11email: [email protected],{coe18d004,sadagopan}@iiitdm.ac.in 22institutetext: Indian Institute of Information Technology Design and Manufacturing, Kurnool.
22email: [email protected]
Hamiltonicity: Variants and Generalization in -free Chordal Bipartite graphs††thanks: This work is partially supported by DAE-NBHM project, NBHM/ 02011/37/2017/RD II/16646
Abstract
A bipartite graph is chordal bipartite if every cycle of length at least six has a chord in it. Mller [10] has shown that the Hamiltonian cycle problem is NP-complete on chordal bipartite graphs by presenting a polynomial-time reduction from the satisfiability problem. The microscopic view of the reduction instances reveals that the instances are -free chordal bipartite graphs, and hence the status of Hamiltonicity in -free chordal bipartite graphs is open. In this paper, we identify the first non-trivial subclass of -free chordal bipartite graphs which is -free chordal bipartite graphs, and present structural and algorithmic results on -free chordal bipartite graphs. We investigate the structure of -free chordal bipartite graphs and show that these graphs have a Nested Neighborhood Ordering (NNO), a special ordering among its vertices. Further, using this ordering, we present polynomial-time algorithms for classical problems such as the Hamiltonian cycle (path), also the variants and generalizations of the Hamiltonian cycle (path) problem. We also obtain polynomial-time algorithms for treewidth (pathwidth), and minimum fill-in in -free chordal bipartite graph. We also present some results on complement graphs of -free chordal bipartite graphs.
Keywords:
-free chordal bipartite graphs Nested Neighborhood Ordering Hamiltonian cycle (path) Longest cycle (path) Steiner cycle (path) Treewidth Pathwidth Minimum fill-in1 Introduction
The graphs with forbidden subgraphs possess a nice structural characterization. The structural characterization of these graphs has attracted researchers from both mathematics and computing. The popular graphs are chordal graphs [1], which forbid induced cycles of length at least four, and chordal bipartite graphs [2], which are bipartite graphs that forbid induced cycles of length at least six. Further, these graph classes have a nice structural characterization with respect to minimal vertex separators and a special ordering, namely, perfect elimination ordering [3] among its vertices (edges). These graphs are largely studied in the literature to understand the computational complexity of classical optimization problems such as vertex cover, dominating set, coloring, etc., as these problems are known to be NP-complete on general graphs. Thus these graphs help to identify the gap between NP-complete instances and polynomial-time solvable instances for classical combinatorial problems.
The Hamiltonian cycle (path) problem is a famous problem that asks for the presence of a cycle (path) that visits each node exactly once in a graph. A graph is said to be Hamiltonian if it has a Hamiltonian cycle. The Hamiltonian problem plays a significant role in various research areas such as circuit design [4], operational research [5], biology [6], etc. On the complexity front, this problem is well studied and it remains NP-complete on general graphs. Interestingly, this problem is polynomial-time solvable on special graphs such as cographs and permutation graphs [7]. Surprisingly, this problem is NP-complete on chordal graphs [8], bipartite graphs [9], and -free graphs [3].
Mller [10] has shown that the Hamiltonian cycle problem is NP-complete on chordal bipartite graphs by presenting a polynomial-time reduction from the satisfiability problem. The microscopic view of the reduction instances reveals that the instances are -free chordal bipartite graphs. It is natural to study the complexity of the Hamiltonian cycle problem in -free chordal bipartite graphs and its subclasses. Since -free chordal bipartite graphs are complete bipartite graphs, the first non-trivial graph class in this line of research is -free chordal bipartite graphs. Further, the Steiner tree problem and the dominating set problem are also NP-complete for chordal bipartite graphs [11] as there is a polynomial-time reduction from the vertex cover problem. Interestingly, the instances generated have in it. This gives us another motivation to study the structure of -free chordal bipartite graphs.
It is known from the literature that the Hamiltonian cycle problem is NP-complete on -free graphs [3]. Therefore, it is NP-complete on -free graphs as well. In this paper, we present a polynomial-time algorithm for -free graphs which are precisely -free chordal bipartite graphs.
A graph is -bisplit if it has a stable set (an independent set) such that has at most bicliques (complete bipartite graphs). A graph is weak bisplit if it is -bisplit for some . It is known from [12], recognizing weak bisplit graphs is NP-complete, whereas recognition of -bisplit graphs for every fixed is polynomial-time solvable. A graph is bisplit if its vertex set can be partitioned into three stable sets , , and such that induces a complete bipartite subgraph (a biclique) in . Note that 1-bisplit graphs are bisplit graphs. Brandstädt et al. [12] provided linear time recognition algorithm for bisplit graphs. Subsequently, Abueida et al. [13] has given time recognition algorithm for bisplit graphs. Various popular problems like, Hamiltonian cycle (path) problem, domination, independent dominating set and feedback vertex set are NP-complete on bisplit graphs. So, it is natural to investigate the complexities of the problems mentioned above in a subclass of bisplit graphs. Interestingly, chordal bipartite graphs are a subclass of bisplit graphs and hence due to [10] the Hamiltonian cycle (path) problem is NP-complete on this graph class. This is another motivation to investigate the structure of -free chordal bipartite graphs, which are a subclass of bisplit graphs.
In recent times, the class of -free graphs have received a good attention, and problems such as independent set [14], k-colourbility [15], and feedback vertex set [16] have polynomial-time algorithms restricted to -free graphs.
The longest path problem is the problem of finding an induced path of maximum length in . Since this problem is a generalization of the Hamiltonian path problem, it is NP-complete on general graphs. This problem is polynomial-time solvable in interval graphs [17] and biconvex graphs [18]. A minimum leaf spanning tree is a spanning tree of with the minimum number of leaves. This problem is NP-complete on general graphs, and polynomial-time solvable on cographs [19]. It is important to highlight that the minimum leaf spanning tree problem in cographs can be solved using the longest path problem as a black box. In this paper, we wish to see whether we can come up with a framework for Hamiltonicity and its variants in -free chordal bipartite graphs.
It is important to highlight that other classical problem such as Steiner tree, dominating set, connected dominating set are known to be NP-complete on chordal bipartite graphs [11].
Similar to the Hamiltonian cycle (path) problem, its variants also attracted many researchers. We shall see some of the popular variants of the Hamiltonian cycle (path) problem. A graph with the vertex set and the edge set is pancyclic [20] if it contains cycles of all lengths , . A graph is (2)-pancyclic graph [21] if it contains exactly two cycles of length , . A graph is said to be bipancyclic [22] if it contains a cycle of length , . A graph is said to be Hamiltonian connected if there exists a Hamiltonian path between every pair of vertices. Asratian [23] and Kewenet et al. [24] have given sufficient conditions for a graph to be Hamiltonian connected. A graph is said to be homogeneously traceable if there exists a Hamiltonian path beginning at every vertex of . Skupień [25] has given necessary condition for a graph to be homogeneously traceable. Chartrand et al.[26] proved that there exists a homogeneously traceable non-Hamiltonian graph of order for all positive integers except . A hypo-Hamiltonian graph is a non-Hamiltonian graph such that is Hamiltonian for every vertex . A graph is -ordered Hamiltonian if for every ordered sequence of vertices, there exists a Hamiltonian cycle that encounters the vertices of the sequence in the given order. Faudree et al. [27] have given degree conditions for a graph to be -ordered Hamiltonian. These variants are known to be NP-complete on general graphs, and chordal biparatite graphs.
In the literature, there are many conditions for Hamiltonicity and its variants. Due to the inherent difficulty of the problem, all these conditions are either necessary conditions or sufficient conditions, however no known necessary and sufficient conditions.
We show that Chvátal’s Hamiltonian cycle (path) necessary condition is sufficient for -free chordal bipartite graphs. We also present a necessary and sufficient condition for the existence of the Steiner path (cycle) in -free chordal bipartite graphs.
Our work: In this paper, we study the structure of -free chordal bipartite graphs and present a new ordering referred to as Nested Neighbourhood Ordering among its vertices. We present a polynomial-time algorithm for the Hamiltonian cycle (path) problem using the Nested Neighbourhood Ordering. Further, using this ordering, we present polynomial-time algorithms for longest path (cycle), minimum leaf spanning tree, Steiner path (cycle), treewidth (pathwidth), and minimum fill-in. We believe that these results can help us in the study of other combinatorial problems restricted to -free chordal bipartite graphs, and also in the structural investigation of -free chordal bipartite graphs, . Further, our understanding shall help us in obtaining a dichotomy: easy vs hard input instances of chordal bipartite graphs. We also present some results on complement graphs of -free chordal bipartite graphs.
Related work: Structure of -free graphs has been looked at while studying the Difference graph [28], 3-colorable -free graphs [29], and -free graphs [30]. However, the explicit mention of NNO has not been reported in the literature. To the best of our knowledge, the algorithmic results presented in this paper are new and have not been reported in the literature.
1.1 Preliminaries
In this paper, we work with simple, connected, undirected and unweighted graphs. For a graph , let denote the vertex set and denote the edge set. The notation represents an edge incident on the vertices and . The neighborhood of a vertex of , , is the set of vertices adjacent to in . The degree of a vertex is denoted by . We use and interchangeably if the graph under consideration is clear from the context. A graph is called an induced subgraph of if for all , if and only if . The graph induced on is denoted by . A graph is said to be connected if there exists a path between every pair of vertices. If is disconnected, then denotes the number of connected components in (each component being maximal). A bipartite graph is chordal bipartite if every cycle of length at least six has a chord. A maximal biclique is a complete bipartite graph such that there is no strict supergraphs or . A maximum biclique is a maximal biclique with the property that is minimum. Note that is an induced path of length and denotes a path that starts at and ends at , and denotes its length. We use and interchangeably. Let denote the complement of the graph , where and .
2 Structural Results
In this section, we shall present a structural characterization of -free chordal bipartite graphs. Also, we introduce Nested Neighborhood Ordering (NNO) among its vertices. We shall fix the following notation to present our results. For a chordal bipartite with bipartition , let and . The edge set . Let and , , and , , such that is a maximum biclique.
Lemma 1
Let be a -free chordal bipartite graph. Then, such that and such that .
Proof
Suppose there exists in such that for all in , . Then is the maximum biclique, contradicting the fact that is maximum. Similar argument is true for . Therefore, the lemma follows. ∎
Lemma 2
Let be a -free chordal bipartite graph. Then, , and , .
Proof
On the contrary, , . Case 1: . Then, is the maximum biclique, a contradiction. Case 2: . This implies that there exists such that . Since is connected, , say . In , is an induced . Note that, due to the maximality of , as per Lemma 1, we find . This contradicts that is -free. Case 3: and . I.e., such that and , . In , ), , is an induced . Note that the existence of is due to Lemma 1. This is contradicting the -freeness of . Similarly, , , can be proved. ∎
Lemma 3
Let be a -free chordal bipartite graph. For , , if , then . Similarly, for , if , .
Proof
Let us assume to the contrary that . I.e., .
Case 1: . I.e., such that . Since , such that and . Since , vertex is adjacent to at least one more vertex such that . The path ) is an induced . This is a contradiction.
Case 2: , and . I.e., such that , and , . Since is a connected graph, , an induced path of length at least 3. The path ) has an induced path of length at least 5. This is a contradiction. Similarly, for all pairs of distinct vertices with , can be proved. ∎
Theorem 2.1
Let be a -free chordal bipartite graphs with being the maximum biclique. Let and are orderings of vertices. If , then . Further, if , then .
Proof
We refer to the above ordering of vertices as Nested Neighbourhood Ordering (NNO) of . From now on, we shall arrange the vertices in in non-decreasing order of their degrees so that we can work with NNO of .
Lemma 4
Let be a -free chordal bipartite graph. Then, is bisplit.
Proof
By our structural result, we know that is partitioned into four stable sets namely , , , and . We observe that induces a maximum biclique and , is an independent set. Therefore, by definition, is bisplit. ∎
3 Hamiltonicity in -free Chordal Bipartite graphs
In this section, we shall present polynomial-time algorithms for the Hamiltonian cycle (path) problem in -free chordal bipartite graphs. For a connected graph and set , denotes the number of connected components in the graph induced on the set . It is well-known, due to, Chvatal [31] that if a graph has a Hamiltonian cycle, then for every . Similarly, if a graph has a Hamiltonian path, then for every .
Theorem 3.1
For a -free chordal bipartite graph , has a Hamiltonian cycle if and only if (i) and (ii) has an ordering , such that , and has an ordering , , .
Proof
Necessity: (i) Any cycle in a bipartite graph is even and alternates between vertices of and . Since the Hamilton cycle visits all the vertices in and , it must have . (ii) On the contrary, such that is the first vertex in the ordering with . That is, for , and . Since follows NNO, . From Theorem 2.1, we know that . This implies that . This is a contradiction to Chvatal’s necessary condition for the Hamiltonian cycle. Similarly, in , can be proved.
Sufficiency: Let and . Since has an ordering such that , , for clarity purpose, we define as follows; , , that is, is adjacent to at least two vertices and at most vertices , is adjacent to at least three vertices and at most vertices and similarly is adjacent to at least vertices and at most vertices . Observe that, due to the maximality of , any of can be adjacent to at most vertices of . Similarly, in , for all , .
Let and . The vertices in can be ordered as and the vertices in can be ordered as .
Note that and .
Further, and .
Since , it follows that .
In , is a Hamiltonian cycle. ∎
Theorem 3.2
For a -free chordal bipartite graph , has a Hamiltonian path if and only if one of the following is true
(i) and has an ordering, , and has an ordering, , .
(ii) and has an ordering,, and has an ordering, , .
Proof
Necessity: (i) Without loss of generality, we assume . Any Hamiltonian path starting at and alternates between and can end at or . Therefore or . To prove that satisfies the ordering, we assume to the contrary that such that is the first vertex in the ordering such that . Since follows NNO, . From Theorem 2.1, we know that . Note that, as per the ordering of , . On removing from we have components in and forms another component. This implies that . Clearly, . Thus we contradict the Chvatal’s necessary condition for the Hamiltonian path.
Similarly has an ordering such that , .
(ii) For , the argument is similar to the above. Suppose such that is the first vertex in the ordering such that . From Theorem 2.1, . Consider the set and . Further, . Note that and . Since , . Clearly, , contradicting the Chvatal’s condition for the Hamiltonian path.
Sufficiency: (i) Let , and . Consider . . Note that and . In ,
is a Hamiltonian path.
(ii) Consider and
.
In , is a Hamiltonian path. This completes the proof of this claim. ∎
Theorem 3.3
Let be a -free chordal bipartite graph. Finding a Hamiltonian path and cycle in are polynomial-time solvable.
4 Chvátal’s Necessary condition is Sufficient on -free chordal bipartite graphs
For the Hamiltonian cycle (path) problem, it is well-known from the literature that there are no necessary and sufficient conditions. However, we know the condition due to Chvátal is necessary but not sufficient and results due to Ore and Dirac are sufficient but not necessary. In this section, we show that Chvátal’s necessary condition is sufficient for -free chordal bipartite graphs.
Theorem 4.1
Let be a -free chordal bipartite graph with . If satisfies , for every non-empty subset , then has the Hamiltonian cycle.
Proof
Assume on the contrary, that has no Hamiltonian cycle, then there exists or in that violates the degree conditions mentioned in Theorem 2. Let be the first vertex in the ordering with . By Theorem 2.1, we know that follows NNO, . This implies that , which is a contradiction to the premise of the theorem. Similarly, in can be proved. ∎
Theorem 4.2
Let be a -free chordal bipartite graph with or . If satisfies , for every non-empty subset , then has the Hamiltonian path.
Proof
Case 1: . Assume on the contrary that has no Hamiltonian path, then there exists or in that violates degree conditions mentioned in Theorem 3.2. Let be the first vertex in the ordering with . By Theorem 2.1, we know that has NNO and hence . On removing from , we have components in and forms another component. This implies that . Clearly, , a contradiction.
Case 2: . Assume on the contrary that has no Hamiltonian path. Let be the first vertex in in the ordering such that . By Theorem 2.1, satisfies NNO. Consider the set and . Further, . Note that and . Since , , contradicting the premise. ∎
5 Hamiltonicity variants in -free chordal bipartite graphs
The variants of Hamiltonicity reported in the literature are bipancyclic, homogeneously traceable, EXACTLY 2 SIMPLE PATH COVER, Hamiltonian connected, and hypohamitonian. Interestingly, for all of them, similar to the Hamiltonian cycle we do not know necessary and sufficient conditions. In this paper, we establish necessary and sufficient conditions for a few of the variants restricted to -free chordal bipartite graphs.
5.1 Bipancyclic -free chordal bipartite graphs
Bondy [20] has given a sufficient condition for a graph to be pancyclic. Similarly, Amar [22] has given a sufficient condition for a graph to be bipancyclic in terms of vertex degree along with Hamiltonicity. It is important to highlight that for -free chordal bipartite graphs, being a Hamiltonian is necessary and sufficient to be bipancyclic.
Theorem 5.1
For a -free chordal bipartite graph of order , is Hamiltonian if and only if is bipancyclic.
Proof
Necessity: We know that the graph satisfies Theorem 3.1. From the structural results, it is clear that the graph induced on , say is a complete bipartite subgraph and follows NNO. Let . We obtain the cycles of length , , by following the Hamiltonian cycle procedure given in Theorem 3.1.
⋮
For the cycles, , , the following procedure is used.
⋮
Thus we obtain the cycles , in . Hence is a bipancyclic graph.
Sufficiency: Since is a -free chordal bipartite bipancyclic graph, we have the cycles of length , . It is easy to see that the cycle contains all the vertices of , which is a Hamiltonian cycle. ∎
Remark : The above proof is constructive and we can get all these cycles in polynomial time.
5.2 Homogeneously traceable -free chordal bipartite graphs
A graph is said to be homogeneously traceable if there exists a Hamiltonian path beginning at every vertex of . It is obvious that every Hamiltonian is homogeneously traceable. On the other hand, there exist homogeneously traceable non-Hamiltonian graphs. The Petersen graph is an example of a homogeneously traceable non-Hamiltonian graph. A graph is semi-Hamiltonian if it has a Hamiltonian path and does not have a Hamiltonian cycle. We denote the semi-Hamiltonian problem as ONE ENDPOINT SPECIFIED SEMI-HAMILTONIAN if one endpoint is specified in the input. ONE ENDPOINT SPECIFIED SEMI-HAMILTONIAN [32] problem is NP-complete on general graphs as there is a polynomial-time reduction from satisfiability problem. The Homogeneously traceable problem is a generalization of ONE ENDPOINT SPECIFIED SEMI-HAMILTONIAN problem. Chartrand et al.[26] has given a construction of homogeneously traceable non-Hamiltonian graph with vertices, . Interestingly, every homogeneously traceable -free chordal bipartite graphs are Hamiltonian graphs.
Theorem 5.2
For a -free chordal bipartite graph , is Hamiltonian if and only if is homogeneously traceable.
Proof
Necessity: It is easy to see that the Hamiltonian graphs are homogeneously traceable.
Sufficiency: Let be homogeneously traceable. Case 1: . By Theorem 2.1, the vertices of follows NNO property. Since is homogeneously traceable, we have Hamiltonian path beginning at every vertex of . Without out loss of generality, we begin the Hamiltonian path at vertex . We observe that the degree of is at least two. In general, , . Similarly, if we begin at , then the vertices of satisfies the following property, , . Now we observe that the graph follows Theorem 3.1. Therefore, is Hamiltonian.
Case 2: . We now show that this case is not possible. Assume on the contrary that this case is possible. Suppose we begin constructing the path at vertex and visit all of . Let be the set of vertices that helps to visit . Note that . Similarly, . Further, and . This implies that . It is clear that some vertices of are left out in the path . Therefore, the constructed path is not a Hamiltonian path. Hence this case is not possible.
∎
Corollary 1
Let be a -free chordal bipartite graph with . Then, is non-Hamiltonian connected.
Proof
Follows from the definition of Hamiltonian connected and Theorem 5.2.∎
5.3 EXACTLY 2 SIMPLE PATH COVER in -free chordal bipartite graphs
Simple path cover is a simple path that covers all the vertices of . By EXACTLY 2 SIMPLE PATH COVER [32], we denote the set of graphs that can be covered by two simple paths, but cannot be covered by one simple path. A Hamiltonian path can be viewed as one simple path that covers all the vertices of . These problems are NP-complete on general graphs. Since the Hamiltonian path problem is polynomial-time solvable in -free chordal bipartite graphs, it is natural to look at the complexity of EXACTLY 2 SIMPLE PATH COVER in this graph class. The notation refers to there exists unique .
Theorem 5.3
For a -free chordal bipartite graph , has Exactly 2 Simple Path Cover if and only if one of the following is true
(i) and has an ordering, and , and has an ordering, , .
(ii) and has an ordering, , and has an ordering, and , .
(iii) and has an ordering, and , and has an ordering, , .
(iv) and has an ordering, , and has an ordering, and , .
Proof
Necessity: (i) Without loss of generality, on the contrary, assume that a vertex such that or there exist at least two vertices such that and .
Case 1: There does not exist such that . By Theorem 3.2, we observe that is an yes instance of the Hamiltonian path problem, which is a one simple path cover. A contradiction.
Case 2: There exist at least two such vertices and . Without loss of generality, assume that . By following the procedure given in Theorem 3.2, we obtain three simple paths , , and that cover .
,
,
,
A similar argument can be given for (ii), (iii) and (iv)
Sufficiency: There exists exactly one vertex , such that . By Theorem 3.2, is a no instance of the Hamiltonian path problem and thus cannot be covered by one simple path. By following the procedure given in Theorem 3.2, we obtain the following two simple paths , and that cover .
,
Similarly (ii), (iii) and (iv) can be proved.
∎
5.4 Hamiltonian connected -free chordal bipartite graphs
A graph is said to be Hamiltonian connected if there exists a Hamiltonian path between every pair of vertices. Some of the related problems studied in the literature are TWO ENDPOINT SPECIFIED-SEMI-HAMILTONIAN [32], where both the endpoints are specified. This problem is NP-complete on chordal bipartite graphs. Hamiltonian connected is a generalization of this problem. In this paper, we investigate the Hamiltonian connectedness of . If has a Hamiltonian path, then satisfies Theorem 3.2. It is clear from Corollary 1 that if , then is non-Hamiltonian connected. We shall now look at the case where .
Theorem 5.4
Let be a -free chordal bipartite graph with . Then, is non-Hamiltonian connected.
Proof
Assume on the contrary, that is Hamiltonian connected. By the definition, there exists a Hamiltonian path between every pair of vertices. Without loss of generality, we choose a pair and from . Suppose, if we begin constructing the path at and visit the vertices of using except the vertex . Note that and . Further, and . Since , it follows that , in particular, . Now, we are left with two vertices in , say and , and a vertex . We observer that either ends in leaving or ends in leaving . Clearly, is not a Hamiltonian path, which is a contradiction. Hence is non-Hamiltonian connected. ∎
5.5 Path-hypohamitonian -free chordal bipartite graphs
We know that bipartite graphs are non-hypohamiltonian graphs. So it is natural to ask for the variants of hypohamiltonian, one such variant is path-hypohamiltonian. A graph is called path-hypohamiltonian, if has no Hamiltonian path and , has a Hamiltonian path. In this section, we show that -free chordal bipartite graphs are non-path-hypohamiltonian.
Theorem 5.5
Let be a -free chordal bipartite graph and has no Hamiltonian path. Then, is non-path-hypohamiltonian.
Proof
We now exhibit a vertex such that has no Hamiltonian path. Since is a no instance of Hamiltonian path problem, by Theorem 3.2, either (i) or (ii) is true. (i) and there exists a vertex such that or such that (ii) there exists a vertex such that or such that .
(i) We observe that is an yes instance of the Hamiltonian path problem and thus we get a Hamiltonian path in . Now we choose . In , the degree . By Theorem 3.2, is a no instance of the Hamiltonian path problem. Therefore, is non-path-hypohamiltonian.
(ii) We choose . In , It is easy to see that . By Theorem 3.2, is a no instance of Hamiltonian path problem. Therefore, is non-path-hypohamiltonian.
Remark: The problems discussed in this section and their proofs are constructive in nature, therefore we obtain a polynomial-time algorithm for Hamiltonicity variants.
6 Generalizations of Hamiltonian path (cycle) in -free chordal bipartite graphs
We know that, if a problem is NP-complete for a graph class under study, then the problem is also NP-complete in all its superclasses. Further, the generalization of the problem under study is also NP-complete in that graph class. For example, the Hamiltonian path is NP-complete on split graphs therefore it is NP-complete in chordal graphs. The longest path problem which is a generalization of the Hamiltonian path problem is NP-complete in split graphs. If a problem is polynomial-time solvable in a graph class, then it is appropriate to investigate the complexity of its generalization in that graph class. Interestingly, in -free chordal bipartite graphs, Hamiltonian path (cycle) problems are polynomial-time solvable. So it is natural to look at the generalization of the Hamiltonian path (cycle) problems and their complexity study in -free chordal bipartite graphs. In this section, we use the Hamiltonian cycle (path) problem as a framework to solve other combinatorial problems. For all other problems, we modify the input graph to obtain . The challenge lies in identifying for each combinatorial problem such as longest cycle (path), Steiner cycle (path). By calling the appropriate algorithm (Hamiltonian cycle, or Hamiltonian path Algorithm) on , we obtain a result. A suitable modification to the result will give the longest cycle (path), Steiner cycle (path) for . We shall see some of the generalizations of Hamiltonicity.
6.1 Longest paths in -free chordal bipartite graphs
For a connected graph , the longest path is an induced path of maximum length in . Since the Hamiltonian path is a path of maximum length, finding the longest path is trivially solvable if the input instance is an yes instance of the Hamiltonian path problem. Thus the longest path problem is a generalization of the Hamiltonian path problem, and hence the longest path problem is NP-complete if the Hamiltonian path problem is NP-complete on the graph class under study. On the other hand, it is interesting to investigate the complexity of the longest path problem in graphs where the Hamiltonian path problem is polynomial-time solvable. Since, the Hamiltonian path problem in -free chordal bipartite graphs is polynomial-time solvable, in this section, we shall investigate the complexity of the longest path problem in -free chordal bipartite graphs.
Pruning: We shall now prune by removing vertices that will not be part of any longest path in . Without loss of generality, we assume that has no Hamiltonian path, and hence , or there must exists a vertex in () that does not satisfies the conditions mentioned in Theorem 3.2. As part of pruning, we prune such vertices from . Recall that . Let be the first vertex in with . Remove and relabel the vertices of so that the sequence is reduced to . With respect to the modified sequence, if we find such that , then prune and update the sequence. If there are no such , then . After, say iterations, becomes such that for . Similarly, after iterations, becomes such that for . After pruning the vertices in is reduced to the set , ,, similarly, reduced to the set , . From now on, when we refer to (), it refers to the modified (). Let be the modified graph of . .
Case 1:
We observe that satisfies NNO and as per Theorem 3.2, has a Hamiltonian path, which is
Case 2: ,
If , By Theorem 3.2, is not an yes instance of the Hamiltonian path problem. We remove vertices from . Let be the modified graph. If , then be same as .
Case 2.1: in such that
Since , is not an yes instance of the Hamiltonian path problem as per Theorem 3.2. However has a Hamiltonian path as per Theorem 3.2.
Case 2.2: in such that
By Theorem 3.2, is an yes instance of the Hamiltonian path problem.
Claim 1: is a longest path in .
Proof
be the graph obtained by pruning the vertices from and in and thus becomes an yes instance of the Hamiltonian path problem. Since satisfies (NNO), for all the pruned vertices of and , their neighborhood is a subset of and respectively. This shows that the pruned vertices of and cannot be augmented to to get a longer path in . This proves that is a longest path in . ∎
Trace of the longest path algorithm:

For Figure 1, we shall trace the longest path algorithm. Consider the vertices of , , violates the degree constraint, so we prune and relabel the vertices as , as , and as . The updated sequence of is .
With respect to the modified sequence, , prune and relabel the vertex as . Now all the vertices of satisfies the degree constraint and the sequence is .
By applying the procedure to the vertices of , we get as .
The resultant graph falls under Case 1. We obtain the longest path

Consider Figure 2. The vertex violates the degree constrains, prune and we obtain , whose sequence reduced to . Similarly and violates the constraint and thus the sequence of is reduced to . follows Case 2 of the procedure. Let be the graph obtained by removing , vertices from . We observe that , by Case 2.1, remove and the longest path is
Theorem 6.1
Let be a -free chordal bipartite graph. Finding the longest path in is polynomial-time solvable.
Proof
Follows from the above discussion on pruning and Claim 1. ∎
Remarks: As an extension of longest path problem, we naturally obtain a minimum leaf spanning tree of , which is a spanning tree of with the minimum number of leaves, in polynomial-time. Since satisfies NNO, the vertices pruned while constructing , cannot be included as internal vertices of . We shall now construct a minimum leaf spanning tree with as a subtree. (i) the pruned vertices are augmented to as leaves to obtain . (ii) if , then the vertices in not included in are added to as leaves to obtain . Similarly, if , then the vertices in not included in are added to as leaves to obtain . This shows that has leaves. Maximum leaf spanning tree of can be constructed by choosing edge and augment all other vertices of to the vertex , similarly to .
Corollary 2
Minimum connected dominating set in -free chordal bipartite graph is polynomial-time solvable.
Proof
Follows from Theorem 6.1.
6.2 Longest cycles in -free chordal bipartite graphs
Similar to the longest path, the longest cycle is an induced cycle of maximum length in . It is natural to ask for the longest cycle in a graph if has no Hamiltonian cycle because it is trivially solvable when has a Hamiltonian cycle. Since, the Hamiltonian cycle problem in -free chordal bipartite graphs is polynomial-time solvable, in this section, we shall investigate the complexity of the longest cycle problem.
Pruning: Without loss of generality, we assume that has no Hamiltonian cycle, and hence or there must exist a vertex in that does not satisfies the condition mentioned in Theorem 2. The violated vertices cannot be a part of the longest cycle, so we prune such vertices from . Let be the first vertex in with . Remove and relabel the vertices of until there are no such . After say iterations, becomes such that for , 1, .
Similarly, after say iterations, becomes such that for , 1, . After pruning, reduced to the set , and reduced to the set , . Let the modified graph be .
Case 1:
satisfies NNO and by Theorem 3.1, is an yes instance of the Hamiltonian cycle problem.
Case 2: ,
By Theorem 3.1, and hence is an yes instance of the Hamiltonian cycle problem. We Remove , vertices from in results and by Theorem 3.1, has a Hamiltonian cycle.
Claim 2: is a longest cycle in .
Proof
We prune the vertices from and in and let the modified graph be . We observe that satisfies the condition mentioned in Theorem 2. Since satisfies (NNO), the neighborhood of pruned vertices of and is a subset of and respectively. Therefore the pruned vertices cannot be augmented to to get a longer cycle in . Hence is a longest cycle in . ∎
Trace of the Algorithm:
Consider the graph given in Figure 1, and violates the degree constraint, we prune the vertices and the sequence becomes . With respect to the modified sequence , prune and the sequence becomes . Similarly, in , is pruned, . We find such that , prune , . Graph satisfies case 1, and the longest cycle .
Case 2: Consider the graph given in Figure 2, vertices and are pruned and becomes . Similarly, is pruned and the sequence becomes . In the modified graph, and violates degree constraint and thus has a vertex . satisfies case 2 , . Let be the graph obtained by removing . The longest cycle .
6.3 Steiner paths in -free chordal bipartite graphs
The Steiner path problem is introduced in [33] which is a variant of the Steiner tree and a generalization of the Hamiltonian path problem. Given , find a path containing all of minimizing , if exists. Note that, this constrained path problem is precisely the Hamiltonian path problem when . This has another motivation as well. The Steiner tree problem [11] is the problem of connecting a given set of vertices (known as terminal vertices) by adding a minimum number of vertices from (known as Steiner vertices). The Steiner tree problem is trivially solvable in -free chordal bipartite graphs. It is natural to ask for a variant, namely the Steiner path. It is important to highlight that not all input graphs have Steiner paths. We shall present constructive proof for the existence of the Steiner path in a -free chordal bipartite graph.
Lemma 5
For a -free chordal bipartite graph and , has Steiner path if and only if the vertices of has an ordering such that , and .
Proof
We modify the instance of Steiner path problem of to the instance of Hamiltonian path problem of , where is the graph induced on the set .
Necessity : Assume on the contrary, there exists a vertex such that . Since is a no instance of the Hamiltonian path problem, the path obtained from is not a Steiner path, a contradiction.
Sufficiency: Since has an ordering and , , satisfies NNO in . By passing to the Hamiltonian path algorithm we obtain a path . Since the path spans all of , is a Steiner path in . Therefore, is a Steiner path. Since is an independent set of size , any path containing must have additional vertices and hence is a minimum Steiner path.
∎
Lemma 6
For a -free chordal bipartite graph and , has Steiner path if and only if there exists in such that , .
Proof
Let be the graph induced on .
Necessity : It is easy to see that if , then is a minimum Steiner path.
We shall now see the case where, . Assume on the contrary, there exists a vertex such that . We observe that is a no instance of Hamiltonian path problem, a contradiction.
Sufficiency: We observe that has a Hamiltonian path which is a Steiner path in . Note that the path
is a Steiner path of minimum cardinality. ∎
Lemma 7
For a -free chordal bipartite graph and ), has Steiner path if and only if has NNO with , , of .
Proof
Let be the graph induced on the set
Necessity : Proof is similar to the necessity of Lemma 6.
Sufficiency: The modified graph has a Hamiltonian path. We obtain the path which is a minimum Steiner path in . ∎
On the similar line, other cases , , and , and , and , and and and can be proved.
Trace: Let us consider the set, in Figure 3 (a). It is clear that all the vertices in set satisfies the above given degree constrains and hence there exists a Steiner path, . Suppose, if , then we observe that the vertex violates the degree constraint and hence there does not exist Steiner path in Figure 3 (b).


6.4 Steiner cycles in -free chordal bipartite graphs
Similar to the Steiner path, given a graph , the Steiner cycle problem asks for a simple cycle containing all of minimizing . Suppose, if , then this problem is precisely the Hamiltonian cycle problem. If is an yes instance of the Hamiltonian cycle problem, then this problem is trivially solvable. We observe that not all input graphs have a solution to the Steiner cycle problem. We shall present constructive proof for the existence of a Steiner cycle in a -free chordal bipartite graph.
Lemma 8
For a -free chordal bipartite graph and , has Steiner cycle if and only if the vertices of has an ordering such that , and .
Proof
Let be the graph induced on the set .
Necessity : Assume on the contrary, there exists a vertex such that . Since is a no instance of the Hamiltonian cycle problem, the cycle obtained from is not a Steiner path, a contradiction.
Sufficiency: Since has an ordering and , , satisfies NNO in . We call our Hamiltonian cycle algorithm on which outputs a cycle . Since the cycle spans all of , is a Steiner cycle in . Therefore, is a Steiner cycle. Any cycle containing must have additional vertices and hence is a minimum Steiner cycle.
∎
Lemma 9
For a -free chordal bipartite graph and , has Steiner cycle if and only if there exists in such that , .
Proof
Let be the graph induced on .
Necessity : If , then the Steiner cycle problem is trivially solvable. We obtain the Steiner cycle . We assume that .
Assume on the contrary, there exists a vertex such that . We observe that is a no instance of Hamiltonian cycle problem, a contradiction.
Sufficiency: We observe that has a Hamiltonian cycle which is a Steiner cycle in . The cycle .
is a Steiner cycle of minimum cardinality. ∎
Lemma 10
For a -free chordal bipartite graph and , has Steiner cycle if and only if has NNO with , , of .
Proof
Let be the graph induced on the set
Necessity : Proof is similar to the necessity of Lemma 9
Sufficiency: We observe that has a Hamiltonian cycle. The cycle
is a minimum Steiner cycle in . ∎
For other cases such as , , and , and , and , and and and , a similar argument can be given.
Trace: Consider the illustration given in Figure 4. We trace and of Figure 4 for the set . In Figure 4 (a), , so there must exist at least two vertices, in such that . We consider as and as . We observe that and . The Steiner cycle, . In Figure 4 (b), there does not exist at least two vertices satisfying the degree constraint and hence it is a no instance of a Steiner cycle.


Remark: Proofs of the problems discussed in this section are constructive in nature and thus we obtain a polynomial-time algorithm for generalization of the Hamiltonian cycle (path).
7 Treewidth and Pathwidth of -free chordal bipartite graphs
In general, many graph-theoretic problems have linear-time algorithms in trees. This motivates us to investigate the tree-like representation of graphs so that algorithmic techniques used in trees can be used to study the computational complexity of those problems in trees. The study of treewidth investigates this line of study. This problem was introduced by Robertson and Seymour [34]. This problem is NP-complete for bipartite graphs [35] and planar graphs. Treewidth can be obtained for cographs in time and for chordal bipartite graphs in time [36]. We have the following result in [36] for chordal bipartite graphs. Given a chordal bipartite graph , and a positive integer , if the treewidth of is at most then it returns yes with the underlying chordal embedding of , otherwise, it says no. However, the exact value of treewidth is not explicitly mentioned due to the inherent complex structure of chordal bipartite graphs. Interestingly, for -free chordal bipartite graphs, we present an exact value for treewidth as well as the underlying chordal embedding in linear time.
In this section, we present a polynomial-time algorithm to find a tree decomposition of a -free chordal bipartite graph, and hence the treewidth can be computed in polynomial time.
Definition :
A tree decomposition of a graph is a pair where is a tree and , is a vertex in such that for each , . Further,
-
(i)
,
-
(ii)
For every edge , there exists some such that and
-
(iii)
For every vertex the set induces a subtree in the tree .
The width of a tree decomposition is . The treewidth of a graph , denoted by , is the least possible width of a tree decomposition of minus one. The vertex set is also referred to as . In this section, we shall present an algorithm that outputs a tree decomposition of .
Correctness of Algorithm 1
Lemma 11
The graph obtained by Algorithm 1 is a tree and it satisfies all the three properties of tree decomposition mentioned in the definition.
Proof
-
(i)
is a Tree
Let , and is adjacent to by steps 6, 10, 15, 18 of Algorithm 1. From the construction, it is clear that the invariant maintained by Algorithm 1 is connectedness. We observe that at each step, , is created and an edge is added to corresponding to sets and which shows that is acyclic. This implies that is connected and acyclic. Hence is a tree. -
(ii)
For every edge , there exist some such that
By our construction, at each step a vertex and is added to for some . Hence there exist some such that . This shows that . -
(iii)
For every vertex the set induces subtree of the tree .
As per the construction, the vertices are added to the label . It is clear from Steps (5-20), the vertices of and are included based on NNO and an edge is added to . Similarly, from Steps (24-40), the vertices of and are included. Observe that for each , the set induces a subtree in .
Theorem 7.1
The treewidth of a -free chordal bipartite graph is .
Proof
We observe that in any tree decomposition there exists a label, whose cardinality is at least . On the contrary, suppose there exists a tree decomposition such that . Without loss of generality, we assume that and label. By the property of NNO, the vertex is adjacent to . Clearly, either the set label or label does not form a subtree in . Therefore, label. Similarly, each must be part of label. ∎
Lemma 12
The tree obtained from Algorithm 1 is a tree decomposition of such that the treewidth, .
Proof
By our construction, we see that the cardinality of each label is at most , in particular, . ∎
Corollary 3
Let be a -free chordal bipartite graph. Then, the pathwidth of is .
Proof
We know that for any graph , the pathwidth of is at least the treewidth of . By Theorem 7.1, the treewidth of a -free chordal bipartite graph is . We observe that the tree decomposition of output by Algorithm 1 is a also a path decomposition of . Hence the pathwidth of is same as the treewidth of which is . ∎
Trace of the Treewidth (Pathwidth) Algorithm (Algorithm 1):
Consider the illustration given in Figure 1. We shall trace the treewidth algorithm for Figure. 1. By Step 3, we create a label . The trace of other steps are included in Figure 6 and Figure 7.



8 Minimum Fill-in in -free chordal bipartite graphs
Having studied treewidth, we focus on problems that are related to treewidth. We know that a graph has treewidth at most if and only if has a chordal completion whose maximum clique size is at most . This motivates us to study the complexity of the chordal completion problem in -free chordal bipartite graphs. For a graph , the minimum fill-in (chordal completion) [38] problem is the problem of finding a chordal embedding of which is a graph obtained by an augmenting minimum number of edges to so that is chordal. The minimum fill-in problem is NP-complete on general graphs [37]. In [38] an time algorithm is presented for chordal bipartite graphs. Subsequently, in [39] it is improved to . Interestingly, a chordal embedding of a -free chordal bipartite graph is a split graph. In this section, we present a linear-time algorithm to find the minimum fill-in for -free chordal bipartite graphs.
Lemma 13
Let be a -free chordal bipartite graph. The number of edges augmented to find a chordal embedding of is min{
Proof
Let be a chordal embedding of with and , where is the set of augmented edges. We know that is a maximal biclique in . So, one of the partitions of must be a clique in . We consider the followings cases to find the edges added from to .
Case 1: is a clique. Then, in any , must be a clique.
On the contrary, there exist a pair of vertices, say , , , such that . Due to NNO property in , we get an induced cycle of length four. This contradicts the fact that is chordal. Therefore, induces a clique and the number of edges augmented is .
Case 2: is a clique. Then, must be a clique.
Suppose not, then there exist a pair of vertices, say , , , that are not adjacent in . Similar to Case 1, we get an induced cycle of length four, which is a contradiction. Therefore, we augment edges to .
From the above case analysis, Lemma 13 follows. ∎
Correctness of Algorithm 2
Lemma 14
Proof
By our construction, the graph induced on () is a complete graph. This implies that the graph induced on is a split graph, which is a chordal graph. We know that the pendant vertices of cannot be a part of a cycle. It is clear from the Steps (3-7) and the fact that follows NNO in , , , forms a clique. Similarly, for as well. We observe that there does not exist an induced cycle of length at least four in . Therefore, the graph constructed by Algorithm 2 is a chordal graph. From Steps (3-7) and Steps (14-18), it is clear that the number of edges added is the number mentioned in Lemma 13, which is min{. ∎
Trace of Algorithm 2: Consider the illustration given in Figure 8. We trace Algorithm 2 for Figure 8. The degree of , , Steps (3-5) of Algorithm 2 make a clique. Similarly, , forms a clique. Here, , = 66. Steps (14-18), initially chooses and add edges to . At Iteration 2, is connected to . The resultant graph is a chordal graph.

Theorem 8.1
The chordal embedding of a -free chordal bipartite graph is a split graph.
Proof
By construction, it is clear that is a maximal biclique, and , are independent sets. Let be a chordal embedding of . Algorithm 2 makes as a clique. The set forms an independent set. We see that the graph is partitioned into an independent and a clique. Therefore, is a split graph.
9 Results on Complement graphs of -free chordal bipartite graphs
The generalization of the minimum fill-in problem is cluster editing problem [40] where we modify the input graph by adding/removing at most edges. Note that finding the complement of a graph is an example of a cluster editing problem. Interestingly, the complement of -free chordal bipartite graph is chordal. We now present some results on complement graphs of -free chordal bipartite graphs.
We use the following notation, definition and results to prove our results.
Let denote the complement of the graph , where , and . Since , the notation we follow for is applicable for also.
Definition 1
A vertex of is called simplicial if induces a complete subgraph of .
Definition 2
Let be an undirected graph and let be an ordering of the vertices. We say that is a perfect vertex elimination scheme (or perfect elimination ordering) if each is a simplicial vertex of the induced subgraph .
Theorem 9.1
(Dirac 1961, Fulkerson and Gross, 1965, Rose 1970). A graph is chordal if and only if has a PEO.
Theorem 9.2
If is a -free chordal bipartite graph, then is a chordal graph.
Proof
To show that is chordal, we now exhibit a Perfect Elimination Ordering (PEO) in . Considering an ordering of , . We now show that is a PEO. On the contrary, assume that is not a PEO. Let be the first vertex in whose neighborhood is not a clique in the graph induced on .
Case 1:
We claim that is a clique. Suppose not, then there exist such that . This shows that in , , a contradiction to the independent set property of . Note that is a subset of . Therefore, is a simplicial vertex.
Case 2: .
Let . This implies that . Since satisfies NNO, to vertices of are adjacent to the vertices of the set , and is a clique. Let .
We now claim that the graph induced on is a clique. Suppose not, we obtain a contradiction to the independent set property of similar to Case 1. Note that is a subset of .
Therefore, is a simplicial vertex. Similar argument is true for .
From the above two cases, we conclude that is a PEO. Hence by Theorem 9.1, is a chordal graph.
Suppose or , then and are clique in . Therefore, is chordal. ∎
Lemma 15
For a graph , if the vertex connectivity is at least the independence number then is Hamiltonian [41].
Theorem 9.3
Let be a -free chordal bipartite graph such that and are non empty. If is Hamiltonian, then is Hamiltonian.
Proof
Since is an independent set in , it is clique in . Similarly, is a clique in .
We observe that any independent set in contains at most two vertices, in particular one vertex from and other from . Therefore, the independence number is at most two. We observer that is connected and now we show that there does not exist a cut vertex in . On the contrary, assume that there exists a cut vertex . W.l.o.g. assume that and be the neighbors of in .
Case 1: . Since the graph induced on is a clique, there exists a path in . This shows that is connected. Similar argument is true for , and in .
Case 2: , and . Since , and the set induces a clique, we obtain a path , where , and in . This shows that is not a cut vertex. Therefore, the vertex connectivity of is at least two. From Lemma 15, we conclude that is Hamiltonian.
Time Complexity Analysis :
The Nested Neighbourhood Ordering (NNO) of -free chordal bipartite graphs can be obtained in linear time by using perfect edge elimination ordering proposed by Fulkerson and Gross. Further, the Hamiltonian cycle (path) can be obtained in linear time. Since bipancyclic, and homogeneously traceable involves order call to Hamiltonian cycle (path) algorithm, these two incurs time. All other algorithmic results run in linear time.
Conclusions and Further Research
In this paper, we have presented structural results on -free chordal bipartite graphs. Subsequently, using these results, we have presented polynomial-time algorithms for the Hamiltonian cycle (path), also its variants and generalizations. We also presented polynomial-time algorithms for combinatorial problems such as treewidth (pathwidth), and minimum fill-in. We have also shown that Chvátal’s necessary condition is sufficient for this graph class. Further, we have presented some results on complement graphs of -free chordal bipartite graphs. These results exploit the nested neighborhood ordering of -free chordal bipartite graphs which is an important contribution of this paper. A natural direction for further research is to study -free chordal bipartite graphs and -free chordal bipartite graphs as the complexity of most of these problems are open in these graph classes.
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