The real-world problem of Urban Bicycles Renting Systems (UBRS) in a city requires the optimization of vehicle routes connecting several bicycle base stations and storage centers. This problem can be modeled as a capacitated Vehicle Routing Problem (VRP) with multiple depots and the simultaneaous need for pickup and delivery at each base station location. Based on the VRP model specification, an evolutionary approach is proposed to address the UBRS problem. Individuals are encoded as permutations of base stations and then translated to a set of routes subject to the constraints related to vehicle capacity and node demands. Better-fitted offspring generated via order crossover or swap mutation are asynchronously inserted in the population. The proposed evolutionary algorithm is engaged for the UBRS problem using data from the city of Barcelona with promising results. Some relevant parameters that can enhance the proposed approach have been identified and analysed via the computational experiments.