Linear time algorithm for the vertex-edge domination problem in convex bipartite graphs

For a connected graph, the Hamiltonian cycle (path) is a simple cycle (path) that spans all the vertices in the graph. It is known from \cite{muller,garey} that HAMILTONIAN CYCLE (PATH) are NP-complete in general graphs and chordal bipartite graphs. A convex bipartite graph $G$ with bipartition $(X,Y)$ and an ordering $X=(x_1,\ldots,x_n)$, is a bipartite graph such that for each $y \in Y$, the neighborhood of $y$ in $X$ appears consecutively. $G$ is said to have convexity with respect to $X$. Further, convex bipartite graphs are a subclass of chordal bipartite graphs. In this paper, we present a necessary and sufficient condition for the existence of a Hamiltonian cycle in convex bipartite graphs and further we obtain a linear-time algorithm for this graph class. We also show that Chvatal's necessary condition is sufficient for convex bipartite graphs. The closely related problem is HAMILTONIAN PATH whose complexity is open in convex bipartite graphs. We classify the class of convex bipartite graphs as {\em monotone} and {\em non-monotone} graphs. For monotone convex bipartite graphs, we present a linear-time algorithm to output a Hamiltonian path. We believe that these results can be used to obtain algorithms for Hamiltonian path problem in non-monotone convex bipartite graphs. It is important to highlight (a) in \cite{keil,esha}, it is incorrectly claimed that Hamiltonian path problem in convex bipartite graphs is polynomial-time solvable by referring to \cite{muller} which actually discusses Hamiltonian cycle (b) the algorithm appeared in \cite{esha} for the longest path problem (Hamiltonian path problem) in biconvex and convex bipartite graphs have an error and it does not compute an optimum solution always. We present an infinite set of counterexamples in support of our claim.

In the k red (blue) domination problem for a bipartite graph \(G=(X,Y,E)\), we seek a subset \(D \subseteq X\) (respectively \(D \subseteq Y\)) of cardinality at most k that dominates vertices of Y (respectively X). The decision version of this problem is \(\textsc {NP}\)-complete for perfect elimination bipartite graphs but solvable in polynomial time for chordal bipartite graphs. We present a linear time algorithm to solve the minimum cardinality red domination problem for convex bipartite graphs. The algorithm presented is faster and simpler than that in the literature. Due to the asymmetry in convex bipartite graphs, the algorithm does not extend to k blue domination. We present a linear time algorithm to solve the minimum cardinality blue domination problem for convex bipartite graphs.KeywordsConvex bipartite graphRed dominating setBlue dominating set

For a graph \(G=(V,E)\), a set \(M\subseteq E\) is called a matching in G if no two edges in M share a common vertex. A matching M in G is called an induced matching in G if G[M], the subgraph of G induced by M, is same as G[S], the subgraph of G induced by \(S=\{v \in V |\) v is incident on an edge of M\(\}\). The Maximum Induced Matching problem is to find an induced matching of maximum cardinality. Given a graph G and a positive integer k, the Induced Matching Decision problem is to decide whether G has an induced matching of cardinality at least k. The Induced Matching Decision problem is NP-complete on bipartite graphs, but polynomial time solvable for convex bipartite graphs. In this paper, we show that the Induced Matching Decision problem is NP-complete for star-convex bipartite graphs and perfect elimination bipartite graphs. On the positive side, we propose polynomial time algorithms to solve the Maximum Induced Matching problem in circular-convex bipartite graphs and triad-convex bipartite graphs by making polynomial reductions from the Maximum Induced Matching problem in these graph classes to the Maximum Induced Matching problem in convex bipartite graphs.

Circular convex bipartite graphs: Maximum matching and Hamiltonian circuits

Counting independent sets in tree convex bipartite graphs

A bipartite graph G(X, Y) whose vertex set is partitioned into X and Y is a convex bipartite graph, if there is an ordering of $$X=(x_1,\ldots ,x_m)$$ such that for all $$y \in Y$$ , $$N_G(y)$$ is consecutive with respect to the ordering of X, and G is said to have convexity with respect to X. A k-star caterpillar is a tree with a collection of stars with each star having k vertices of degree one whose roots are joined by a path. For a bipartite graph with partitions X and Y, we associate a k-star caterpillar on X such that for each vertex in Y, its neighborhood induces a tree. The minimum Steiner tree problem (STREE) is defined as follows: given a connected graph $$G=(V,E)$$ and a subset of vertices $$R \subseteq V(G)$$ , the objective is to find a minimum cardinality set $$S \subseteq V(G)$$ such that the set $$R \cup S$$ induces a connected subgraph. In this paper, we present the following dichotomy result: we show that STREE is NP-complete for 1-star caterpillar convex bipartite graphs and polynomial-time solvable for 0-star caterpillar convex bipartite graphs (also known as convex bipartite graphs). We also strengthen the well-known result of Müller and Brandstädt (Theoret Comput Sci 53(2-3):257-265, 1987), which says STREE in chordal bipartite graphs is NP-complete (reduction instances are 3-star caterpillar convex bipartite graphs). As an application, we use our STREE results to solve: (i) the classical dominating set problem in convex bipartite graphs, (ii) STREE on interval graphs, linear time.

We show that the computational complexity of the maximum edge biclique (MEB) problem in tree convex bipartite graphs depends on the associated trees. That is, MEB is \(\mathcal {NP}\)-complete for star convex bipartite graphs, but polynomial time solvable for tree convex bipartite graphs whose associated trees have a constant number of leaves. In particular, MEB is polynomial time solvable for triad convex bipartite graphs. Moreover, we show that the same algorithm strategy may not work for circular convex bipartite graphs, and triad convex bipartite graphs are incomparable with respect to chordal bipartite graphs.

For any positive integer k, the total k-domatic partition problem is to partition the vertices of a graph G into k pairwise disjoint total dominating sets. In this paper, we study the problem for planar graphs, chordal bipartite graphs, convex bipartite graphs, and bipartite permutation graphs. We show that the total 3-domatic partition problem on planar graphs is NP-complete. Moreover, we give an alternative algorithm to solve the total k-domatic partition problem for chordal bipartite graphs with weak elimination orderings, and adapt it to solve the problem in linear time for bipartite permutation graphs and convex bipartite graphs even if Gamma-free forms of the adjacency matrices of the considered graphs are not given.

A subset $$M\subseteq E$$ of edges of a graph $$G=(V,E)$$ is called a matching in G if no two edges in M share a common vertex. A matching M in G is called an induced matching if G[M], the subgraph of G induced by M, is the same as G[S], the subgraph of G induced by $$S=\{v \in V |$$ v is incident on an edge of $$M\}$$ . The Maximum Induced Matching problem is to find an induced matching of maximum cardinality. Given a graph G and a positive integer k, the Induced Matching Decision problem is to decide whether G has an induced matching of cardinality at least k. The Maximum Weight Induced Matching problem in a weighted graph $$G=(V,E)$$ in which the weight of each edge is a positive real number, is to find an induced matching such that the sum of the weights of its edges is maximum. It is known that the Induced Matching Decision problem and hence the Maximum Weight Induced Matching problem is known to be NP-complete for general graphs and bipartite graphs. In this paper, we strengthened this result by showing that the Induced Matching Decision problem is NP-complete for star-convex bipartite graphs, comb-convex bipartite graphs, and perfect elimination bipartite graphs, the subclasses of the class of bipartite graphs. On the positive side, we propose polynomial time algorithms for the Maximum Weight Induced Matching problem for circular-convex bipartite graphs and triad-convex bipartite graphs by making polynomial time reductions from the Maximum Weight Induced Matching problem in these graph classes to the Maximum Weight Induced Matching problem in convex bipartite graphs.

Scalable parallel algorithms for maximum matching and Hamiltonian circuit in convex bipartite graphs

A bipartite graph G=(U,W,E) with vertex set V=U∪W is convex if there exists an ordering of the vertices of W such that for each u∈U, the neighbors of u are consecutive in W. A compact representation of a convex bipartite graph for specifying such an ordering can be computed in O(|V|+|E|) time. The paired-domination problem on bipartite graphs has been shown to be NP-complete. The complexity of the paired-domination problem on convex bipartite graphs has remained unknown. In this paper, we present an O(|V|) time algorithm to solve the paired-domination problem on convex bipartite graphs given a compact representation. As a byproduct, we show that our algorithm can be directly applied to solve the total domination problem on convex bipartite graphs in the same time bound.

Parallel recognition of the consecutive ones property with applications

A linear time algorithm for maximum matchings in convex, bipartite graphs

Matchings in convex bipartite graphs correspond to the problem of scheduling unit-length tasks on a single disjunctive resource, given a release time and a deadline for every task. The unweighted case was studied by several authors since Glover first considered the problem in 1967 [Glover, F. 1967. Maximum matching in convex bipartite graphs. Naval Res. Logist. Quart. 14 313–316] and until 1996, when Steiner and Yeomans found an algorithm whose running time is linear in the number of tasks [Steiner, G., J. S. Yeomans. 1996. A linear time algorithm for determining maximum matchings in convex, bipartite graphs. Comput. Math. Appl. 31(12) 91–96]. We address a weighted variant of this problem. Given a node-weighted convex bipartite graph G=(X, Y, E) (where Y is linearly ordered and the neighborhood of each node of X is an interval of Y), we show that it is possible to find an X-perfect matching of maximum (or minimum) weight in O(|E| + |Y| log |X|) time and O(|X| + |Y|) space. For the case in which only the nodes of Y are weighted and their weights are positive, the algorithm can be used to find a maximum-weight (not necessarily X-perfect) matching.

Feedback vertex sets on restricted bipartite graphs