One of the most popular and useful areas of graph theory is graph colorings. A graph coloring is an assignment of integers to the vertices of a graph so that no two adjacent vertices are assigned the same integer. This problem frequently arises in scheduling and channel assignment applications. A list coloring of a graph is an assignment of integers to the vertices of a graph as before with the restriction that the integers must come from specific lists of available colors at each vertex. For a physical application of this problem, consider a wireless network. Due to hardware restrictions, each radio has a limited set of frequencies through which it can communicate, and radios within a certain distance of each other cannot operate on the same frequency without interfering. We model this problem as a graph by representing the wireless radios by vertices and assigning a list to each vertex according to its available frequencies. We then seek a coloring of the graph from these lists. In this thesis, we give an overview of the last thirty years of research in list colorings. We begin with an introduction of the list coloring problem, as defined by Erdös, Rubin, and Taylor in [6]. We continue with a study of variations of the problem, including cases when all the lists have the same length and cases when we allow different lengths. We will briefly mention edge colorings and overview some restricted list colors such as game colorings and L(p, q)-labelings before concluding with a list of open questions. / Master of Science

The famous Four Color Theorem states that any planar graph can be properly colored using at most four colors. However, if we want to properly color the square of a planar graph (or alternatively, color the graph using distinct colors on vertices at distance up to two from each other), we will always require at least \Delta + 1 colors, where \Delta is the maximum degree in the graph. For all \Delta, Wegner constructed planar graphs (even without 3-cycles) that require about \frac{3}{2} \Delta colors for such a coloring. To prove a stronger upper bound, we consider only planar graphs that contain no 4-cycles and no 5-cycles (but which may contain 3-cycles). Zhu, Lu, Wang, and Chen showed that for a graph G in this class with \Delta \ge 9, we can color G^2 using no more than \Delta + 5 colors. In this thesis we improve this result, showing that for a planar graph G with maximum degree \Delta \ge 32 having no 4-cycles and no 5-cycles, at most \Delta + 3 colors are needed to properly color G^2. Our approach uses the discharging method, and the result extends to list-coloring and other related coloring concepts as well.

This work introduces two new parameterizations of graph problems generalizing vertex cover which fill part of the space between vertex cover and clique width in the hierarchy of graf parameterizations. We also study parameterized complexity of Hamiltonian path and cycle, vertex coloring, precoloring extension and equitable coloring parameterized by these two parameterizations. With the exception of precoloring extension which is W[1]-hard in one case, all the other problems listed above are tractable for both parameterizations. The boundary between tractability and intractability of these problems can therefore be moved closer to parameterization by clique width.

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We study the maximum differential coloring problem, where an n-vertex graph must be colored with colors numbered 1, 2...n such that the minimal difference between the two colors of any edge is maximized. This problem is motivated by coloring maps in which not all countries are contiguous. Since it is known that this problem is NP-hard for general graphs; we consider planar graphs and subclasses thereof. In Chapter 1 we introduce the topic of this thesis and in Chapter 2 we review relevant definitions and basic results. In Chapter 3 we prove that the maximum differential coloring problem remains NP-hard even for planar graphs. Then, we present tight bounds for regular caterpillars and spider graphs and close-to-optimal differential coloring algorithms for general caterpillars and biconnected triangle-free outer-planar graphs. In Chapter 4 we introduce the (d, kn)-differential coloring problem. While it was known that the problem of determining whether a general graph is (2, n)-differential colorable is NP-complete, in this chapter we provide a complete characterization of bipartite, planar and outerplanar graphs that admit (2, n)-differential colorings. We show that it is NP-complete to determine whether a graph admits a (3, 2n)-differential coloring. The same negative result holds for the ([2n/3], 2n)-differential coloring problem, even when input graph is planar. In Chapter 5 we experimentally evaluate and compare several algorithms for coloring a map. Motivated by different application scenarios, we classify our approaches into two categories, depending on the dimensionality of the underlying color space. To cope with the one dimensional color space (e.g., gray-scale colors), we employ the (d, kn)-differential coloring. In Chapter 6 we describe a practical approach for visualizing multiple relationships defined on the same dataset using a geographic map metaphor, where clusters of nodes form countries and neighboring countries correspond to nearby clusters. The aim is to provide a visualization that allows us to compare two or more such maps. In the case where we are considering multiple relationships we also provide an interactive tool to visually explore the effect of combining two or more such relationships. Our method ensures good readability and mental map preservation, based on dynamic node placement with node stability, dynamic clustering with cluster stability, and dynamic coloring with color stability. Finally in Chapter 7 we discuss future work and open problems.

The work in this thesis can be divided into two different parts. In the first part, we suggest an approximate edge 3-coloring polynomial time algorithm for cubic graphs. For any cubic graph with n vertices, using this coloring algorithm, we get an edge 3-coloring with at most n/3 error vertices. In the second part, we study Jim Propp's Rotor-Router model on some non-bipartite graph. We find the difference between the number of chips at vertices after performing a walk on this graph using Propp model and the expected number of chips after a random walk. It is known that for line of integers and d-dimenional grid, this deviation is constant. However, it is also proved that for k-ary infinite trees, for some initial configuration the deviation is no longer a constant and say it is D. We present a similar study on some non-bipartite graph constructed from k-ary infinite trees and conclude that for this graph with the same initial configuration, the deviation is almost (k²)D.

A graph is an ordered pair composed by a set of vertices and a set of edges, the latter consisting of unordered pairs of vertices. Two vertices in such a pair are each others neighbors. Two edges are adjacent if they share a common vertex. Denote the amount of edges that share a specific vertex as the degree of the vertex. A proper edge-coloring of a graph is an assignment of colors from some finite set, to the edges of a graph where no two adjacent edges have the same color. A bipartition (X,Y) of a set of vertices V is an ordered pair of two disjoint sets of vertices such that V is the union of X and Y, where all the vertices in X only have neighbors in Y and vice versa. A bipartite graph is a graph whose vertices admit a bipartition (X,Y). Let G be one such graph. An X-interval coloring of G is a proper edge coloring where the colors of the edges incident to each vertex in X form an interval of integers. Denote by χ'int(G,X) the least number of colors needed for an X-interval coloring of G. In this paper we prove that if G is a bipartite graph with maximum degree 3n (n is a natural number), where all the vertices in X have degree 3, then <img src="http://www.diva-portal.org/cgi-bin/mimetex.cgi?%5Cmathit%7B%5Cchi'_%7Bint%7D%5Cleft(G,X%5Cright)%5Cleq%7D%0A%5C%5C%0A%5Cmathit%7B%5Cleft(n-1%5Cright)%5Cleft(3n+5%5Cright)/2+3%7D%0A%5C%5C%0A%5Cmathit%7Bif%20n%20is%20odd,%7D%0A%5C%5C%0A%5Cmathit%7Bor%7D%0A%5C%5C%0A%5Cmathbf%7B3n%5E%7B2%7D/2+1%7D%0A%5C%5C%0A%5Cmathit%7Bif%20n%20is%20even%7D.%0A" />

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[pt] Uma coloração de arestas é a atribuição de cores às arestas de um grafo, de modo que arestas adjacentes não recebam a mesma cor. O menor inteiro positivo para o qual um grafo admite uma coloração de arestas é dito seu índice cromático. Fizemos revisão bibliográfica dos principais resultados conhecidos nessa área. Uma coloração total, por sua vez, é a aplicação de cores aos vértices e arestas de um grafo de modo que elementos adjacentes ou incidentes recebam cores distintas. O número cromático total de um grafo é o menor inteiro positivo para o qual o grafo possui coloração total. Dada uma coloração total, se a diferença entre as cardinalidades de quaisquer duas classes de cor for no máximo um, então dizemos que a coloração é equilibrada e o menor número inteiro positivo que satisfaz essa condição é dito o número cromático total equilibrado do grafo. Para tal valor, Wang (2002) conjecturou um limite superior. Um grafo multipartido completo balanceado é aquele em que o conjunto de vértices pode ser particionado em conjuntos independentes com a mesma quantidade de vértices, sendo adjacentes quaisquer dois vértices de diferentes partes da partição. Determinamos o número cromático total equilibrado dos grafos multipartidos completos balanceados, contribuindo, desta forma, com novos resultados na área de coloração de grafos. / [en] An edge coloring is the assignment of colors to the edges of a graph, so that adjacent edges do not receive the same color. The smallest positive integer for which a graph admits an edge coloring is said to be its chromatic index. We did a literature review of the main known results of this area. A total coloring, in turn, is the application of colors to the vertices and edges of a graph so that adjacent or incident elements receive distinct colors. The total chromatic number of a graph is the least positive integer for which the graph has a total coloring.Given a total coloring, if the difference between the cardinality of any two color classes is at most one, then we say that the coloring is equitable and the smallest positive integer that satisfies this condition is said to be the graph s equitable total chromatic number. For such value, Wang (2002) conjectured an upper bound. A complete multipartite balanced graph is the one in which the set of vertices can be partitioned into independent sets with the same quantity of vertices, being adjacent any two vertices of different parts of the partition. We determine the equitable total chromatic number of complete multipartite graphs, contributing, therefore, with new results in the area of graph coloring.

The classical graph edge coloring problem deals in coloring the edges of a given graph with minimum number of colors such that no two adjacent edges in the graph, get the same color in the proposed coloring. In the following work, we look at the other end of the spectrum where in our goal is to maximize the number of colors used for coloring the edges of the graph under some vertex specific constraints. We deal with the MAXIMUM EDGE COLORING problem which is defined as the following –For an integer q ≥2 and a graph G, the goal is to find a coloring of the edges of G with the maximum number of colors such that every vertex of the graph sees at most q colors. The question is very well motivated by the problem of channel assignment in wireless networks. This problem is NP-hard for q ≥ 2, and has been well-studied from the point of view of approximation. This problem has not been studied in the parameterized context before. Hence as a next step, this thesis investigates the parameterized complexity of this problem where the standard parameter is the solution size. The main focus of the work is the special case of q=2 ,i.e. MAXIMUM EDGE 2-COLORING which is theoretically intricate and practically relevant in the wireless networks setting. We first show an exponential kernel for the MAXIMUM EDGE q-COLORING problem where q is a fixed constant and q ≥ 2.We do a more specific analysis for the kernel of the MAXIMUM EDGE 2-COLORING problem. The kernel obtained here is still exponential in size but is better than the kernel obtained for MAXIMUM EDGE q-COLORING problem in case of q=2. We then show a fixed parameter tractable algorithm for the MAXIMUM EDGE 2-COLORING problem with a running time of O*∗(kO(k)).We also show a fixed parameter tractable algorithm for the MAXIMUM EDGE q-COLORING problem with a running time of O∗(kO(qk) qO(k)). The fixed parameter tractability of the dual parametrization of the MAXIMUM EDGE 2-COLORING problem is established by arguing a linear vertex kernel for the problem. We also show that the MAXIMUM EDGE 2-COLORING problem remains hard on graphs where the maximum degree is a constant and also on graphs without cycles of length four. In both these cases, we obtain quadratic kernels. A closely related variant of the problem is the question of MAX EDGE{1,2-}COLORING. For this problem, the vertices in the input graph may have different qε,{1.2} values and the goal is to use at least k colors for the edge coloring of the graph such that every vertex sees at most q colors, where q is either one or two. We show that the MAX EDGE{1,2}-COLORING problem is W[1]-hard on graphs that have no cycles of length four.