The vehicle’s maintenance costs, uptime and security are the most important goals for owners and transport companies, but these goals are conflictual and the major cause for delays is related to the maintenance policies. The main objective of transporters is to respond properly to their customer’s demands. In order to deal with this competitiveness, transport companies are working to improve the management of their fleets by focusing in particular on vehicle maintenance, which impact the vehicles uptime, and generate the most important cost. In addition, a vehicle maintenance policy aims to avoid failures and keep the vehicle up and safe. This objective is reached by ensuring a high reliability; otherwise, an unexpected failure of a component can cause vehicle down and can affect the entire sub-system while generating costs. In this paper, we propose a new maintenance policy based on multi-objective optimization. This problem is solved using the Speed-Constrained Multiobjective Particle Swarm Optimization (SMPSO) for an instance of 18 components and 20 vehicles. First, we give an overview of the existing techniques used for vehicle’s maintenance policy, then we present the mathematical model that describes the cost of maintenance and the level of safety. Numerical experiments are presented to demonstrate the efficiency of our approach.