In this thesis, we are interested to deal with combinatorial optimization problems related to design management tools for vehicle-sharing systems. These problems are close to the Pickup-and-Delivery Problems (PDP) in the literature. After performing a survey on the problems area and on the resolution methods, we focused on three specific problems and we proposed one approach for each problem. The first one is the sharing Vehicles Redeployment Planning Problem (VRPP), which is considered as a multi-vehicles extension of the One-commodity Pickup-and-Delivery Problem (1-PDP). We proposed a linear model and a hybrid heuristic which combines the ILS and VND. The proposed approach uses the rout-first, cluster-second strategy: we construct a Hamiltonian route, and then improve it using a procedure combines a shacking step and a VND local search. The used neighborhoods are adapted to the relaxation of capacity; the obtained route would be then split into several vehicles tours in the clustering phase.The two following problems are considered as extensions of VRPP introducing the split demand constraint : VRPP with Multi-Passage (VRPP-MP) and VRPP with Transferring objects (VRPP-T). We proposed an approach with the divide-first, route-second strategy for VRPP-MP. It consists of dividing in advance the demand, and then solves it using a hybrid scheme of GRASP/VND. In the VRPP-T, the objects carried could be exchanged between carriers when crossing on the sites. The VRPP-T is modeled here as a multi-flows problem on a dynamic network. We proposed an insertion method based on this modeling.
