We study the problem of the optimal design of routes and frequencies in urban public transit systems, the Transit Network Design Problem (TNDP). We model it as a multi-objective combinatorial optimization problem, which consists in optimizing simultaneously the conflicting objectives of users and operators. A new approximative algorithm based on the GRASP metaheuristic is proposed to solve the TNDP. This algorithm can be classified as a multi-objective metaheuristic since it produces a set of non-dominated solutions in a single run. It differs from most previous approaches, which have used the Weighted Sum Method to generate a set of non-dominated solutions by running a single-objective optimization algorithm for several weights representing different trade-off levels between the conflicting objectives. Numerical results are presented, showing that the multi-objective metaheuristic is more efficient in terms of execution time than the Weighted Sum Method.