This thesis deals with dynamic Multi-Vehicle
Routing Problem (MVRP) in both deterministic and stochastic scenarios. The objective of the MVRP is to find the best paths
for a fleet of vehicles, with the aim of visiting a set of targets.
Based on the Cooperative Receding Horizon (CRH) approach
proposed by Cassandras et al.(CRH) for the Euclidean case, this thesis: i) presents another algorithm that is more efficient with clustered targets (tCRH); ii) illustrates an algorithm that exploits CRH and tCRH strengths (aCRH); iii) extends CRH, tCRH and aCRH to realistic urban map case
