Dissertations / Theses on the topic 'Graph problems'

This document is a long abstract of my research work, concerning graph theory and algorithms on graphs. It summarizes some results, gives ideas of the proof for some of them and presents the context of the different topics together with some interesting open questions connected to them The first part precises the notations used in the rest of the paper; the second part deals with some problems on cycles in digraphs; the third part is an overview of two graph coloring problems and one problem on structures in colored graphs; finally the fourth part focus on some results in algorithmic graph theory, mainly in parametrized complexity.

Erdos proved the well-known result that every graph has a spanning, bipartite subgraph such that every vertex has degree at least half of its original degree. Bollobas and Scott conjectured that one can get a slightly weaker result if we require the subgraph to be not only spanning and bipartite, but also balanced. We prove this conjecture for graphs of maximum degree 3. The majority of the paper however, will focus on graph tiling. Graph tiling (or sometimes referred to as graph packing) is where, given a graph H, we find a spanning subgraph of some larger graph G that consists entirely of disjoint copies of H. With the Regularity Lemma and the Blow-up Lemma as our main tools, we prove an asymptotic minimum degree condition for an arbitrary bipartite graph G to be tiled by another arbitrary bipartite graph H. This proves a conjecture of Zhao and also implies an asymptotic version of a result of Kuhn and Osthus for bipartite graphs.

A graph G is called planar if it can be drawn on the plan such that no two distinct edges intersect each other but at common endpoints. Such drawing is called a plane embedding of G. A plane graph is a graph with a fixed embedding. A straight-line drawing G of a graph G = (V, E) is a drawing where each vertex of V is drawn as a distinct point on the plane and each edge of G is drawn as a line segment connecting two end vertices. In this thesis, we study a set of planar graph drawing problems.

First, we consider the problem of monotone drawing: A path P in a straight line drawing Γ is monotone if there exists a line l such that the orthogonal projections of the vertices of P on l appear along l in the order they appear in P. We call l a monotone line (or monotone direction) of P. G is called a monotone drawing of G if it contains at least one monotone path P_uw between every pair of vertices u,w of G. Monotone drawings were recently introduced by Angelini et al. and represent a new visualization paradigm, and is also closely related to several other important graph drawing problems. As in many graph drawing problems, one of the main concerns of this research is to reduce the drawing size, which is the size of the smallest integer grid such that every graph in the graph class can be drawn in such a grid. We present two approaches for the problem of monotone drawings of trees. Our first approach show that every n-vertex tree T admits a monotone drawing on a grid of size O(n^1.205) × O( n^1.205) grid. Our second approach further reduces the size of drawing to 12n × 12n, which is asymptotically optimal. Both of our two drawings can be constructed in O(n) time.

We also consider monotone drawings of 3-connected plane graphs. We prove that the classical Schnyder drawing of 3-connected plane graphs is a monotone drawing on a f × f grid, which can be constructed in O(n) time.

Second, we consider the problem of orthogonal drawing. An orthogonal drawing of a plane graph G is a planar drawing of G such that each vertex of G is drawn as a point on the plane, and each edge is drawn as a sequence of horizontal and vertical line segments with no crossings. Orthogonal drawing has attracted much attention due to its various applications in circuit schematics, relationship diagrams, data flow diagrams etc. . Rahman et al. gave a necessary and sufficient condition for a plane graph G of maximum degree 3 to have an orthogonal drawing without bends. An orthogonal drawing D(G) is orthogonally convex if all faces of D(G) are orthogonally convex polygons. Chang et al. gave a necessary and sufficient condition (which strengthens the conditions in the previous result) for a plane graph G of maximum degree 3 to have an orthogonal convex drawing without bends. We further strengthen the results such that if G satisfies the same conditions as in previous papers, it not only has an orthogonally convex drawing, but also a stronger star-shaped orthogonal drawing.

Given a graph, a matching is a set of vertex-disjoint edges. Graph matchings have been well studied, since they play a fundamental role in algorithmic theory as well as motivate many practical applications. Of particular interest is the problem of finding a maximum cardinality matching of a graph. Also of interest is the weighted variant: the problem of computing a minimum-cost maximum cardinality matching. For an arbitrary graph with m edges and n vertices, there are known, long-standing combinatorial algorithms that compute a maximum cardinality matching in O(m\sqrt{n}) time. For graphs with non-negative integer edge costs at most C, it is known how to compute a minimum-cost maximum cardinality matching in roughly O(m\sqrt{n} log(nC)) time using combinatorial methods. While non-combinatorial methods exist, they are generally impractical and not well understood due to their complexity. As a result, there is great interest in obtaining faster matching algorithms that are purely combinatorial in nature. Improving existing combinatorial algorithms for arbitrary graphs is considered to be a very difficult problem. To make the problem more approachable, it is desirable to make some additional assumptions about the graph. For our work, we make two such assumptions. First, we assume the graph is bipartite. Second, we assume that the graph has a small balanced separator, meaning it is possible to split the graph into two roughly equal-size components by removing a relatively small portion of the graph. Several well-studied classes of graphs have separator-like properties, including planar graphs, minor-free graphs, and geometric graphs. For such graphs, we describe a framework, a general set of techniques for designing efficient algorithms. We demonstrate this framework by applying it to yield polynomial-factor improvements for several open-problems in bipartite matching.
Doctor of Philosophy
Assume we are given a list of objects, and a list of compatible pairs of these objects. A matching consists of a chosen subset of these compatible pairs, where each object participates in at most one chosen pair. For any chosen pair of objects, we say the these two objects are matched. Generally, we seek to maximize the number of compatible matches. A maximum cardinality matching is a matching with the largest possible size. In many cases, there are multiple options for maximizing the number of compatible pairings. While maximizing the size of the matching is often the primary concern, one may also seek to minimize the cost of the matching. This is known as the minimum-cost maximum-cardinality matching problem. These two matching problems have been well studied, since they play a fundamental role in algorithmic theory as well as motivate many practical applications. Our interest is in the design of algorithms for both of these problems that are efficiently scalable, even as the number of objects involved grows very large. To aid in the design of scalable algorithms, we observe that some inputs have good separators, meaning that by removing some subset S of objects, one can divide the remaining objects into two sets V and V', where all pairs of objects between V and V' are incompatible. We design several new algorithms that exploit good separators, and prove that these algorithms scale better than previously existing approaches.

Thesis: Ph. D., Massachusetts Institute of Technology, Department of Mathematics, 2015.
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pages 149-156).
A graph G is r-Ramsey minimal with respect to a graph H if every r-coloring of the edges of G yields a monochromatic copy of H, but the same is not true for any proper subgraph of G. The study of the properties of graphs that are Ramsey minimal with respect to some H and similar problems is known as graph Ramsey theory; we study several problems in this area. Burr, Erdös, and Lovász introduced s(H), the minimum over all G that are 2- Ramsey minimal for H of [delta](G), the minimum degree of G. We find the values of s(H) for several classes of graphs H, most notably for all 3-connected bipartite graphs which proves many cases of a conjecture due to Szabó, Zumstein, and Zürcher. One natural question when studying graph Ramsey theory is what happens when, rather than considering all 2-colorings of a graph G, we restrict to a subset of the possible 2-colorings. Erdös and Hajnal conjectured that, for any fixed color pattern C, there is some [epsilon] > 0 so that every 2-coloring of the edges of a Kn, the complete graph on n vertices, which doesn't contain a copy of C contains a monochromatic clique on n[epsilon] vertices. Hajnal generalized this conjecture to more than 2 colors and asked in particular about the case when the number of colors is 3 and C is a rainbow triangle (a K3 where each edge is a different color); we prove Hajnal's conjecture for rainbow triangles. One may also wonder what would happen if we wish to cover all of the vertices with monochromatic copies of graphs. Let F = {F₁, F₂, . . .} be a sequence of graphs such that Fn is a graph on n vertices with maximum degree at most [delta]. If each Fn is bipartite, then the vertices of any 2-edge-colored complete graph can be partitioned into at most 2C[delta] vertex disjoint monochromatic copies of graphs from F, where C is an absolute constant. This result is best possible, up to the constant C.
by Andrey Vadim Grinshpun.
Ph. D.

Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2018.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 189-199).
In the face of massive data sets, classical algorithmic models, where the algorithm reads the entire input, performs a full computation, then reports the entire output, are rendered infeasible. To handle these data sets, alternative algorithmic models are suggested to solve problems under the restricted, namely sub-linear, resources such as time, memory or randomness. This thesis aims at addressing these limitations on graph problems and combinatorial optimization problems through a number of different models. First, we consider the graph spanner problem in the local computation algorithm (LCA) model. A graph spanner is a subgraph of the input graph that preserves all pairwise distances up to a small multiplicative stretch. Given a query edge from the input graph, the LCA explores a sub-linear portion of the input graph, then decides whether to include this edge in its spanner or not - the answers to all edge queries constitute the output of the LCA. We provide the first LCA constructions for 3 and 5-spanners of general graphs with almost optimal trade-offs between spanner sizes and stretches, and for fixed-stretch spanners of low maximum-degree graphs. Next, we study the set cover problem in the oracle access model. The algorithm accesses a sub-linear portion of the input set system by probing for elements in a set, and for sets containing an element, then computes an approximate minimum set cover: a collection of an approximately-minimum number of sets whose union includes all elements. We provide probe-efficient algorithms for set cover, and complement our results with almost tight lower bound constructions. We further extend our study to the LP-relaxation variants and to the streaming setting, obtaining the first streaming results for the fractional set cover problem. Lastly, we design local-access generators for a collection of fundamental random graph models. We demonstrate how to generate graphs according to the desired probability distribution in an on-the-fly fashion. Our algorithms receive probes about arbitrary parts of the input graph, then construct just enough of the graph to answer these probes, using only polylogarithmic time, additional space and random bits per probe. We also provide the first implementation of random neighbor probes, which is a basic algorithmic building block with applications in various huge graph models.
by Anak Yodpinyanee.
Ph. D.

Cette thèse considère deux problèmes de disposition des graphes : le problème de la bande passante cyclique (CBP) et le problème de l’agencement linéaire minimum (MinLA). Le CBP est une extension naturelle du problème de minimisation de la bande passante (BMP) et le MinLA est un problème de somme minimale. Ces problèmes sont largement appliqués dans la vie réelle. Puisqu’ils sont NP-difficile, il est difficile de les résoudre dans le cas général. Par conséquent, cette thèse est consacrée au développement d’algorithmes heuristiques efficaces pour faire face à ces problèmes. Plus précisément, nous introduisons deux algorithmes de recherche locale itétée, un algorithme mémétique avec différents opérateurs de recombinaison pour le CBP et une heuristique de voisinage basée sur un ensemble pour résoudre le MinLA. On montre expérimentalement que pour le CBP, les deux algorithmes de recherche locale itéré pouvaient concurrencer favorablement les méthodes de l’état de l’art, le croisement approprié est identifié pour l’algorithme mémétique. On montre également que pour le MinLA, l’heuristique de voisinage basée sur l’ensemble s’est avérée plus efficace que des algorithmes avec voisinage traditionnel à 2-flip
This thesis considers two graph layout problems: the cyclic bandwidth problem (CBP) and the minimum linear arrangement problem (MinLA). The CBP is a natural extension of the bandwidth minimization problem (BMP) and the MinLA is a min-sum problem. These problems are widely applied in the real life. Since they are NP-hard problems, it is computational difficult to solve them in the general case. Therefore, this thesis is dedicated to developing effective heuristic algorithms to deal with these challenging problems.Specifically, we introduce two iterated local search algorithms, a memetic algorithm with different recombination operators for the CBP and a set based neighborhood heuristic algorithm to solve the MinLA. The two iterated local search algorithms are experimentallydemonstrated to be able to compete favourably with state-of-the-art methods, the feature of a suitable crossover for the memetic algorithm is identified for the CBP and the set based neighborhood heuristic algorithm is proven to be more efficient than the traditional 2-flip neighborhood algorithm

Cette thèse concerne quatre problèmes de coloration de graphes NPdifficiles, à savoir le problème de coloration (GCP), le problème de coloration équitable (ECP), le problème de coloration des sommets pondérés et le problème de sous-graphe critique (k-VCS). Ces problèmes sont largement étudiés dans la littérature, non seulement pour leur difficulté théorique, mais aussi pour leurs applications réelles dans de nombreux domaines. Étant donné qu'ils appartiennent à la classe de problèmes NP-difficiles, il est difficile de les résoudre dans le cas général de manière exacte. Pour cette raison, cette thèse est consacrée au développement d'approches heuristiques pour aborder ces problèmes complexes. Plus précisément, nous développons un algorithme mémétique de réduction (RMA) pour la coloration des graphes, un algorithme de recherche réalisable et irréalisable (FISA) pour la coloration équitable et un réalisable et irréalisable (AFISA) pour le problème de coloration des sommets pondérés et un algorithme de suppression basé sur le retour en arrière (IBR) pour le problème k-VCS. Tous les algorithmes ont été expérimentalement évalués et comparés aux méthodes de l'état de l'art
This thesis concerns four NP-hard graph coloring problems, namely, graph coloring (GCP), equitable coloring (ECP), weighted vertex coloring (WVCP) and k-vertex-critical subgraphs (k-VCS). These problems are extensively studied in the literature not only for their theoretical intractability, but also for their real-world applications in many domains. Given that they belong to the class of NP-hard problems, it is computationally difficult to solve them exactly in the general case. For this reason, this thesis is devoted to developing effective heuristic approaches to tackle these challenging problems. We develop a reduction memetic algorithm (RMA) for the graph coloring problem, a feasible and infeasible search algorithm (FISA) for the equitable coloring problem, an adaptive feasible and infeasible search algorithm (AFISA) for the weighted vertex coloring problem and an iterated backtrack-based removal (IBR) algorithm for the k-VCS problem. All these algorithms were experimentally evaluated and compared with state-of-the-art methods

Graph algorithms are concerned with the algorithmic aspects of solving graph problems. The problems are motivated from and have application to diverse areas of computer science, engineering and other disciplines. Problems arising from these areas of application are good candidates for parallelization since they often have both intense computational needs and stringent response time requirements. Motivated by these concerns, this thesis investigates parallel algorithms for these kinds of graph problems that have at least one of the following properties: the problems involve some type of dynamic updates; the sparsification technique is applicable; or the problems are closely related to communications network issues. The models of parallel computation used in our studies are the Parallel Random Access Machine (PRAM) model and the practical interconnection network models such as meshes and hypercubes. ¶ Consider a communications network which can be represented by a graph G = (V;E), where V is a set of sites (processors), and E is a set of links which are used to connect the sites (processors). In some cases, we also assign weights and/or directions to the edges in E. Associated with this network, there are many problems such as (i) whether the network is k-edge (k-vertex) connected withfixed k; (ii) whether there are k-edge (k-vertex) disjoint paths between u and v for a pair of given vertices u and v after the network is dynamically updated by adding and/or deleting an edge etc; (iii) whether the sites in the network can communicate with each other when some sites and links fail; (iv) identifying the first k edges in the network whose deletion will result in the maximum increase in the routing cost in the resulting network for fixed k; (v) how to augment the network at optimal cost with a given feasible set of weighted edges such that the augmented network is k-edge (k-vertex) connected; (vi) how to route messages through the network efficiently. In this thesis we answer the problems mentioned above by presenting efficient parallel algorithms to solve them. As far as we know, most of the proposed algorithms are the first ones in the parallel setting. ¶ Even though most of the problems concerned in this thesis are related to communications networks, we also study the classic edge-coloring problem. The outstanding difficulty to solve this problem in parallel is that we do not yet know whether or not it is in NC. In this thesis we present an improved parallel algorithm for the problem which needs [bigcircle]([bigtriangleup][superscript 4.5]log [superscript 3] [bigtriangleup] log n + [bigtriangleup][superscript 4] log [superscript 4] n) time using [bigcircle](n[superscript 2][bigtriangleup] + n[bigtriangleup][superscript 3]) processors, where n is the number of vertices and [bigtriangleup] is the maximum vertex degree. Compared with a previously known result on the same model, we improved by an [bigcircle]([bigtriangleup][superscript 1.5]) factor in time. The non-trivial part is to reduce this problem to the edge-coloring update problem. We also generalize this problem to the approximate edge-coloring problem by giving a faster parallel algorithm for the latter case. ¶ Throughout the design and analysis of parallel graph algorithms, we also find a technique called the sparsification technique is very powerful in the design of efficient sequential and parallel algorithms on dense undirected graphs. We believe that this technique may be useful in its own right for guiding the design of efficient sequential and parallel algorithms for problems in other areas as well as in graph theory.

Paul Gunther (1966), proved the following result: Given a continuous function f on a compact surface M of constant curvature -1 and its periodic lift g to the universal covering, the hyperbolic plane, then the averages of the lift g over increasing spheres converge to the average of the function f over the surface M. Heinz Huber (1956) considered the following problem on the hyperbolic plane H: Consider a strictly hyperbolic subgroup of automorphisms on H with compact quotient, and choose a conjugacy class in this group. Count the number of vertices inside an increasing ball, which are images of a fixed point x in H under automorphisms in the chosen conjugacy class, and describe the asymptotic behaviour of this number as the size of the ball goes to infinity. In this thesis, we use a well-known analogy between the hyperbolic plane and the regular tree to solve the above problems, and some related ones, on a tree. We deal mainly with regular trees, however some results incorporate more general graphs.

Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2017.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 237-255).
Distributed graph algorithms provide efficient and theoretically sound methods for solving graph problems in distributed settings and more generally for performing distributed computation in networks. These algorithms are applicable in a wide variety of settings, ranging from computer networks to massively parallel computing and beyond. This thesis addresses a number of the central problems of distributed graph algorithms. These problems generally revolve around two of the principal challenges of the area, locality and congestion. The problems include computing maximal independent set, minimum spanning tree, minimum edge cut and minimum vertex cut, graph connectivity decompositions, network information dissemination, minimum-weight connected dominating set, and scheduling distributed protocols. We develop novel techniques, concepts, and tools for these problems, and present algorithms and impossibility results which improve considerably on the state of the art, in several cases resolving or advancing long-standing open problems.
by Mohsen Ghaffari.
Ph. D.

Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2015.
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pages 104-106).
Machine-gradable assessments in online education platforms are currently limited to questions that require only keyboard or mouse input, and grading efforts generally focus only on final answers. Some types of problems in the science, technology, engineering, and math (STEM) domain, however, are most naturally answered through sketches drawn with a pen. We introduce a simple graph problem type that accepts solutions drawn using a stylus as a proof-of-concept extension to online education platforms. Simple graphs have a small number of components (vertices, arrows, and edges only), and we describe a three-step recognition process consisting of segmentation, symbol classication, and domain interpretation for converting users' pen strokes into a simple graph object representation. An experiment run on Mechanical Turk demonstrates the usability of our trained, recognition-driven drawing interface, and examples of simple graph problems illustrate how course developers can not only check students' final answers but also provide students with intermediate feedback.
by Katharine M. Daly.
M. Eng.

Graph theory is the study of networks of objects (called vertices) joined by links (called edges). Since many real world problems can be represented by a graph, graph theory has applications in areas such as sociology, chemistry, and computing. In this thesis, a number of open problems in graph theory are studied.

Les problèmes de partitionnement de graphique sont une classe bien connue des problèmes d'optimisation combinatoire NP-difficiles avec un large éventail d'applications, telles que la conception de plans VLSI, la physique statistique, la planification d'une équipe sportive, la segmentation d'images et la structuration de protéines. En raison de la grande complexité de ces problèmes, les approches heuristiques et métaheuristiques sont couramment utilisées pour aborder les problèmes difficiles. Cette thèse considère trois problèmes représentatifs de cette famille, incluant le problème "max-k-cut", le problème "max-bisection" et le problème de séparation de sommets (VSP). Elle vise à élaborer des algorithmes heuristiques efficaces basés sur une ensemble d'opérateurs de recherche complémentaires. Plus précisément, nous développons une heuristique à opérateur multiple (MOH) pour "max-k-cut", un algorithme de recherche Tabu itérée (ITS) pour "max-bisection" et un algorithme "path relinking" (PR-VSP) pour VSP. Des résultats expérimentaux sur des jeux de test standard démontrent que les algorithmes proposés rivalisent favorablement avec les approches existantes de la littérature. L'utilisation combinée de plusieurs opérateurs de recherche est analysée afin de mettre en évidence l'influence de ces opérateurs sur la performance des algorithmes
Graph partitioning problems are a class of well-known NP-hard combinatorial optimization problems with a wide range of applications, such as VLSI layout design, statistical physics, sports team scheduling, image segmentation, and protein conformation for instances. This thesis considers three representative problems in this family, including the max-k-cut problem, the max-bisection problem and the vertex separator problem (VSP). Due to high computational complexity, heuristic and metaheuristic approaches are commonly used for approximating the challenging problems. This thesis is devoted to developing efficient metaheuristic algorithms based on a collection of complementary search operators. Specifically, we develop a multiple operator heuristic (MOH) for max-k-cut, an iterated tabu search (ITS) algorithm for max-bisection and a path relinking (PR-VSP) algorithm for VSP. Extensive computational experiments and comparisons demonstrate that the proposed algorithms compete favorably with state-of-the-art approaches in the literature. The combined use of multiple search operators is analyzed to shed lights on the influence over the performance of the algorithms

Graph theory is fascinating branch of math. Leonhard Euler introduced the concept of Graph Theory in his paper about the seven bridges of Konigsberg published in 1736. In a nutshell, graph theory is the study of pair-wise relationships between objects. Each object is represented using a vertex and in case of a relationship between a pair of vertices, they will be connected using an edge. In this dissertation, graph theory is used to study several important combinatorial optimization problems. In chapter 2, we study the multi-dimensional assignment problem using their underlying hypergraphs. It will be shown how the MAP can be represented by a k-partite graph and how any solution to MAP is associated to a k-clique in the respective k-partite graph. Two heuristics are proposed to solve the MAP and computational studies are performed to compare the performance of the proposed methods with exact solutions. On the heels of chapter 3, a new branch-and-bound method is proposed to solve the problem of finding all k-cliques in a k-partite graph. The new method utilizes bitsets as the data-structure to represent graph data. A new pruning method is introduced in BitCLQ, and CPU instructions are used to improve the performance of the branch-and-bound method. BitCLQ gains up to 300% speed up over existing methods. In chapter 4, two new heuristic to solve decomposable cost MAP's are proposed. The proposed heuristic are based on the partitioning of the underlying graph representing the MAP. In the first heuristic method, MAP's are partitioned into several smaller MAP's with the same dimensiality and smaller cardinality. The solution to the original MAP is constructed incrementally, by using the solutions obtained from each of the smaller MAP's. The second heuristic works in the same fashion. But instead of partitioning the graph along the cardinality, graphs are divided into smaller graphs with the same cardinality but smaller dimensionality. The result of each heuristic is then compared with a well-known existing heuristic. An important problem in graph theory is the maximum clique problem (MCQ). A clique in a graph is defined as a complete subgraph. MCQ problem entails finding the size of the largest clique contained in a graph. General branch-and-bound methods to solve MCQ use graph coloring to find an upper bound on the size of the maximum clique. Recently, a new MAX-SAT based branch-and-bound method for MCQ is proposed that improves the quality of the upper bound obtained from graph coloring. In chapter 5, a branch and bound algorithm is proposed for the maximum clique problem. The proposed method uses bitsets as the data-structure. The result of the computational studies to compare the proposed method with existing methods for MCQ is provided. Chapter 6 contains an application of a graph theory in solving a risk management problem. A new mixed-integer mathematical model to formulate a risk-based network is provided. It will be shown that an optimal solution of the model is a maximal clique in the underlying graph representing the network. The model is then solved using a graph-theoretic approach and the results are compared to CPLEX.

This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2019
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pages 59-60).
In this thesis, we show conditional lower bounds for graph distance problems in the sensitivity setting, a restriction on the dynamic setting. We consider graph diameter, radius, and eccentricities over a few distance metrics, and sensitivities both constant and logarithmic in the size of the graph. Despite these restrictions, we find that many lower bound results from the static and fully dynamic settings still hold under popular conjectures. We show many of these lower bounds for graphs with constant maximum degree as well.
by Bertie Ancona.
M. Eng.
M.Eng. Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science

In this dissertation the results of Jerrum and Sinclair on the conductance of Markov chains are used to prove that almost all generalized Steinhaus graphs are rapidly mixing and an algorithm for the uniform generation of 2 - (4k + 1,4,1) cyclic Mendelsohn designs is developed.

Center location on cactus graphs. The p-center problem has been shown to be NP-hard for case of a general graph, yet polynomial algorithms exist for the case of a tree graph. Specifically, we consider "cactus graphs" where each edge is contained in at most one cycle. We show that the p-center problem on this class can be solved in polynomial time using a decomposition algorithm. We partition the graph into a set of subgraphs which are then solved sequentially. The solutions to the subgraphs are linked by a single parameter. The algorithm runs in polynomial time. Locating capacity limited centers on trees. The uncapacitated p-center problem on trees is solvable in polynomial time. We extend this result to include the case where each center can serve a limited number of customers and show that the capacitated p-center on trees can be solved in polynomial time when the capacities are identical. The algorithm consists of solving a capacitated covering problem and then using search routines to find the optimal domination radius. Center location on spheres. We discuss the unweighted center location problem. The following results are presented: (i) An O(n) time algorithm to solve the 1-center problem if the vertices are on one half of the sphere, and an O(n) time algorithm to check whether this condition holds. Both algorithms are based on presenting the problems as 3-dimensional convex programming problems with linear constraints and applying a pruning technique to find the optimum in O(n) time. (ii) An O(n$\sp3$ log n) time algorithm for the 2-center problem on the whole sphere. (iii) A reduction to show that the general p-center problem on a sphere is NP-hard. Locating hyperplanes on hypercubes. In linear regression models we are interested in locating a (d-1) dimensional hyperplane that will be as "close" as possible to existing vertices in the d-dimensional hypercube. The least squares criterion is usually applied for the linear fitting problem; while fitting according to the least absolute value ("minisum") seems to be "complicated". We solve fitting problems with the minisum criterion and present linear time algorithms when the dimension d is fixed. (Abstract shortened with permission of author.)

A dominating set in a graph is a set S of vertices such that every vertex not in S is adjacent to a member S. A global defensive alliance in a graph is a dominating set S with the property that every vertex in S has in its closed neighborhood at least as many vertices in S as in V -- S. A global offensive alliance in a graph is a dominating set S with the property that every vertex in V -- S has in its closed neighborhood at least as many vertices in S as in V -- S.
We first study alliances in graphs. There are many results in this area. For example, it is known that every connected n-vertex graph G has a global offensive alliance of size at most 2n/3. Another result is that any global defensive alliance in G has size at least ( 4n+1 - 1)/2. Our study focuses particularly on trees and algorithms for finding alliances in trees. We find the cardinality of a minimum global offensive alliance for complete k-ary trees and the minimum cardinality global defensive alliance for complete binary and ternary trees. Also, we present a linear time algorithm for finding the minimum global offensive alliance in a tree. Additionally, for a general graph, an upper bound is given on the size of a minimum global offensive alliance in terms its degree sequence. The methods that we use in this part of the thesis are mainly algorithmic and deterministic.
Then we study independent dominating sets in graphs. An independent dominating set is a set of mutually nonadjacent vertices which is also a dominating set. This is a well-studied topic (see Haynes, Hedetniemi and Slater [22]). Our main result is to show that every d-regular graph of order n with girth at least 5 and satisfying d = o(1) and d2(log d)3/2 = o(n) contains an independent dominating set of size at most (1 + o(1)) nlogdd . This generalizes the results of Duckworth and Wormald [15] for random regular graphs. We construct the independent dominating set using recent probabilistic methods which resemble Rodl's semi-random method (see for example Alon and Spencer [1]).

In this dissertation, we are interested in studying several parameters of graphs and understanding their extreme values. We begin in Chapter~$2$ with a question on edge colouring. When can a partial proper edge colouring of a graph of maximum degree $\Delta$ be extended to a proper colouring of the entire graph using an `optimal' set of colours? Albertson and Moore conjectured this is always possible provided no two precoloured edges are within distance $2$. The main result of Chapter~$2$ comes close to proving this conjecture. Moreover, in Chapter~$3$, we completely answer the previous question for the class of planar graphs. Next, in Chapter~$4$, we investigate some Ramsey theoretical problems. We determine exactly what minimum degree a graph $G$ must have to guarantee that, for any two-colouring of $E(G)$, we can partition $V(G)$ into two parts where each part induces a connected monochromatic subgraph. This completely resolves a conjecture of Bal and Debiasio. We also prove a `covering' version of this result. Finally, we study another variant of these problems which deals with coverings of a graph by monochromatic components of distinct colours. The following saturation problem proposed by Barrus, Ferrara, Vandenbussche, and Wenger is considered in Chapter~$5$. Given a graph $H$ and a set of colours $\{1,2,\ldots,t\}$ (for some integer $t\geq |E(H)|$), we define $sat_{t}(n, R(H))$ to be the minimum number of $t$-coloured edges in a graph on $n$ vertices which does not contain a rainbow copy of $H$ but the addition of any non-edge in any colour from $\{1,2,\ldots,t\}$ creates such a copy. We prove several results concerning these extremal numbers. In particular, we determine the correct order of $sat_{t}(n, R(H))$, as a function of $n$, for every connected graph $H$ of minimum degree greater than $1$ and for every integer $t\geq e(H)$. In Chapter~$6$, we consider the following question: under what conditions does a Hamiltonian graph on $n$ vertices possess a second cycle of length at least $n-o(n)$? We prove that the `weak' assumption of a minimum degree greater or equal to $3$ guarantees the existence of such a long cycle. We solve two problems related to majority colouring in Chapter~$7$. This topic was recently studied by Kreutzer, Oum, Seymour, van der Zypen and Wood. They raised the problem of determining, for a natural number $k$, the smallest positive integer $m = m(k)$ such that every digraph can be coloured with $m$ colours, where each vertex has the same colour as at most a proportion of $\frac{1}{k}$ of its out-neighbours. Our main theorem states that $m(k) \in \{2k-1, 2k\}$. We study the following problem, raised by Caro and Yuster, in Chapter~$8$. Does every graph $G$ contain a `large' induced subgraph $H$ which has $k$ vertices of degree exactly $\Delta(H)$? We answer in the affirmative an approximate version of this question. Indeed, we prove that, for every $k$, there exists $g(k)$ such that any $n$ vertex graph $G$ with maximum degree $\Delta$ contains an induced subgraph $H$ with at least $n-g(k)\sqrt{\Delta}$ vertices such that $V(H)$ contains at least $k$ vertices of the same degree $d \ge \Delta(H)-g(k)$. This result is sharp up to the order of $g(k)$. %Subsequently, we investigate a concept called $\textit{path-pairability}$. A graph is said to be path-pairable if for any pairing of its vertices there exist a collection of edge-disjoint paths routing the the vertices of each pair. A question we are concerned here asks whether every planar path pairable graph on $n$ vertices must possess a vertex of degree linear in $n$. Indeed, we answer this question in the affirmative. We also sketch a proof resolving an analogous question for graphs embeddable on surfaces of bounded genus. Finally, in Chapter~$9$, we move on to examine $k$-linked tournaments. A tournament $T$ is said to be $k$-linked if for any two disjoint sets of vertices $\{x_1,\ldots ,x_k\}$ and $\{y_1,\dots,y_k\}$ there are directed vertex disjoint paths $P_1,\dots, P_k$ such that $P_i$ joins $x_i$ to $y_i$ for $i = 1,\ldots, k$. We prove that any $4k$ strongly-connected tournament with sufficiently large minimum out-degree is $k$-linked. This result comes close to proving a conjecture of Pokrovskiy.

Un aspecte fonamental quan cal resoldre un problema vibroacústic en un sistema mecànic és el de determinar com flueix l’energia des d’una font donada, cap a qualsevol part del sistema. Això permet decidir quines són les accions a prendre per disminuir, per exemple, els nivells de soroll i vibracions en una determinada àrea del sistema. El comportament dinàmic d’un sistema mecànic es pot estimar utilitzant diversos mètodes numèrics, cadascun dels quals enfocat a un marge de freqüència determinat. Mentre a baixes freqüències es poden aplicar mètodes deterministes com el Mètode d’Elements Finits (FEM) o el Mètode d’Elements de Contorn (BEM), a altes freqüències, els mètodes estadístics com l’Anàlisi Estadística Energètica (SEA), esdevenen inevitables. A més a més, diverses tècniques com el FE-SEA híbrid, els models de Distribució Energètica (ED) o l’Anàlisi Estadística de distribució d’Energia modal (SmEdA), entre d’altres, han estat recentment plantejades per tal de tractar amb l’anomenat problema de les mitges freqüències. Tanmateix, encara que alguns mètodes numèrics poden predir la resposta vibroacústica puntual o amitjanada d’un sistema, aquests no proporcionen de forma directa informació sobre com flueix l’energia per tot el sistema. Per tant, cal algun tipus de post-processament per a determinar quines són les vies de transmissió d’energia. L’energia transmesa a través d’un determinat camí que connecti un subsistema font, on l’energia és introduïda, i un subsistema receptor, es pot calcular numèricament. Tot i això, la identificació dels camins que dominen la transmissió d’energia des d’una font fins a un receptor normalment acostuma a basar-se en l’experiència i el parer de l’enginyer. Així doncs, un mètode que permeti obtenir aquests camins de forma automàtica resultaria molt útil. La teoria de grafs proporciona una sortida a aquest problema, ja que existeixen diversos algorismes de càlcul de camins en grafs. En aquesta tesi, es proposa un enllaç entre els models vibroacústics i la teoria de grafs, que permet adreçar els problemes de vies de transmissió de forma directa. La dissertació comença centrant-se en els models SEA. Primerament, es mostra que té sentit realitzar una anàlisi de vies de transmissió (TPA) en SEA. Seguidament, es defineix un graf que representa de forma acurada els models SEA. Tenint en compte que la transmissió d’energia entre fonts i receptors es pot justificar mitjançant la contribució d’un grup finit de vies dominants en varis casos d’interès, es presenta un algorisme per calcular-les. A continuació, s’implementa un algorisme que inclou en el càlcul de camins la naturalesa estocàstica dels factors de pèrdues SEA. Tot seguit, es tracta com es pot estendre l’anàlisi de vies de transmissió al marge de la mitja freqüència. L’aplicació de la teoria de grafs a les mitges freqüències s’adapta per alguns models ED, així com també SmEdA. Finalment, es presenta una altra possible aplicació de la teoria de grafs en vibroacústica. S’implementa una estratègia basada en algorismes de talls en grafs per tal de reduir l’energia en un subsistema receptor amb la modificació d’un grup reduït de factors de pèrdues. Aquest grup de variacions, es troba calculant talls en el graf que separin els subsistemes fonts dels receptors.
A fundamental aspect when solving a vibroacoustic problem in a mechanical system is that of finding out how energy flows from a given source to any part of the system. This would help making decisions to undertake actions for diminishing, for example, the noise or vibration levels at a given system area. The dynamic behavior of a mechanical system can be estimated using different numerical methods, each of them targeting a certain frequency range. Whereas at low frequencies deterministic methods such as the Finite Element Method (FEM) or the Boundary Element Method (BEM) can be applied, statistical methods like Statistical Energy Analysis (SEA) become unavoidable at high frequencies. In addition, a large variety of approaches such as the hybrid FE-SEA, the Energy Distribution (ED) models or the Statistical modal Energy distribution Analysis (SmEdA), among many others, have been recently proposed to tackle with the so-called mid-frequency problem. However, although numerical methods can predict the pointwise or averaged vibroacoustic response of a system, they do not directly provide information on how energy flows throughout the system. Therefore, some kind of post-processing is required to determine energy transmission paths. The energy transmitted through a particular path linking a source subsystem, where external energy is being input, and a target subsystem, can be computed numerically. Yet, identifying which paths dominate the whole energy transmission from source to target usually relies on the engineer's expertise and judgement. Thus, an approach for the automatic identification of those paths would prove very useful. Graph theory provides a way out to this problem, since powerful path algorithms for graphs are available. In this thesis, a link between vibroacoustic models and graph theory is proposed, which allows one to address energy transmission path problems in a straightforward manner. The dissertation starts focusing on SEA models. It is first shown that performing a transmission path analysis (TPA) in SEA makes sense. Then a graph that accurately represents the SEA model is defined. Given that the energy transmission between sources and targets is justified by the contribution of a limited group of dominant paths in many cases of practical interest, an algorithm to find them is presented. Thereafter, an enhanced algorithm is devised to include the stochastic nature of SEA loss factors in the ranking of paths. Next, it is discussed how transmission path analysis can be extended to the mid frequency range. The graph approach for path computation becomes adapted for some ED models, as well as for SmEdA. Finally, we outline another possible application of graph theory to vibroacoustics. A graph cut algorithm strategy is implemented to achieve energy reduction at a target subsystem with the sole modification of a reduced set of loss factors. The set is found by computing cuts in the graph separating source and receiver subsystems.
Un aspecto fundamental a la hora de resolver un problema vibroacústico en un sistema mecánico es el de determinar cómo fluye la energía desde una determinada fuente hasta cualquier parte del sistema. Ello ayudaría a tomar decisiones para emprender acciones destinadas a disminuir, por ejemplo, los niveles de ruido y vibraciones en un área del sistema dada. El comportamiento dinámico de un sistema mecánico se puede estimar utilizando varios métodos numéricos, cada uno de ellos enfocado a un determinado rango de frecuencia. Mientras en las bajas frecuencias se pueden aplicar métodos deterministas como el Método de los Elementos Finitos (FEM) o el método de Elementos de Contorno (BEM), los métodos estadísticos como el Análisis Estadístico Energético son inevitables en las altas frecuencias. Además, se han desarrollado gran variedad de técnicas como el FE-SEA híbrido, los modelos de Distribución de Energía (ED) o el Análisis Estadístico de distribución de Energía modal (SmEdA), entre otras, para tratar el llamado problema de las medias frecuencias. Sin embargo, aunque los métodos numéricos pueden predecir la respuesta vibroacústica puntual o promediada de un sistema mecánico, ellos no proporcionan información sobre como fluye la energía en el sistema. Por lo tanto, hace falta algún tipo de post-procesado para determinar las vías de transmisión de energía. La energía transmitida a través de un determinado camino que conecta un subsistema fuente, donde se introduce la energía, y un subsistema receptor, se puede calcular numéricamente. A pesar de ello, identificar qué caminos dominan la transmisión de energía desde la fuente al receptor normalmente suele recaer en la experiencia o el juicio del ingeniero. Así pues, un método automático para identificar estos caminos resultaría muy útil. La teoría de grafos proporciona una solución a este problema, ya que existen potentes algoritmos de cálculos de caminos en grafos. En esta tesis, se propone un enlace entre los modelos vibroacústicos y la teoría de grafos, que permite abordar los problemas de vías de transmisión de forma directa. La disertación empieza centrándose en los modelos SEA. Primeramente, se muestra que tiene sentido realizar un análisis de vías de transmisión (TPA) en un modelo SEA. Seguidamente, se define un grafo que representa fielmente un modelo SEA. Teniendo en cuenta que en muchos casos de interés práctico, la transmisión de energía entre fuentes y receptores se puede justificar mediante la contribución de un grupo finito de vías de transmisión, se define un algoritmo para encontrarlas. A continuación, se implementa un algoritmo que incluye en el cómputo de caminos la naturaleza estocástica de los factores de pérdidas SEA. Luego, se trata la extensión del análisis de vías de transmisión al rango de media frecuencia. La técnica de teoría de grafos aplicada a cálculo de caminos se adapta para algunos modelos ED y también SmEdA. Finalmente, se presenta otra posible aplicación de la teoría de grafos a la vibroacústica. Se implementa una estrategia basada en algoritmos de cortes en grafos destinada a reducir la energía en un subsistema receptor mediante la simple modificación de un grupo reducido de factores de pérdidas. El grupo se encuentra calculando cortes que separen en el grafo los subsistemas fuentes de los subsistemas receptores.

Le problème de la clique maximum (MCP) est un problème d'optimisation combinatoire important avec un large éventail d'applications pratiques dans de nombreux domaines, y compris la recherche d'information, l'analyse de la transmission du signal, la théorie de la classification, l'économie, la planification et l'ingénierie biomédicale. En outre, un certain nombre de problèmes d'optimisation combinatoire sont étroitement liés au MCP, tels que la coloration de graphe, la somme coloration, réglez détermination du gagnant emballage et optimale. Cette thèse est consacrée à l'élaboration d'approches heuristiques efficaces pour s'attaquer au problème de la clique maximum et ses généralisations. Pour atteindre cet objectif, nous avons développé une approche de recherche tabou adaptative multistart pour le problème de clique maximum classique, un algorithme recherche tabou multi-voisinage pour la clique maximum de sommets pondérés, et une méthode métaheuristique hybride pour le problème de la clique maximum d'arêtes pondérés. En outre, nous appliquons ces méthodes heuristiques développées pour résoudre ces problèmes difficiles qui sont étroitement liés au problème de la clique maximum. Tous les algorithmes sont mis en oeuvre et testés avec succès sur un certain nombre de cas de référence provenant de divers domaines d'application. Les méthodes proposées concurrencent favorablement les autres approches de l'état de l'art
The maximum clique problem (MCP) is an important combinatorial optimization problem with a wide range of practical applications in numerous fields, including information retrieval, signal transmission analysis, classification theory, economics, scheduling, and biomedical engineering. Moreover, a number of combinatorial optimization problems are tightly related to MCP, such as graph coloring, sum coloring, set packing and optimal winner determination. This thesis is devoted to developing effective heuristic approaches to tackle the maximum clique problem and its generalizations. To achieve this, we developed an adaptive multistart tabu search approach for the classic maximum clique problem, a multi-neighborhood tabu search algorithm for the maximum vertex weight clique and a hybrid metaheuristic method for the maximum edge weight clique problem. Moreover, we apply these developed heuristic approaches to solve these hard problems which are tightly related to the maximum clique problem. All algorithms are implemented and successfully tested on a number of benchmark instances from diverse application areas. The proposed methods favorably compete with other state-of-art approaches

We explore algorithmic aspects of two known combinatorial problems, Graph Colouring and Hamiltonian Cycle, by examining properties of their solution space. One can model the set of solutions of a combinatorial problem $P$ by the solution graph $R(P)$, where vertices are solutions of $P$ and there is an edge between two vertices, when the two corresponding solutions satisfy an adjacency reconfiguration rule. For example, we can define the reconfiguration rule for graph colouring to be that two solutions are adjacent when they differ in colour in exactly one vertex. The exploration of the properties of the solution graph $R(P)$ can give rise to interesting questions. The connectivity of $R(P)$ is the most prominent question in this research area. This is reasonable, since the main motivation for modelling combinatorial solutions as a graph is to be able to transform one into the other in a stepwise fashion, by following paths between solutions in the graph. Connectivity questions can be made binary, that is expressed as decision problems which accept a 'yes' or 'no' answer. For example, given two specific solutions, is there a path between them? Is the graph of solutions $R(P)$ connected? In this thesis, we first show that the diameter of the solution graph $R_{l}(G)$ of vertex $l$-colourings of k-colourable chordal and chordal bipartite graphs $G$ is $O(n^2)$, where $l > k$ and n is the number of vertices of $G$. Then, we formulate a decision problem on the connectivity of the graph colouring solution graph, where we allow extra colours to be used in order to enforce a path between two colourings with no path between them. We give some results for general instances and we also explore what kind of graphs pose a challenge to determine the complexity of the problem for general instances. Finally, we give a linear algorithm which decides whether there is a path between two solutions of the Hamiltonian Cycle Problem for graphs of maximum degree five, and thus providing insights towards the complexity classification of the decision problem.

Shortest path problems arise in a variety of applications ranging from transportation planning to network routing among others. One group of these problems involves finding shortest paths in graphs where the edge weights are defined by probability distributions. While some research has addressed the problem of finding a single shortest path, no research has been done on finding multiple paths in such graphs. This thesis addresses the problem of finding paths for multiple robots through a graph in which the edge weights represent the probability that each edge will fail. The objective is to find paths for n robots that maximize the probability that at least k of them will arrive at the destination. If we make certain restrictions on the edge weights and topology of the graph, this problem can be solved in O(n log n)time. If we restrict only the topology, we can find approximate solutions which are still guaranteed to be better than the single most reliable path.