E-mobility, in particular electric vehicles (EVs), play a crucial role in the energy transition. While businesses are increasingly adopting EVs, there is still a lot of opportunity to grow. One aspect of this growth is the way these vehicles are used by companies, especially when it comes to the logistics of EV charging. To encourage companies to further reduce their carbon footprint by more efficiently utilizing EVs, this project proposes a combined vehicle routing and charging model. These models can be used separately, as well as together, allowing the charging model to be combined with any pre-existing routing engine. The goal of this project is to show the benefits of allowing EVs to be charged between shifts during the day, rather than exclusively overnight, as well as to show how such schedules can be made. Our results show that giving vehicles the opportunity to charge between shifts can significantly reduce the costs associated with fleet operations. If the fleet contains non-electric vehicles as well as electric ones, we also see a significant reduction in the number of kilometers driven using fossil fuels. When sufficient chargers were available, even when the vehicles had little time to charge, a feasible schedule could always be found. Moreover, when more realistic charging intervals were used, most vehicles were even able to fully recharge before the start of their next shift. Finally, we concluded that the set of chargers needed to find such a feasible schedule can be relatively small, meaning that even without extensive additions to the charging infrastructure, companies can still benefit from this policy change.

The k-truncated metric dimension of a graph is the minimum number of sensors (a subset of the vertex set) needed to uniquely identify every vertex in the graph based on its distance to the sensors, where the sensors have a measuring range of k. We give an algorithm with the goal that given any tree and any value for the measuring range of the sensors k, the algorithm finds the k-truncated metric dimension of that tree. The algorithm presented in this thesis is a modification of the algorithm given by Gutkovich and Song Yeoh [6]. The algorithm in this thesis improves on their algorithm in both validity and time complexity. We show that given any tree and any value k, the algorithm returns a k-resolving set for that tree. Moreover, we conjecture the difference in the k-truncated metric dimension of any tree and the size of the k-resolving set found by the algorithm for that tree is never greater than one. The time complexity of the algorithm is proven to be O(k3n), where k is the measuring range of the sensors and n is the number of vertices in the tree. This implies that the time complexity is linear in n for fixed k.

For this thesis, we consider two $k$-colorings of a graph $G$ adjacent if one can recolor one into the other by changing the color of one vertex. The reconfiguration graph of a graph $G$ on $k$ colors $\mathcal{C}_{k}(G)$ is the graph for which the vertices are the $k$-colorings of $G$, and an edge is between two $k$-colorings if they are adjacent. We further investigate the diameter of the reconfiguration graph on $k$ colors: $\mathrm{diam}\left(\mathcal{C}_{k}(G)\right)$. 
The general conjecture the thesis is based around says that $\mathrm{diam}\left(\mathcal{C}_{k}(G)\right)$ for every graph $G$ and $k \geq \Delta(G)+2$. This conjecture is confirmed for various families of graphs, for example the complete graph $K_n$ and complete bipartite $K_{n,m}$. This thesis will prove the lower bound of the conjecture for the family of complete $r$-partite graphs $G = K_{x_1,x_2,\ldots,x_r}$, utilising an approach from Cambie et al. for the proof. Furthermore we give an algorithm that computes the $k$-colorings of $G$, the reconfiguration graph $\mathcal{C}_{k}(G)$, and its diameter $\mathrm{diam}\left(\mathcal{C}_{k}(G)\right)$ and give a few results on this diameter for small graphs.

This thesis provides a fresh perspective on the (vertex) integrity of graphs, serving as a measure of network robustness. The study begins by introducing fundamental concepts and methods for evaluating the integrity of different graph families. An Integer Linear Programming (ILP) model, specifically designed for assessing integrity, is then presented. By applying this model, integrity values are calculated for various graph families, and patterns within the results are identified. These patterns contribute to establishing boundaries or determining exact values of integrity for the analyzed graph families. The analyzed graph families encompass Glued Paths, generalized Theta graphs, (Double) Cone graphs, Fan graph, Lollipop graphs, generalized Barbell graphs, (Dutch) Windmill graphs, Paley graphs, and Kneser graphs. Additionally, two conjectures are formulated: one concerning a lower bound for the integrity of all Paley graphs, and another addressing the exact integrity values of specific Kneser graphs. The ILP model proves to be a valuable tool for further exploration of graph family integrity, offering opportunities for additional research and expanding our understanding of network robustness.

A set of lines passing through the origin in Euclidean space is called equiangular if the angle between any two lines is the same. The question of finding the maximum number of such lines, N(d) in any dimension d is an extensively studied problem. Closely related, is the problem of finding the maximum number of lines, N_α(d), such that the common angle between the lines is arccosα. In recent years, many progress has been made on this problem. We review some of these breakthrough results and the techniques they use to approach this problem. The first main result is a linear upper bound on N_α(d) which is found using a completely novel approach with respect to techniques used in previous works. Another main result that we discuss solves the problem of finding N_α(d) for high enough dimensions. Some classic results from some of the first studies on equiangular lines are also discussed. Finally, some suggestions are given for possible further research.

A code C is defined to be a set of S words, where a word is a sequence of n entries. We call S the size and n the length of the code. The entries of the code can have k different values, {0, .., (k − 1)}. Define a perfect k-hash code (PHC) as a code with the property that any collection of v words in the code is different at at least one index. PHC’s are useful mathematical objects within different fields of theoretical computer science and coding theory. This thesis will focus on one typical kind of PHC, a trifferent code. Such a trifferent code is defined as a PHC where k = v = 3. This means that any collection of three words in the code has to differ at some index. We now define T (n) to be the largest possible size of a trifferent code given that it has length n. The question that arises is, what is the value of T (n)? It turns out that determining the exact value is complicated, unless n is really small. Therefore, we try to understand the asymptotic nature of the function T (n). This is what we call the trifference problem. This paper will cover and prove the best known asymptotic upper and lower bound on T (n). Moreover, it will explain and include a Python code that can be used to show and prove all values of T (n) for n ∈ {1, .., 6}. Lastly, two different ways to explicitly construct trifferent codes for any value of n will be given and compared.

This thesis uses the method of interlacing polynomials to study the behaviour of eigenvalues of a matrix after a rank-one update. Specifically, interlacing polynomials, common interlacing and interlacing families are exhaustively studied. These are excellent tools to find bounds on the eigenvalues of updated matrices by keeping track of how they move.

This enables us to prove results in different mathematical fields. We investigate three of them. The first one is from spectral graph theory: we prove the existence of a sharp κ-approximation for any graph.

The second result is from linear algebra. It states that if a matrix has a high stable rank, it must contain a large column submatrix with large least singular value.  

Lastly, the proof of the Kadison-Singer Problem is discussed. Despite being a problem from analysis, it was solved with the interlacing method, which is originally a method from discrete mathematics.

This thesis shows how these three seemingly different problems are all connected by the same method, highlighting its advantages. The objective is to present a clear framework of the different facets of the interlacing method and provide an insight in the situations where one can expect the said method to be useful.

We consider the game cops and robbers, which is a pursuit-evasion game played on a graph G. The cops and the robber take turns moving across the vertices of G, where the goal for the cops is to eventually catch the robber. Specifically, we study the cop number of G, i.e. the minimum number of cops that is needed to catch the robber on G. We investigate the relation between the cop number of the Erdős-Rényi (ER) random graph G(n, p_n) and compare it to another graph parameter, the domination number. Our goal is to collect results from previous research and create an overview. Throughout this thesis, we provide some examples of graphs for which the cop number is equal to the domination number. Furthermore, we provide proofs for some results on the domination number of the ER random graph. The main takeaway is that the cop number is asymptotic to the domination number for particular values of p_n.