A vertex coloring of a graph G = (V, E) that uses k colors is called an injective k-coloring of G if no two vertices having a common neighbor have the same color. The minimum k for which G has an injective k-coloring ...
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A vertex coloring of a graph G = (V, E) that uses k colors is called an injective k-coloring of G if no two vertices having a common neighbor have the same color. The minimum k for which G has an injective k-coloring is called the injective chromatic number of G. Given a graph G and a positive integer k, the DECIDE INJECTIVE COLORING PROBLEM iS to decide whether G admits an injective k-coloring. It is known that DECIDE INJECTIVE COLORING PROBLEM is NP-complete for bipartite graphs. In this paper, we strengthen this result by showing that this problem remains NP-complete for perfect elimination bipartite graphs, star-convex bipartite graphs and comb-convex bipartite graphs, which are proper subclasses of bipartite graphs. Moreover, we show that for every epsilon > 0, it is not possible to efficiently approximate the injective chromatic number of a perfect elimination bipartite graph within a factor of n(1/3-epsilon) unless ZPP = NP. On the positive side, we propose a linear time algorithm for biconvex bipartite graphs and O(nm) time algorithm for convex bipartite graphs for finding the optimal injective coloring. We prove that the injective chromatic number of a chordal bipartite graph can be determined in polynomial time. It is known that DECIDE INJECTIVE COLORING PROBLEM is NP-complete for chordal graphs. We give a linear time algorithm for computing the injective chromatic number of proper interval graphs, which is a proper subclass of chordal graphs. DECIDE INJECTIVE COLORING PROBLEM is also known to be NP-complete for split graphs. We show that DECIDE INJECTIVE COLORING PROBLEM remains NP-complete for K-1,K-t-free split graphs for t >= 4 and polynomially solvable for t <= 3. (C) 2020 Elsevier B.V. All rights reserved.
We present parameterized algorithms for the k-path problem, the p-packing of q-sets problem, and the q-dimensional p-matching problem. Our algorithms solve these problems with high probability in time exponential only...
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We present parameterized algorithms for the k-path problem, the p-packing of q-sets problem, and the q-dimensional p-matching problem. Our algorithms solve these problems with high probability in time exponential only in the parameter (k, p, q) and using polynomial space. The constant bases of the exponentials are significantly smaller than in previous works;for example, for the k-path problem the improvement is from 2 to 1.66. We also show how to detect if a d-regular graph admits an edge coloring with d colors in time within a polynomial factor of 2((d-1)n/2). Our techniques generalize an algebraic approach studied in various recent works. (c) 2017 Elsevier Inc. All rights reserved.
We study the problem of reconfiguring one list edge-coloring of a graph into another list edge-coloring by changing only one edge color assignment at a time, while at all times maintaining a list edge-coloring, given ...
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We study the problem of reconfiguring one list edge-coloring of a graph into another list edge-coloring by changing only one edge color assignment at a time, while at all times maintaining a list edge-coloring, given a list of allowed colors for each edge. Ito, Kaminski and Demaine gave a sufficient condition so that any list edge-coloring of a tree can be transformed into any other. In this paper, we give a new sufficient condition which improves the known one. Our sufficient condition is best possible in some sense. The proof is constructive, and yields a polynomial-time algorithm that finds a transformation between two given list edge-colorings of a tree with n vertices via O(n(2)) recoloring steps. We remark that the upper bound O(n(2)) on the number of recoloring steps is tight, because there is an infinite family of instances on paths that satisfy our sufficient condition and whose reconfiguration requires Omega(n(2)) recoloring steps.
This paper considers the bandwidth reduction problem for large-scale matrices in serial computations. A heuristic for bandwidth reduction reorders the rows and columns of a given sparse matrix so that the method place...
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This paper considers the bandwidth reduction problem for large-scale matrices in serial computations. A heuristic for bandwidth reduction reorders the rows and columns of a given sparse matrix so that the method places entries with a nonzero value as close to the main diagonal as possible. Bandwidth optimization is a critical issue for many scientific and engineering applications. In this regard, this paper proposes an ant colony hyperheuristic approach for the bandwidth reduction of symmetric and nonsymmetric matrices. The ant colony hyperheuristic approach evolves and selects graph theory bandwidth reduction algorithms for application areas. This paper evaluates the resulting heuristics for bandwidth reduction in each application area against the most promising low-cost heuristics for bandwidth reduction. This paper also includes a numerical examination of the current state-of-the-art metaheuristic algorithms for matrix bandwidth reduction. The results yielded on a wide-ranging set of standard benchmark matrices showed that the proposed approach outperformed state-of-the-art low-cost heuristics for bandwidth reduction when applied to problem cases arising from several application areas, clearly indicating the promise of the proposal. (C) 2020 Elsevier B.V. All rights reserved.
Recently Lexicographic Breadth First Search (LBFS) has received considerable attention and has often been employed in a multi-sweep fashion. One variant of LBFS called LBFS+ breaks ties by choosing the last vertex of ...
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Recently Lexicographic Breadth First Search (LBFS) has received considerable attention and has often been employed in a multi-sweep fashion. One variant of LBFS called LBFS+ breaks ties by choosing the last vertex of the tied set in a previous LBFS. This has motivated the study of vertices that may appear last in an LBFS (called end-vertices). In this paper, we present various theoretical and algorithmic results concerning end-vertices. (C) 2009 Elsevier B.V. All rights reserved.
We find the minimal cutwidth and bisection width values for abelian Cayley graphs with up to 4 generators and present an algorithm for finding the corresponding optimal ordering. We also find minimal cuts of each orde...
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We find the minimal cutwidth and bisection width values for abelian Cayley graphs with up to 4 generators and present an algorithm for finding the corresponding optimal ordering. We also find minimal cuts of each order. (C) 2007 Elsevier B.V. All rights reserved.
SUBgraph RECONFIGURATION is a family of problems focusing on the reachability of the solution space in which feasible solutions are subgraphs, represented either as sets of vertices or sets of edges, satisfying a pres...
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SUBgraph RECONFIGURATION is a family of problems focusing on the reachability of the solution space in which feasible solutions are subgraphs, represented either as sets of vertices or sets of edges, satisfying a prescribed graph structure property. Although there has been previous work that can be categorized as SUBgraph RECONFIGURATION, most of the related results appear under the name of the property under consideration;for example, independent set, clique, and matching. In this paper, we systematically clarify the complexity status of SUBgraph RECONFIGURATION with respect to graph structure properties. (C) 2019 Elsevier B.V. All rights reserved.
Bipartite graphs are widely used to capture the relationships between two types of entities. In bipartite graph analysis, finding the maximum balanced biclique (MBB) is an important problem with numerous applications....
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Bipartite graphs are widely used to capture the relationships between two types of entities. In bipartite graph analysis, finding the maximum balanced biclique (MBB) is an important problem with numerous applications. A biclique is balanced if its two disjoint vertex sets are of equal size. However, in real-world scenarios, each vertex is associated with a weight to denote its properties, such as influence, i.e., weighted bipartite graph. For weighted bipartite graphs, the previous studies for MBB are no longer applicable due to the ignorance of weight. To fill the gap, in this paper, we propose a reasonable definition of "balance" by restricting the weight difference between two sides of a biclique within k. Given a weighted bipartite graph G and a constraint k, we aim to find the maximum k-balanced biclique (Max k BB) with the maximum weight. To address the problem, we first propose an approach based on biclique enumeration on single side of G following the Branch-and-Bound framework. To improve the performance, we further devise three optimization strategies to prune invalid search branches. Moreover, we utilize graph reduction strategy to reduce the redundant search space. Extensive experiments are conducted on 12 real bipartite datasets to demonstrate the efficiency, effectiveness and scalability of our proposed algorithms. The experimental results show that our algorithms can address MBB detection problem efficiently, and the case study demonstrates the effectiveness of our model compared with MBB model.
In this paper, we propose a method which can be used to decompose a 2D or 3D constraint problem into a C-tree. With this decomposition, a geometric constraint problem can be reduced into basic merge patterns, which ar...
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In this paper, we propose a method which can be used to decompose a 2D or 3D constraint problem into a C-tree. With this decomposition, a geometric constraint problem can be reduced into basic merge patterns, which are the smallest problems we need to solve in order to solve the original problem in certain sense. Based on the C-tree decomposition algorithm, we implemented a software package MMP/Geometer. Experimental results show that MMP/Geometer finds the smallest decomposition for all the testing examples efficiently. (c) 2005 Elsevier Ltd. All rights reserved.
Structurally cohesive subgroups are a powerful and mathematically rigorous way to characterize network robustness. Their strength lies in the ability to detect strong connections among vertices that not only have no n...
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Structurally cohesive subgroups are a powerful and mathematically rigorous way to characterize network robustness. Their strength lies in the ability to detect strong connections among vertices that not only have no neighbors in common, but that may be distantly separated in the graph. Unfortunately, identifying cohesive subgroups is a computationally intensive problem, which has limited empirical assessments of cohesion to relatively small graphs of at most a few thousand vertices. We describe here an approach that exploits the properties of cliques, k-cores and vertex separators to iteratively reduce the complexity of the graph to the point where standard algorithms can be used to complete the analysis. As a proof of principle, we apply our method to the cohesion analysis of a 29,462-vertex biconnected component extracted from a 128,151-vertex co-authorship data set. (C) 2016 Elsevier B.V. All rights reserved.
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