Search or ask a question
Book ChapterDOI

# A Note on k-Colorability of P5-Free Graphs

, Xiao Shu4
25 Aug 2008-Vol. 5162, pp 387-394
TL;DR: A polynomial-time algorithm determining whether or not, for a fixed k, a P 5 -free graph can be k-colored is presented, and if such a coloring exists, the algorithm will produce one.
Abstract: We present a polynomial-time algorithm determining whether or not, for a fixed k, a P 5 -free graph can be k-colored. If such a coloring exists, the algorithm will produce one.

## Summary (1 min read)

### 1 Introduction

• Graph coloring is among the most important and applicable graph problems.
• For other classes of graphs, like perfect graphs [8], the problem is polynomial-time solvable.
• Then in Section 3, the authors present their recursive polynomial-time algorithm that answers thek-colorability question forP5-free graphs.

### 2 Background and Definitions

• In this section the authors provide the necessary background and definitions used in the rest of the paper.
• The following structural result aboutP5-free graphs is from Bacsó and Tuza [2]: THEOREM 1 Every connected P5-free graph has either a dominating clique or a dominating P3.
• This listing corresponds to their initial instanceΦ.

### 3 The Algorithm

• This section describes a polynomial time algorithm that decides whether or notG is k-colorable.
• Identify and color a maximal dominating clique or aP3 if no such clique exists (Theorem 1).
• This partitions the vertices intofixed setsindexed by available colors.
• Thus, for each instanceφi the authors recursively see if each fixed set can be colored with the corresponding restricted color lists (the base case is when the color listsare a single color).
• As mentioned, the difficult part is reducing the dependencies between each pair of fixed sets (Step 2).

### 3.1 Removing the Dependencies Between Two Fixed Sets

• Let Slist denote a fixed set of vertices with color list given bylist.
• This is becauseP and Q are subsets of different fixed sets.
• Thus there must be at most one special componentC.
• Using this procedure along with Theorem 2, the authors can remove the dep ndencies between two dynamic setsP andQ for a given list-coloring instanceφ.
• Since the authors know that the special componentC has already been handled.

### 4 Summary

• The algorithm recursively uses list coloring techniques and thus its complexity is high even though it is polynomial, as is the case with all list coloring algorithms.
• In a relatedpaper (in preparation), the authors will give a slightly faster algorithm also based on list coloring techniques, however this algorithm provides less insight into the structure ofP5-free graphs.
• Is the problem ofk-coloring aP7-free graph NP-complete for anyk ≥.
• Two other related open problems are to determine the complexities of theMAXIMUM INDEPENDENT SET andMINIMUM INDEPENDENT DOMINATING SET problems onP5-free graphs.

Did you find this useful? Give us your feedback

Content maybe subject to copyright    Report

A note on k-colorability of P
5
-free graphs
Ch
´
ınh T. Ho

ang
Marcin Kami
´
nski
Vadim Lozin
J. Sawada
§
X. Shu
Abstract
A polynomial time algorithm that determines whether or not, for a ﬁxed k, a P
5
-free graph can
be k-colored is presented in this paper. If such a coloring exists, the algorithm will produce a valid
k-coloring.
Keywords: P
5
-free, graph coloring, dominating clique
1 Introduction
Graph coloring is among the most important and applicable graph problems. The k-colorability prob-
lem is the question of whether or not the vertices of a graph can be colored with one of k colors so
that no two adjacent vertices are assigned the same color. In general, the k-colorability problem is NP-
complete [10]. Even for planar graphs with no vertex degree exceeding 4, the problem is NP-complete
[5]. However, for other classes of graphs, like perfect graphs [8], the problem is polynomial-time solv-
able. For the following special class of perfect graphs, there are efﬁcient polynomial time algorithms
for ﬁnding optimal colorings: chordal graphs [6], weakly chordal graphs [9], and comparability graphs
[4]. For more information on perfect graphs, see [1], [3], and [7].
Another interesting class of graphs are those that are P
t
-free, that is, graphs with no chordless paths
v
1
, v
2
, . . . , v
t
of length t 1 as induced subgraph for some ﬁxed t. If t = 3 or t = 4, then there exists
efﬁcient algorithms to answer the k-colorability question (see [3]). However, it is known that CHRO-
MATIC NUMBER for P
5
-free graphs is NP-complete [11]. Thus, it is of some interest to consider the
problem of k-coloring a P
t
-free graph for some ﬁxed k 3 and t 5. Taking this parameterization
Physics and Computer Science, Wilfrid Laurier University, Canada. Research supported by NSERC. E-mail:
choang@wlu.ca
RUTCOR, Rutgers University, 640 Bartholomew Road, Piscataway, NJ 08854, USA. E-mail:
mkaminski@rutcor.rutgers.edu
Mathematics Institute, University of Warwick, Coventry CV4 7AL UK. E-mail: V.Lozin@warwick.ac.uk
§
Computing and Information Science, University of Guelph, Canada. Research supported by NSERC. E-mail:
sawada@cis.uoguelph.ca
Computing and Information Science, University of Guelph, Canada. E-mail: xshu@uoguelph.ca
1

k\t 3 4 5 6 7 8 ... 12 ...
3 O(m) O(m) O(n
α
) O(mn
α
) ? ? ? ? .. .
4 O(m) O(m) ?? ? ? ? ? NP
c
.. .
5 O(m) O(m) ?? ? ? NP
c
NP
c
NP
c
.. .
6 O(m) O(m) ?? ? ? NP
c
NP
c
NP
c
.. .
7 O(m) O(m) ?? ? ? NP
c
NP
c
NP
c
.. .
.. . .. . .. . ... ... .. . .. . . .. ... ...
Table 1: Known complexities for k-colorability of P
t
-free graphs
into account, a snapshot of the known complexities for the k-colorability problem of P
t
-free graphs is
given in Table 1. From this chart we can see that there is a polynomial algorithm for the 3-colorability
of P
6
-free graphs [12].
In this paper we focus on P
5
-free graphs. Notice that when k = 3, the colorability question for P
5
-
free graphs can be answered in polynomial time (see [13]). We obtain a theorem (Theorem 2) on the
structure of P
5
-free graphs and use it to design a polynomial-time algorithm that determines whether
a P
5
-free graph can be k-colored. If such a coloring exists, then the algorithm will yield a valid k-
coloring.
The remainder of the paper is presented as follows. In Section 2 we present relevant deﬁnitions, con-
cepts, and notations. Then in Section 3, we present our recursive polynomial-time algorithm that an-
swers the k-colorability question for P
5
-free graphs.
2 Background and Deﬁnitions
In this section we provide the necessary background and deﬁnitions used in the rest of the paper. For
starters, we assume that G = (V, E) is a simple undirected graph where |V | = n and |E| = m. If A is
a subset of V , then we let G(A) denote the subgraph of G induced by A.
DEFINITION 1 A set of vertices A is said to dominate another set B, if every vertex in B is adjacent to
at least one vertex in A.
The following structural result about P
5
-free graphs is from Bacs
´
o and Tuza [2]:
THEOREM 1 Every connected P
5
-free graph has either a dominating clique or a dominating P
3
.
DEFINITION 2 Given a graph G, an integer k and for each vertex v, a list l(v) of k colors, the k-list
coloring problem asks whether or not there is a coloring of the vertices of G such that each vertex
receives a color from its list.
2

DEFINITION 3 The restricted k-list coloring problem is the k-list coloring problem in which the lists
l(v) of colors are subsets of {1, 2, . . . , k}.
Our general approach is to take an instance of a speciﬁc coloring problem Φ for a given graph and
replace it with a polynomial number of instances φ
1
, φ
2
, φ
3
, . . . such that the answer to Φ is “yes” if
and only if there is some instance φ
k
that also answers “yes”.
For example, consider a graph with a dominating vertex u where each vertex has color list {1, 2, 3, 4, 5}.
This listing corresponds to our initial instance Φ. Now, by considering different ways to color u, the
following set of four instances will be equivalent to Φ:
φ
1
: l(u) = {1} and the remaining vertices have color lists {2, 3, 4, 5},
φ
2
: l(u) = {2} and the remaining vertices have color lists {1, 3, 4, 5},
φ
3
: l(u) = {3} and the remaining vertices have color lists {1, 2, 4, 5},
φ
4
: l(u) = {4, 5} and the remaining vertices have color lists {1, 2, 3, 4, 5}.
In general, if we recursively apply such an approach we would end up with an exponential number of
equivalent coloring instances to Φ.
3 The Algorithm
Let G be a connected P
5
-free graph. This section describes a polynomial time algorithm that decides
whether or not G is k-colorable. The algorithm is outlined in 3 steps. Step 2 requires some extra
structural analysis and is presented in more detail in the following subsection.
1. Identify and color a maximal dominating clique or a P
3
if no such clique exists (Theorem 1). This
partitions the vertices into ﬁxed sets indexed by available colors. For example, if a P
5
-free graph
has a dominating K
3
(and no dominating K
4
) colored with {1, 2, 3} and k = 4, then the ﬁxed
sets would be given by: S
124
, S
134
, S
234
, S
14
, S
24
, S
34
. For an illustration, see Figure 1. Note that
all the vertices in S
124
are adjacent to the vertex colored 3 and thus have color lists {1, 2, 4}. This
gives rise to our original restricted list-coloring instance Φ. Although the illustration in Figure 1
does not show it, it is possible for there to be edges between any two ﬁxed sets.
2. Two vertices are dependent if there is an edge between them and the intersection of their color
lists is non-empty. In this step, we remove all dependencies between each pair of ﬁxed sets.
This process, detailed in the following subsection, will create a polynomial number of coloring
instances {φ
1
, φ
2
, φ
3
, . . .} equivalent to Φ.
3. For each instance φ
i
from Step 2 the dependencies between each pair of ﬁxed sets has been
removed which means that the vertices within each ﬁxed set can be colored independently. Thus,
3

S
134
S
14
S
124
S
24
S
4
S
34
S
234
2 3
1
Figure 1: The ﬁxed sets in a P
5
-free graph with a dominating K
3
where k = 4.
for each instance φ
i
we recursively see if each ﬁxed set can be colored with the corresponding
restricted color lists (the base case is when the color lists are a single color). If one such instance
provides a valid k-coloring then return the coloring. Otherwise, the graph is not k-colorable.
As mentioned, the difﬁcult part is reducing the dependencies between each pair of ﬁxed sets (Step 2).
3.1 Removing the Dependencies Between Two Fixed Sets
Let S
list
denote a ﬁxed set of vertices with color list given by list. We partition each such xed set
into dynamic sets that each represent a unique subset of the colors in list. For example: S
123
=
P
123
P
12
P
13
P
23
P
1
P
2
P
3
. Initially, S
123
= P
123
and the remaining sets in the partition are
empty. However, as we start removing dependencies, these sets will dynamically change. For example,
if a vertex u is initially in P
123
and one of its neighbors gets colored 2, then u will be removed from
P
123
and added to P
13
.
Recall that our goal is to remove the dependencies between two ﬁxed sets S
p
and S
q
. To do this,
we remove the dependencies between each pair (P, Q) where P is a dynamic subset of S
p
and Q is
a dynamic subset of S
q
. Let col(P ) and col(Q) denote the color lists for the vertices in P and Q
respectively. By visiting these pairs in order from largest to smallest with respect to |col(P )| and then
|col(Q)|, we ensure that we only need to consider each pair once. Applying this approach, the crux
of the reduction process is to remove the dependencies between a pair (P, Q) by creating at most a
polynomial number of equivalent colorings.
Now, observe that there exists a vertex v from the dominating set found in Step 1 of the algorithm that
dominates every vertex in one set, but is not adjacent to any vertex in the other. This is because P and
Q are subsets of different ﬁxed sets. WLOG assume that v dominates Q.
4

Y
4
Y
3
Y
2
Y
1
QP
y
1
y
2
y
4
y
3
v
a
c
d
b
Figure 2: Illustration for proof of Theorem 2
THEOREM 2 Let H be a P
5
-free graph partitioned into three sets P , Q and {v} where v is adjacent to
every vertex in Q but not adjacent to any vertex in P . If we let Q
denote all components of H(Q) that
are adjacent to some vertex in P then one of the following must hold.
1. There exists exactly one special component C in G(P ) that contains two vertices a and b such that
a is adjacent to some component Y
1
G(Q) but not adjacent to another component Y
2
G(Q)
while b is adjacent to Y
2
but not Y
1
.
2. There is a vertex x that dominates every component in Q
, except at most one (call it T).
PROOF: Suppose that there are two unique components X
1
, X
2
G(P ) with a, b X
1
and c, d X
2
and components Y
1
6= Y
2
and Y
3
6= Y
4
from G(Q) such that:
a is adjacent to Y
1
but not adjacent to Y
2
,
b is adjacent to Y
2
but not adjacent to Y
1
,
c is adjacent to Y
3
but not adjacent to Y
4
,
d is adjacent to Y
4
but not adjacent to Y
3
.
Let y
1
(respectively, y
2
, y
3
, y
4
) be a vertex in Y
1
(respectively, Y
2
, Y
3
, Y
4
) that is adjacent to a (respec-
tively, b, c, d) and not b (respectively, a, d, c). Since H is P
5
-free, there must be edges (a, b) and (c, d),
otherwise a, y
1
, v, y
2
, b or c, y
3
, v, y
4
, d would be P
5
s. An illustration of these vertices and components
is given in Figure 2.
Suppose Y
2
= Y
3
. Then b is not adjacent to y
3
, for otherwise there exists a P
5
a, b, y
3
, c, d. Now, there
exists a P
5
y
1
, a, b, y
2
, y
3
(if y
2
is adjacent to y
3
) or a P
5
a, b, y
2
, v, y
3
(if y
2
is not adjacent to y
3
). Thus,
Y
2
and Y
3
must be unique components. Similarly, we have Y
2
6= Y
4
. Now since b, y
2
, v, y
3
, c cannot be
5

##### Citations
More filters
Book ChapterDOI
05 Dec 2009
TL;DR: This work provides a certifying algorithm for the problem of deciding whether a P 5-free graph is 3-colorable by showing there are exactly six finite graphs that are P5-free and not 3- colorable and minimal with respect to this property.
Abstract: We provide a certifying algorithm for the problem of deciding whether a P 5-free graph is 3-colorable by showing there are exactly six finite graphs that are P 5-free and not 3-colorable and minimal with respect to this property.

49 citations

### Cites background or methods from "A Note on k-Colorability of P5-Free..."

• ...Previously known algorithms ([5,10,13]) provide a yes-certificate by constructing a 3-coloring if one exists....

[...]

• ...In [4] and [5], it is shown that k-COLORABILITY can be solved for the class of P5-free graphs in polynomial time for every particular value of k....

[...]

• ...Besides [4], there are several polynomial-time algorithms for 3-coloring a P5-free graph ([5,10,13]) but none of them is a certifying algorithm....

[...]

Journal ArticleDOI

TL;DR: An infinite set of k -critical P 5 -free graphs for every k -chromatic graph G ?
Abstract: With respect to a hereditary class C of graphs, a k -chromatic graph G ? C is said to be k -critical if every proper subgraph of G belonging to C is k - 1 colorable. It is known that there is a finite number of 4-critical P 5 -free graphs. We construct an infinite set of k -critical P 5 -free graphs for every k ? 5 . We also prove that there are exactly eight 5-critical { P 5 , C 5 } -free graphs and thirteen 5-vertex-critical { P 5 , C 5 } -free graphs.

37 citations

Journal ArticleDOI
TL;DR: An O ( n 3 ) algorithm to find a minimum weighted coloring of a ( P 5 , P � 5 )-free graph is designed and can be used to solve the same problem for several classes of graphs, defined by forbidden induced subgraphs, such as (diamond, co-diamond)-free graphs.
Abstract: We design an O ( n 3 ) algorithm to find a minimum weighted coloring of a ( P 5 , P � 5 )-free graph. Furthermore, the same technique can be used to solve the same problem for several classes of graphs, defined by forbidden induced subgraphs, such as (diamond, co-diamond)-free graphs.

34 citations

### Cites background from "A Note on k-Colorability of P5-Free..."

• ...Finding the chromatic number of a P5-free graphs is NP-hard [13], but for every fixed k, the problemof coloring a graphwith k colors admits a polynomial-time algorithm [11,12]....

[...]

Posted Content
TL;DR: A certifying algorithm for the problem of deciding whether a P5-free graph is 3-colorable was proposed in this article, where it was shown that there are exactly six finite graphs that are not 3-colourable.
Abstract: We provide a certifying algorithm for the problem of deciding whether a P5- free graph is 3-colorable by showing there are exactly six finite graphs that are P5-free and not 3-colorable and minimal with respect to this property.

17 citations

Book ChapterDOI
20 Aug 2009
TL;DR: It is proved that the problem is fixed parameter tractable on P 5-free graphs when parameterized by k, which contains the well known and widely studied class of cographs.
Abstract: A graph is k-choosable if it admits a proper coloring of its vertices for every assignment of k (possibly different) allowed colors to choose from for each vertex. It is NP-hard to decide whether a given graph is k-choosable for k ? 3, and this problem is considered strictly harder than the k-coloring problem. Only few positive results are known on input graphs with a given structure. Here, we prove that the problem is fixed parameter tractable on P 5-free graphs when parameterized by k. This graph class contains the well known and widely studied class of cographs. Our result is surprising since the parameterized complexity of k-coloring is still open on P 5-free graphs. To give a complete picture, we show that the problem remains NP-hard on P 5-free graphs when k is a part of the input.

13 citations

### Cites background from "A Note on k-Colorability of P5-Free..."

• ...An interesting point to mention is that the fixed parameter tractability of k-Coloring on P5free graphs is still open [ 10 ]....

[...]

• ...In last year’s MFCS, Hoang et al. showed that k-Coloring can be solved in polynomial time for any fixed k on P5-free graphs [ 10 ], but in their running time k contributes to the degree of the polynomial....

[...]

##### References
More filters
Book ChapterDOI
TL;DR: The work of Dantzig, Fulkerson, Hoffman, Edmonds, Lawler and other pioneers on network flows, matching and matroids acquainted me with the elegant and efficient algorithms that were sometimes possible.
Abstract: Throughout the 1960s I worked on combinatorial optimization problems including logic circuit design with Paul Roth and assembly line balancing and the traveling salesman problem with Mike Held. These experiences made me aware that seemingly simple discrete optimization problems could hold the seeds of combinatorial explosions. The work of Dantzig, Fulkerson, Hoffman, Edmonds, Lawler and other pioneers on network flows, matching and matroids acquainted me with the elegant and efficient algorithms that were sometimes possible. Jack Edmonds’ papers and a few key discussions with him drew my attention to the crucial distinction between polynomial-time and superpolynomial-time solvability. I was also influenced by Jack’s emphasis on min-max theorems as a tool for fast verification of optimal solutions, which foreshadowed Steve Cook’s definition of the complexity class NP. Another influence was George Dantzig’s suggestion that integer programming could serve as a universal format for combinatorial optimization problems.

8,644 citations

01 Jan 1972
TL;DR: Throughout the 1960s I worked on combinatorial optimization problems including logic circuit design with Paul Roth and assembly line balancing and the traveling salesman problem with Mike Held, which made me aware of the importance of distinction between polynomial-time and superpolynomial-time solvability.
Abstract: Throughout the 1960s I worked on combinatorial optimization problems including logic circuit design with Paul Roth and assembly line balancing and the traveling salesman problem with Mike Held. These experiences made me aware that seemingly simple discrete optimization problems could hold the seeds of combinatorial explosions. The work of Dantzig, Fulkerson, Hoffman, Edmonds, Lawler and other pioneers on network flows, matching and matroids acquainted me with the elegant and efficient algorithms that were sometimes possible. Jack Edmonds’ papers and a few key discussions with him drew my attention to the crucial distinction between polynomial-time and superpolynomial-time solvability. I was also influenced by Jack’s emphasis on min-max theorems as a tool for fast verification of optimal solutions, which foreshadowed Steve Cook’s definition of the complexity class NP. Another influence was George Dantzig’s suggestion that integer programming could serve as a universal format for combinatorial optimization problems.

7,714 citations

### Additional excerpts

• ...Ingeneral, thek-colorability problem is NPcomplete [10]....

[...]

• ...In general, thek-colorability problem is NPcomplete [10]....

[...]

Book
01 Jan 1980
TL;DR: This new Annals edition continues to convey the message that intersection graph models are a necessary and important tool for solving real-world problems and remains a stepping stone from which the reader may embark on one of many fascinating research trails.
Abstract: Algorithmic Graph Theory and Perfect Graphs, first published in 1980, has become the classic introduction to the field. This new Annals edition continues to convey the message that intersection graph models are a necessary and important tool for solving real-world problems. It remains a stepping stone from which the reader may embark on one of many fascinating research trails. The past twenty years have been an amazingly fruitful period of research in algorithmic graph theory and structured families of graphs. Especially important have been the theory and applications of new intersection graph models such as generalizations of permutation graphs and interval graphs. These have lead to new families of perfect graphs and many algorithmic results. These are surveyed in the new Epilogue chapter in this second edition. New edition of the "Classic" book on the topic Wonderful introduction to a rich research area Leading author in the field of algorithmic graph theory Beautifully written for the new mathematician or computer scientist Comprehensive treatment

4,090 citations

### "A Note on k-Colorability of P5-Free..." refers background in this paper

• ...For more information on perfect graphs, see [1], [3], and [7]....

[...]

Journal ArticleDOI
TL;DR: This paper shows that a number of NP - complete problems remain NP -complete even when their domains are substantially restricted, and determines essentially the lowest possible upper bounds on node degree for which the problems remainNP -complete.
Abstract: It is widely believed that showing a problem to be NP -complete is tantamount to proving its computational intractability. In this paper we show that a number of NP -complete problems remain NP -complete even when their domains are substantially restricted. First we show the completeness of Simple Max Cut (Max Cut with edge weights restricted to value 1), and, as a corollary, the completeness of the Optimal Linear Arrangement problem. We then show that even if the domains of the Node Cover and Directed Hamiltonian Path problems are restricted to planar graphs, the two problems remain NP -complete, and that these and other graph problems remain NP -complete even when their domains are restricted to graphs with low node degrees. For Graph 3-Colorability, Node Cover, and Undirected Hamiltonian Circuit, we determine essentially the lowest possible upper bounds on node degree for which the problems remain NP -complete.

2,200 citations

Journal ArticleDOI
TL;DR: The method yields polynomial algorithms for vertex packing in perfect graphs, for the matching and matroid intersection problems, for optimum covering of directed cuts of a digraph, and for the minimum value of a submodular set function.
Abstract: L. G. Khachiyan recently published a polynomial algorithm to check feasibility of a system of linear inequalities. The method is an adaptation of an algorithm proposed by Shor for non-linear optimization problems. In this paper we show that the method also yields interesting results in combinatorial optimization. Thus it yields polynomial algorithms for vertex packing in perfect graphs; for the matching and matroid intersection problems; for optimum covering of directed cuts of a digraph; for the minimum value of a submodular set function; and for other important combinatorial problems. On the negative side, it yields a proof that weighted fractional chromatic number is NP-hard.

2,170 citations

### Additional excerpts

• ...Keywords: P5-free, graph coloring, dominating clique...

[...]

14 Jun 2001
Daniel Král
10 Nov 2009
Hajo Broersma
15 Feb 2004