The K-Strong Induced Arboricity of a Graph
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A Brief History of Edge-Colorings — with Personal Reminiscences
Discrete Mathematics Letters Discrete Math. Lett. 6 (2021) 38–46 www.dmlett.com DOI: 10.47443/dml.2021.s105 Review Article A brief history of edge-colorings – with personal reminiscences∗ Bjarne Toft1;y, Robin Wilson2;3 1Department of Mathematics and Computer Science, University of Southern Denmark, Odense, Denmark 2Department of Mathematics and Statistics, Open University, Walton Hall, Milton Keynes, UK 3Department of Mathematics, London School of Economics and Political Science, London, UK (Received: 9 June 2020. Accepted: 27 June 2020. Published online: 11 March 2021.) c 2021 the authors. This is an open access article under the CC BY (International 4.0) license (www.creativecommons.org/licenses/by/4.0/). Abstract In this article we survey some important milestones in the history of edge-colorings of graphs, from the earliest contributions of Peter Guthrie Tait and Denes´ Konig¨ to very recent work. Keywords: edge-coloring; graph theory history; Frank Harary. 2020 Mathematics Subject Classification: 01A60, 05-03, 05C15. 1. Introduction We begin with some basic remarks. If G is a graph, then its chromatic index or edge-chromatic number χ0(G) is the smallest number of colors needed to color its edges so that adjacent edges (those with a vertex in common) are colored differently; for 0 0 0 example, if G is an even cycle then χ (G) = 2, and if G is an odd cycle then χ (G) = 3. For complete graphs, χ (Kn) = n−1 if 0 0 n is even and χ (Kn) = n if n is odd, and for complete bipartite graphs, χ (Kr;s) = max(r; s). -
When the Vertex Coloring of a Graph Is an Edge Coloring of Its Line Graph — a Rare Coincidence
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Repository of the Academy's Library When the vertex coloring of a graph is an edge coloring of its line graph | a rare coincidence Csilla Bujt¶as 1;¤ E. Sampathkumar 2 Zsolt Tuza 1;3 Charles Dominic 2 L. Pushpalatha 4 1 Department of Computer Science and Systems Technology, University of Pannonia, Veszpr¶em,Hungary 2 Department of Mathematics, University of Mysore, Mysore, India 3 Alfr¶edR¶enyi Institute of Mathematics, Hungarian Academy of Sciences, Budapest, Hungary 4 Department of Mathematics, Yuvaraja's College, Mysore, India Abstract The 3-consecutive vertex coloring number Ã3c(G) of a graph G is the maximum number of colors permitted in a coloring of the vertices of G such that the middle vertex of any path P3 ½ G has the same color as one of the ends of that P3. This coloring constraint exactly means that no P3 subgraph of G is properly colored in the classical sense. 0 The 3-consecutive edge coloring number Ã3c(G) is the maximum number of colors permitted in a coloring of the edges of G such that the middle edge of any sequence of three edges (in a path P4 or cycle C3) has the same color as one of the other two edges. For graphs G of minimum degree at least 2, denoting by L(G) the line graph of G, we prove that there is a bijection between the 3-consecutive vertex colorings of G and the 3-consecutive edge col- orings of L(G), which keeps the number of colors unchanged, too. -
Linear K-Arboricities on Trees
Discrete Applied Mathematics 103 (2000) 281–287 View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Elsevier - Publisher Connector Note Linear k-arboricities on trees Gerard J. Changa; 1, Bor-Liang Chenb, Hung-Lin Fua, Kuo-Ching Huangc; ∗;2 aDepartment of Applied Mathematics, National Chiao Tung University, Hsinchu 300, Taiwan bDepartment of Business Administration, National Taichung Institue of Commerce, Taichung 404, Taiwan cDepartment of Applied Mathematics, Providence University, Shalu 433, Taichung, Taiwan Received 31 October 1997; revised 15 November 1999; accepted 22 November 1999 Abstract For a ÿxed positive integer k, the linear k-arboricity lak (G) of a graph G is the minimum number ‘ such that the edge set E(G) can be partitioned into ‘ disjoint sets and that each induces a subgraph whose components are paths of lengths at most k. This paper studies linear k-arboricity from an algorithmic point of view. In particular, we present a linear-time algo- rithm to determine whether a tree T has lak (T)6m. ? 2000 Elsevier Science B.V. All rights reserved. Keywords: Linear forest; Linear k-forest; Linear arboricity; Linear k-arboricity; Tree; Leaf; Penultimate vertex; Algorithm; NP-complete 1. Introduction All graphs in this paper are simple, i.e., ÿnite, undirected, loopless, and without multiple edges. A linear k-forest is a graph whose components are paths of length at most k.Alinear k-forest partition of G is a partition of the edge set E(G) into linear k-forests. The linear k-arboricity of G, denoted by lak (G), is the minimum size of a linear k-forest partition of G. -
Interval Edge-Colorings of Graphs
University of Central Florida STARS Electronic Theses and Dissertations, 2004-2019 2016 Interval Edge-Colorings of Graphs Austin Foster University of Central Florida Part of the Mathematics Commons Find similar works at: https://stars.library.ucf.edu/etd University of Central Florida Libraries http://library.ucf.edu This Masters Thesis (Open Access) is brought to you for free and open access by STARS. It has been accepted for inclusion in Electronic Theses and Dissertations, 2004-2019 by an authorized administrator of STARS. For more information, please contact [email protected]. STARS Citation Foster, Austin, "Interval Edge-Colorings of Graphs" (2016). Electronic Theses and Dissertations, 2004-2019. 5133. https://stars.library.ucf.edu/etd/5133 INTERVAL EDGE-COLORINGS OF GRAPHS by AUSTIN JAMES FOSTER B.S. University of Central Florida, 2015 A thesis submitted in partial fulfilment of the requirements for the degree of Master of Science in the Department of Mathematics in the College of Sciences at the University of Central Florida Orlando, Florida Summer Term 2016 Major Professor: Zixia Song ABSTRACT A proper edge-coloring of a graph G by positive integers is called an interval edge-coloring if the colors assigned to the edges incident to any vertex in G are consecutive (i.e., those colors form an interval of integers). The notion of interval edge-colorings was first introduced by Asratian and Kamalian in 1987, motivated by the problem of finding compact school timetables. In 1992, Hansen described another scenario using interval edge-colorings to schedule parent-teacher con- ferences so that every person’s conferences occur in consecutive slots. -
Vizing's Theorem and Edge-Chromatic Graph
VIZING'S THEOREM AND EDGE-CHROMATIC GRAPH THEORY ROBERT GREEN Abstract. This paper is an expository piece on edge-chromatic graph theory. The central theorem in this subject is that of Vizing. We shall then explore the properties of graphs where Vizing's upper bound on the chromatic index is tight, and graphs where the lower bound is tight. Finally, we will look at a few generalizations of Vizing's Theorem, as well as some related conjectures. Contents 1. Introduction & Some Basic Definitions 1 2. Vizing's Theorem 2 3. General Properties of Class One and Class Two Graphs 3 4. The Petersen Graph and Other Snarks 4 5. Generalizations and Conjectures Regarding Vizing's Theorem 6 Acknowledgments 8 References 8 1. Introduction & Some Basic Definitions Definition 1.1. An edge colouring of a graph G = (V; E) is a map C : E ! S, where S is a set of colours, such that for all e; f 2 E, if e and f share a vertex, then C(e) 6= C(f). Definition 1.2. The chromatic index of a graph χ0(G) is the minimum number of colours needed for a proper colouring of G. Definition 1.3. The degree of a vertex v, denoted by d(v), is the number of edges of G which have v as a vertex. The maximum degree of a graph is denoted by ∆(G) and the minimum degree of a graph is denoted by δ(G). Vizing's Theorem is the central theorem of edge-chromatic graph theory, since it provides an upper and lower bound for the chromatic index χ0(G) of any graph G. -
Orienting Fully Dynamic Graphs with Worst-Case Time Bounds⋆
Orienting Fully Dynamic Graphs with Worst-Case Time Bounds? Tsvi Kopelowitz1??, Robert Krauthgamer2 ???, Ely Porat3, and Shay Solomon4y 1 University of Michigan, [email protected] 2 Weizmann Institute of Science, [email protected] 3 Bar-Ilan University, [email protected] 4 Weizmann Institute of Science, [email protected] Abstract. In edge orientations, the goal is usually to orient (direct) the edges of an undirected network (modeled by a graph) such that all out- degrees are bounded. When the network is fully dynamic, i.e., admits edge insertions and deletions, we wish to maintain such an orientation while keeping a tab on the update time. Low out-degree orientations turned out to be a surprisingly useful tool for managing networks. Brodal and Fagerberg (1999) initiated the study of the edge orientation problem in terms of the graph's arboricity, which is very natural in this context. Their solution achieves a constant out-degree and a logarithmic amortized update time for all graphs with constant arboricity, which include all planar and excluded-minor graphs. It remained an open ques- tion { first proposed by Brodal and Fagerberg, later by Erickson and others { to obtain similar bounds with worst-case update time. We address this 15 year old question by providing a simple algorithm with worst-case bounds that nearly match the previous amortized bounds. Our algorithm is based on a new approach of maintaining a combina- torial invariant, and achieves a logarithmic out-degree with logarithmic worst-case update times. This result has applications to various dynamic network problems such as maintaining a maximal matching, where we obtain logarithmic worst-case update time compared to a similar amor- tized update time of Neiman and Solomon (2013). -
Faster Sublinear Approximation of the Number of K-Cliques in Low-Arboricity Graphs
Faster sublinear approximation of the number of k-cliques in low-arboricity graphs Talya Eden ✯ Dana Ron ❸ C. Seshadhri ❹ Abstract science [10, 49, 40, 58, 7], with a wide variety of applica- Given query access to an undirected graph G, we consider tions [37, 13, 53, 18, 44, 8, 6, 31, 54, 38, 27, 57, 30, 39]. the problem of computing a (1 ε)-approximation of the This problem has seen a resurgence of interest because number of k-cliques in G. The± standard query model for general graphs allows for degree queries, neighbor queries, of its importance in analyzing massive real-world graphs and pair queries. Let n be the number of vertices, m be (like social networks and biological networks). There the number of edges, and nk be the number of k-cliques. are a number of clever algorithms for exactly counting Previous work by Eden, Ron and Seshadhri (STOC 2018) ∗ n mk/2 k-cliques using matrix multiplications [49, 26] or combi- gives an O ( 1 + )-time algorithm for this problem n /k nk k natorial methods [58]. However, the complexity of these (we use O∗( ) to suppress poly(log n, 1/ε,kk) dependencies). algorithms grows with mΘ(k), where m is the number of · Moreover, this bound is nearly optimal when the expression edges in the graph. is sublinear in the size of the graph. Our motivation is to circumvent this lower bound, by A line of recent work has considered this question parameterizing the complexity in terms of graph arboricity. from a sublinear approximation perspective [20, 24]. -
The Strong Perfect Graph Theorem
Annals of Mathematics, 164 (2006), 51–229 The strong perfect graph theorem ∗ ∗ By Maria Chudnovsky, Neil Robertson, Paul Seymour, * ∗∗∗ and Robin Thomas Abstract A graph G is perfect if for every induced subgraph H, the chromatic number of H equals the size of the largest complete subgraph of H, and G is Berge if no induced subgraph of G is an odd cycle of length at least five or the complement of one. The “strong perfect graph conjecture” (Berge, 1961) asserts that a graph is perfect if and only if it is Berge. A stronger conjecture was made recently by Conforti, Cornu´ejols and Vuˇskovi´c — that every Berge graph either falls into one of a few basic classes, or admits one of a few kinds of separation (designed so that a minimum counterexample to Berge’s conjecture cannot have either of these properties). In this paper we prove both of these conjectures. 1. Introduction We begin with definitions of some of our terms which may be nonstandard. All graphs in this paper are finite and simple. The complement G of a graph G has the same vertex set as G, and distinct vertices u, v are adjacent in G just when they are not adjacent in G.Ahole of G is an induced subgraph of G which is a cycle of length at least 4. An antihole of G is an induced subgraph of G whose complement is a hole in G. A graph G is Berge if every hole and antihole of G has even length. A clique in G is a subset X of V (G) such that every two members of X are adjacent. -
Acyclic Edge-Coloring of Planar Graphs
Acyclic edge-coloring of planar graphs: ∆ colors suffice when ∆ is large Daniel W. Cranston∗ January 31, 2019 Abstract An acyclic edge-coloring of a graph G is a proper edge-coloring of G such that the subgraph ′ induced by any two color classes is acyclic. The acyclic chromatic index, χa(G), is the smallest ′ number of colors allowing an acyclic edge-coloring of G. Clearly χa(G) ∆(G) for every graph G. Cohen, Havet, and M¨uller conjectured that there exists a constant M≥such that every planar ′ graph with ∆(G) M has χa(G) = ∆(G). We prove this conjecture. ≥ 1 Introduction proper A proper edge-coloring of a graph G assigns colors to the edges of G such that two edges receive edge- distinct colors whenever they have an endpoint in common. An acyclic edge-coloring is a proper coloring acyclic edge-coloring such that the subgraph induced by any two color classes is acyclic (equivalently, the edge- ′ edges of each cycle receive at least three distinct colors). The acyclic chromatic index, χa(G), is coloring the smallest number of colors allowing an acyclic edge-coloring of G. In an edge-coloring ϕ, if a acyclic chro- color α is used incident to a vertex v, then α is seen by v. For the maximum degree of G, we write matic ∆(G), and simply ∆ when the context is clear. Note that χ′ (G) ∆(G) for every graph G. When index a ≥ we write graph, we forbid loops and multiple edges. A planar graph is one that can be drawn in seen by planar the plane with no edges crossing. -
NP-Completeness of List Coloring and Precoloring Extension on the Edges of Planar Graphs
NP-completeness of list coloring and precoloring extension on the edges of planar graphs D´aniel Marx∗ 17th October 2004 Abstract In the edge precoloring extension problem we are given a graph with some of the edges having a preassigned color and it has to be decided whether this coloring can be extended to a proper k-edge-coloring of the graph. In list edge coloring every edge has a list of admissible colors, and the question is whether there is a proper edge coloring where every edge receives a color from its list. We show that both problems are NP-complete on (a) planar 3-regular bipartite graphs, (b) bipartite outerplanar graphs, and (c) bipartite series-parallel graphs. This improves previous results of Easton and Parker [6], and Fiala [8]. 1 Introduction In graph vertex coloring we have to assign colors to the vertices such that neighboring vertices receive different colors. Starting with [7] and [28], a gener- alization of coloring was investigated: in the list coloring problem each vertex can receive a color only from its prescribed list of admissible colors. In the pre- coloring extension problem a subset W of the vertices have preassigned colors and we have to extend this precoloring to a proper coloring of the whole graph, using only colors from a given color set C. It can be viewed as a special case of list coloring: the list of a precolored vertex consists of a single color, while the list of every other vertex is C. A thorough survey on list coloring, precoloring extension, and list chromatic number can be found in [26, 1, 12, 13]. -
31 Aug 2020 Injective Edge-Coloring of Sparse Graphs
Injective edge-coloring of sparse graphs Baya Ferdjallah1,4, Samia Kerdjoudj 1,5, and André Raspaud2 1LIFORCE, Faculty of Mathematics, USTHB, BP 32 El-Alia, Bab-Ezzouar 16111, Algiers, Algeria 2LaBRI, Université de Bordeaux, 351 cours de la Libération, 33405 Talence Cedex, France 4Université de Boumerdès, Avenue de l’indépendance, 35000, Boumerdès, Algeria 5Université de Blida 1, Route de Soumâa BP 270, Blida, Algeria September 1, 2020 Abstract An injective edge-coloring c of a graph G is an edge-coloring such that if e1, e2, and e3 are three consecutive edges in G (they are consecutive if they form a path or a cycle of length three), then e1 and e3 receive different colors. The minimum integer k such that, G has an injective edge-coloring with k ′ colors, is called the injective chromatic index of G (χinj(G)). This parameter was introduced by Cardoso et al. [12] motivated by the Packet Radio Network ′ problem. They proved that computing χinj(G) of a graph G is NP-hard. We give new upper bounds for this parameter and we present the rela- tionships of the injective edge-coloring with other colorings of graphs. The obtained general bound gives 8 for the injective chromatic index of a subcubic graph. If the graph is subcubic bipartite we improve this last bound. We prove that a subcubic bipartite graph has an injective chromatic index bounded by arXiv:1907.09838v2 [math.CO] 31 Aug 2020 6. We also prove that if G is a subcubic graph with maximum average degree 7 8 less than 3 (resp. -
Induced Path Factors of Regular Graphs Arxiv:1809.04394V3 [Math.CO] 1
Induced path factors of regular graphs Saieed Akbari∗ Daniel Horsley† Ian M. Wanless† Abstract An induced path factor of a graph G is a set of induced paths in G with the property that every vertex of G is in exactly one of the paths. The induced path number ρ(G) of G is the minimum number of paths in an induced path factor of G. We show that if G is a connected cubic graph on n > 6 vertices, then ρ(G) 6 (n − 1)=3. Fix an integer k > 3. For each n, define Mn to be the maximum value of ρ(G) over all connected k-regular graphs G on n vertices. As n ! 1 with nk even, we show that ck = lim(Mn=n) exists. We prove that 5=18 6 c3 6 1=3 and 3=7 6 c4 6 1=2 and that 1 1 ck = 2 − O(k− ) for k ! 1. Keywords: Induced path, path factor, covering, regular graph, subcubic graph. Classifications: 05C70, 05C38. 1 Introduction We denote the path of order n by Pn. A subgraph H of a graph G is said to be induced if, for any two vertices x and y of H, x and y are adjacent in H if and only if they are adjacent in G. An induced path factor (IPF) of a graph G is a set of induced paths in G with the property that every vertex of G is in exactly one of the paths. We allow paths of any length in an IPF, including the trivial path P1.