Our objective is to study, from an algorithmic perspective, central optimization problems for transportation networks. Such a network can be represented by a temporal graph where the vertices are points of interest (cities, stations, bus stops, etc.), and the edges are connections between these points. Connections may appear and disappear over time, so the edges are equipped with temporal data indicating the moments when they are active.

The emerging theme of temporal (or dynamic) graphs allows us to address real-world issues. In such a graph, connections are not present all the time but only at certain intervals. This reflects, for example, the fact that in a transportation network, certain communication pathways may be temporarily blocked.

Considering dynamic graphs allows us to refine existing algorithmic results and apply them to a more realistic context.

Our goal is to contribute to the recent development of algorithms for this type of object. We will use tools from graph algorithmics to tackle these problems.