A common representational style for drawing graphs is the so-called circular drawings, where vertices are represented as points on a circle, and edges are represented as straight line segments. In such drawings, edges...
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A common representational style for drawing graphs is the so-called circular drawings, where vertices are represented as points on a circle, and edges are represented as straight line segments. In such drawings, edges may cross;these edge crossings have a negative effect on human readability. Recent empirical research shows that increasing the angles of edge crossings reduces the negative effect of crossings on human readability. This result has motivated a number of recent investigations of right angle crossing graph drawings, where each crossing angle is The main result of this paper is a characterization of graphs that admit a circular right angle crossing drawing. We present a linear-time algorithm for testing and constructing such a drawing of a graph, if it exists. Further, we give an upper bound on the number of edges in a circular right angle crossing drawing, and we note that the optimization problem of constructing circular drawings with large angle crossings can be formulated as a quadratic programming problem. (C) 2016 Elsevier B.V. All rights reserved.
We consider the minimum cost edge installation problem (MCEI) in a graph G = (V, E) with edge weight w(e) >= 0. e is an element of E We are given a vertex s is an element of V designated as a sink, an edge capacity...
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We consider the minimum cost edge installation problem (MCEI) in a graph G = (V, E) with edge weight w(e) >= 0. e is an element of E We are given a vertex s is an element of V designated as a sink, an edge capacity lambda > 0. and a source set S subset of V with demand q(v) is an element of |0,lambda|, v is an element of S For each edge e is an element of E. we are allowed to install an integer number h(e) of copies of e MCEI asks to send demand q(v) from each source v is an element of S along a single path P-v to the sink without splitting the demand of any source v is an element of S For each edge e is an element of E. a set of such paths can pass through a single copy of e in C as long as the total demand along the paths does not exceed the edge capacity lambda The objective is to find a set P = {P-v | v is an element of S} of paths of G that minimizes the installing cost Sigma(eCE) h(e)w(e) In this paper. we propose a (15/8 + rho(ST))-approximation algorithm to MCEI. where rho(SI) is any approximation ratio achievable tor the Steiner tree problem
We extend the main result by Dorn, Keicher, and Sikolya from [Math. Z., 263 (2009), pp. 69-87] on the asymptotic periodicity of flows in infinite networks. To this purpose we develop an algorithmic perturbation techni...
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We extend the main result by Dorn, Keicher, and Sikolya from [Math. Z., 263 (2009), pp. 69-87] on the asymptotic periodicity of flows in infinite networks. To this purpose we develop an algorithmic perturbation technique for infinite networks allowing us to change edge lengths without changing the asymptotic behavior. The asymptotic limit is identified with a (periodic) flow in a factor network consisting of a single loop.
Dense sub-graphs of sparse graphs (communities), which appear in most real-world complex networks, play an important role in many contexts. Most existing community detection algorithms produce a hierarchical structure...
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Dense sub-graphs of sparse graphs (communities), which appear in most real-world complex networks, play an important role in many contexts. Most existing community detection algorithms produce a hierarchical structure of communities and seek a partition into communities that optimizes a given quality function. We propose new methods to improve the results of any of these algorithms. First we show how to optimize a general class of additive quality functions (containing the modularity, the performance, and a new similarity based quality function which we propose) over a larger set of partitions than the classical methods. Moreover, we define new multi-scale quality functions which make it possible to detect different scales at which meaningful community structures appear, while classical approaches find only one partition. (C) 2010 Elsevier B.V. All rights reserved.
This paper studies a variant of the graph partitioning problem, called the evacuation planning problem, which asks us to partition a target area, represented by a graph, into several regions so that each region contai...
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This paper studies a variant of the graph partitioning problem, called the evacuation planning problem, which asks us to partition a target area, represented by a graph, into several regions so that each region contains exactly one shelter. Each region must be convex to reduce intersections of evacuation routes, the distance between each point to a shelter must be bounded so that inhabitants can quickly evacuate from a disaster, and the number of inhabitants assigned to each shelter must not exceed the capacity of the shelter. This paper formulates the convexity of connected components as a spanning shortest path forest for general graphs, and proposes a novel algorithm to tackle this multi-objective optimization problem. The algorithm not only obtains a single partition but also enumerates all partitions simultaneously satisfying the above complex constraints, which is difficult to be treated by existing algorithms, using zero-suppressed binary decision diagrams (ZDDs) as a compressed expression. The efficiency of the proposed algorithm is confirmed by the experiments using real-world map data. The results of the experiments show that the proposed algorithm can obtain hundreds of millions of partitions satisfying all the constraints for input graphs with a hundred of edges in a few minutes.
The anti-Ramsey number, ar(G, H) is the minimum integer k such that in any edge colouring of G with k colours there is a rainbow subgraph isomorphic to H, namely, a copy of H with each of its edges assigned a differen...
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The anti-Ramsey number, ar(G, H) is the minimum integer k such that in any edge colouring of G with k colours there is a rainbow subgraph isomorphic to H, namely, a copy of H with each of its edges assigned a different colour. The notion was introduced by Erdos and Simonovits in 1973. Since then the parameter has been studied extensively. The case when H is a star graph was considered by several graph theorists from the combinatorial point of view. Recently this case received the attention of researchers from the algorithm community because of its applications in interface modelling of wireless networks. To the algorithm community, the problem is known as maximum edge q-colouring problem: Find a colouring of the edges of G, maximizing the number of colours satisfying the constraint that each vertex spans at most q colours on its incident edges. It is easy to see that the maximum value of the above optimization problem equals ar(G, K1,q+1) - 1. In this paper, we study the maximum edge 2-colouring problem from the approx-imation algorithm point of view. The case q = 2 is particularly interesting due to its application in real-life problems. algorithmically, this problem is known to be NP-hard for q - 2. For the case of q = 2, it is also known that no polynomial-time algorithm can approximate to a factor less than 3/2 assuming the unique games conjecture. Feng et al. showed a 2-approximation algorithm for this problem. Later Adamaszek and Popa presented a 5/3-approximation algorithm with the additional assumption that the input graph has a perfect matching. Note that the obvious but the only known algorithm issues different colours to the edges of a maximum matching (say M) and different colours to the connected components of G \ M. In this article, we give a new analysis of the aforementioned algorithm to show that for triangle-free graphs with perfect matching the approximation ratio is 8/5. We also show that this algorithm cannot achieve a factor better than 58/37 o
The NP-complete CLOSEST 4-LEAF POWER problem asks, given an undirected graph, whether it can be modified by at most r edge insertions or deletions such that it becomes a 4-leaf power. Herein, a 4-leaf power is a graph...
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The NP-complete CLOSEST 4-LEAF POWER problem asks, given an undirected graph, whether it can be modified by at most r edge insertions or deletions such that it becomes a 4-leaf power. Herein, a 4-leaf power is a graph that can be constructed by considering an unrooted tree-the 4-leaf root-with leaves one-to-one labeled by the graph vertices, where we connect two graph vertices by an edge iff their corresponding leaves are at distance at most 4 in the tree. Complementing previous work on CLOSEST 2-LEAF POWER and CLOSEST 3-LEAF POWER, we give the first algorithmic result for CLOSEST 4-LEAF POWER, showing that CLOSEST 4-LEAF POWER is fixed-parameter tractable with respect to the parameter r. (C) 2008 Elsevier B.V. All rights reserved.
The structure of a large network (graph) can often be revealed by partitioning it into smaller and possibly more dense sub-networks that are easier to handle. One of such decompositions is based on "k-cores"...
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The structure of a large network (graph) can often be revealed by partitioning it into smaller and possibly more dense sub-networks that are easier to handle. One of such decompositions is based on "k-cores", proposed in 1983 by Seidman. Together with connectivity components, cores are one among few concepts that provide efficient decompositions of large graphs and networks. In this paper we propose an efficient algorithm for determining the cores decomposition of a given network with complexity O(m), where m is the number of lines (edges or arcs). In the second part of the paper the classical concept of k-core is generalized in a way that uses a vertex property function instead of degree of a vertex. For local monotone vertex property functions the corresponding generalized cores can be determined in O(***(Delta, log n)) time, where n is the number of vertices and Delta is the maximum degree. Finally the proposed algorithms are illustrated by the analysis of a collaboration network in the field of computational geometry.
A graph G is called a pairwise compatibility graph (PCG, for short) if it admits a tuple (T, w, d min, d max) of a tree T whose leaf set is equal to the vertex set of G, a non-negative edge weight w, and two non-negat...
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A graph G is called a pairwise compatibility graph (PCG, for short) if it admits a tuple (T, w, d min, d max) of a tree T whose leaf set is equal to the vertex set of G, a non-negative edge weight w, and two non-negative reals d min = d max such that G has an edge between two vertices u, v. V if and only if the distance between the two leaves u and v in the weighted tree (T, w) is in the interval [d min, d max]. The tree T is also called a witness tree of the PCG G. How to recognize PCGs is a wide-open problem in the literature. This paper gives a complete characterization for a graph to be a star-PCG (a PCG that admits a star as its witness tree), which provides us the first polynomial-time algorithm for recognizing star-PCGs.
The group nearest neighbor (GNN) search on a road network G(r), i.e., finding the spatial objects as activity assembly points with the smallest sum of distances to query users on G(r), has been extensively studied;how...
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The group nearest neighbor (GNN) search on a road network G(r), i.e., finding the spatial objects as activity assembly points with the smallest sum of distances to query users on G(r), has been extensively studied;however, previous works neglected the fact that social relationships among query users, which ensure the maximally favorable atmosphere in the activity, can play an important role in GNN queries. Meanwhile, the ratings of spatial objects can also be used as recommended guidelines. Many real-world applications, such as location-based social networking services, require such queries. In this paper, we study two new problems: (1) a GNN search on a road network that incorporates cohesive social relationships (CGNN) and (2) a CGNN query under multi-criteria (MCGNN). Specifically, both the query users of highest closeness and the corresponding top-j objects are retrieved. To address critical challenges on the effectiveness of results and the efficiency of computation over large road-social networks: (1) for CGNN, we propose a filtering-and-verification framework. During filtering, we prune substantial unpromising users and objects using social and geospatial constraints. During verification, we obtain the object candidates, among which the top j are selected, with respect to the qualified users;(2) for MCGNN, we propose threshold-based selection and expansion strategies, where different strict boundaries are proposed to ensure that correct top-j objects are found early. Moreover, we further optimize search strategies to improve query performance. Finally, experimental results on real social and road networks significantly demonstrate the efficiency and efficacy of our solutions.
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