algorithms in Graphs
Note
On the Complexity of All -Factors Problem
Hongliang Lu, Wei Wang and Yaolin Jiang
School of Mathematics and Statistics
Xi’an Jiaotong University
Xi’an, Shaanxi 710049, China
Abstract
Let be a graph with vertex set and let be two functions such that . We say that has all -factors if has an -factor for every such that for every and . Two decades ago, Niessen derived from Tutte’s -factor theorem a similar characterization for the property of graphs having all -factors and asked whether there is a polynomial time algorithm for testing whether a graph has all -factors (A characterization of graphs having all -Factors, J. Combin. Theory, Ser. B, 72 (1998), 152–156). In this paper, we show that it is NP-hard to determine whether a graph has all -factors, which gives a negative answer to the question of Niessen.
1 Introduction
We consider finite simple graphs, i.e., undirected graph without loops or multiple edges. Let be a graph with vertex set and edge set .
Let denote the number of components of a graph . A graph is -tough if for every subset of the vertex set with . The toughness of , denoted , is the maximum value of for which is -tough (taking for all ). We say that a graph is almost -tough if for any ,
[TABLE]
Let be a set function. An -factor is a spanning subgraph such that for every . Given two integer-valued functions such that for all , an -factor is also called -factor if for all . In particular, if , then an -factor is also called an -factor. We say that has all -factors if for any integer-valued function defined on such that and for all , contains an -factor. We write
[TABLE]
For simplicity, we write if for all .
Niessen [7] derived from Tutte’s -factor theorem a similar characterization for the property of graphs having all -factors.
Theorem 1** (Niessen [7])**
* has all -factors if and only if*
[TABLE]
for all disjoint sets , where denotes the number of components of such that there exists a vertex with or .
It is well-known that there exists a polynomial time algorithm to determine whether a graph has a -factor. An open problem was naturally proposed in [7]:
Problem 2
Is there a polynomial time algorithm for testing whether a graph has all -factors?
In this note, we obtain the following theorem, which gives a negative answer to Problem 2, unless P=NP.
Theorem 3
It is NP-hard to determine whether a graph has all -factors.
The main ingredient in the proof of Theorem 3 is the following two results.
Theorem 4** (Bauer et. al., [3])**
It is NP-hard to recognize 1-tough cubic graphs.
Theorem 5** (Kano and Lu, [6])**
Let be a connected graph. A graph has an -factor for every with even if and only if is almost 1-tough.
Theorem 5 gives a polynomial time reduction from the toughness of graphs to the degree constrained factors.
2 The Proof of Theorem 3
To prove Theorem 3, we need the following notations.
Definition 6
Let be a graph with . Write , .
- (i)
For any vertex of , let denote the graph obtained from by adding a new vertex together with a new edge , that is, .
- (ii)
Let be a graph with vertex set and edge set , where and ;
- (iii)
For any , we define such that
[TABLE]
Now we show the following result.
Lemma 7
A graph is 1-tough if and only if for any , is almost 1-tough.
Proof. Necessity. Suppose that is 1-tough. Let . For any ,
[TABLE]
Sufficiency. By contradiction, suppose that is not 1-tough. Then there exists such that . Let . One can see that
[TABLE]
which contradicts the fact that is 1-tough.
From Theorem 4 and Lemma 7, one may see that
Lemma 8
It is NP-hard to recognize almost 1-tough cubic graph.
Lemma 9
Let be a connected cubic graph and let . Then contains an -factor if and only if contains an -factor.
Proof. Necessity. Suppose that contains an -factor . Define M_{1}=\{x_{i}y_{i}\ |\ d_{F}(v_{i})\in\{1,2\}\ \mbox{for i\in[n]}\} and M_{2}=\{x_{i}v_{i},y_{i}v_{i}\ |\ d_{F}(v_{i})=0\ \mbox{for i\in[n]}\}. Let be a spanning subgraph of with edge set . From the definition of function , one can see that
[TABLE]
So is an -factor of .
Sufficiency. Suppose that be an -factor of . Let be a spanning subgraph of with edge set . Now we show that is an -factor of . From Definition 6 (iii), one can see that
[TABLE]
Consider . Since , then we have . So we have . Next we may assume that . Then either or . In the former case, we have , and in the latter case we have . So in both cases, one can see that and is an -factor of . This completes the proof.
Lemma 10
Let be a connected cubic graph. Then contains an -factor for any with even if and only if contains all -factors, where and
[TABLE]
Proof. Define
[TABLE]
and
[TABLE]
Let such that for all . From the definition of , one can see that is well-defined. By Lemma 9, it is suffices for us to show that is a bijection. Firstly, we show that is injective. For any such that , there exists , such that . Without loss of generality, we may assume that and . By Definition 6 (iii), we have and , which implies . Next we show is a surjection. For every , we may define such that
[TABLE]
Since is even, is even. So we get that and . Thus is surjective.
This completes the proof.
Proof of Theorem 3. Let be a connected cubic graph. By Theorem 5, is almost 1-tough if and only if contains an -factor for any with even. Thus by Lemma 10, one can see that is almost 1-tough if and only if contains all -factors, where and
[TABLE]
Since it is NP-hard to recognize almost 1-tough graphs by Lemma 8, one can see that it is NP-hard to determine whether a graph contains all -factors. This completes the proof of Theorem 3.
The reference list from the paper itself. Each links out to its DOI / PubMed record.
- 1[1] D. Bauer, S.L. Hakimi and E. Schmeichel, Recognizing tough graphs is NP-hard, Discrete Appl. Math , 28 (1990), 191–195.
- 2[2] D. Bauer, H.J. Broersma and H.J. Veldman, Not every 2-tough graph is hamiltonian, Discrete Appl. Math. , 99 (2000), 317–321.
- 3[3] D. Bauer, J. van den Heuvel, A. Morgana and E. Schmeichel, The complexity of recognizing tough cubic graphs, Discrete Appl. Math. , 79 (1997), 35–44.
- 4[4] D. Bauer, J. van den Heuvel, A. Morgana and E. Schmeichel, Toughness and triangle-free graphs. J Combin. Theory Ser. B , 65 (1995), 208–221.
- 5[5] G. Cornuéjols, General factors of graphs, J. Combin. Theory Ser. B , 45 (1988), 185–198.
- 6[6] M. Kano and H. Lu, Characterization of 1-Tough Graphs using Factors, https://arxiv.org/abs/1702.05873 v 2.
- 7[7] T. Niessen, A characterization of graphs having all ( g , f ) 𝑔 𝑓 (g,f) -Factors, J. Combin. Theory, Ser. B , 72 (1998), 152–156.
- 8[8] W.T. Tutte, The factorization of linear graphs, J. London Math. Soc. , 22 (1947), 107–111.
