  Problems affecting the transport of people or goods are plentiful in industry
and commerce and they also appear to be at the origin of much more complex
problems. In recent years, the logistics and transport sector keeps growing
supported by technological progress, i.e. companies to be competitive are
resorting to innovative technologies aimed at efficiency and effectiveness.
This is why companies are increasingly using technologies such as Artificial
Intelligence (AI), Blockchain and Internet of Things (IoT). Artificial
intelligence, in particular, is often used to solve optimization problems in
order to provide users with the most efficient ways to exploit available
resources. In this work we present an overview of our current research
activities concerning the development of new algorithms, based on CLP
techniques, for route planning problems exploiting the geometric information
intrinsically present in many of them or in some of their variants. The
research so far has focused in particular on the Euclidean Traveling
Salesperson Problem (Euclidean TSP) with the aim to exploit the results
obtained also to other problems of the same category, such as the Euclidean
Vehicle Routing Problem (Euclidean VRP), in the future.
