Designing a congestion pricing scheme involves a number of complex decisions. Focusing on the quantitative parts of a congestion pricing system with link tolls, the problem involves finding the number of tolled links, the link toll locations and their corresponding toll level and schedule. In this paper, we develop and evaluate methods for finding a most efficient design of a congestion pricing scheme in a road network with elastic demand. The design efficiency is measured by the net social surplus, which is computed as the difference between the social surplus and the collection costs (i.e. setup and operation cost) of the congestion pricing system. The problem of finding such a scheme is stated as a combinatorial bi-level optimization problem. On the upper level we maximize the net social surplus and on the lower level we solve a user equilibrium problem with elastic demand, given the toll locations and toll levels, to simulate the user response. We modify a known heuristic procedure for finding the optimal locations and toll levels given a fixed number of tolls to locate, to find the optimal number of tolls to locate as well. A new heuristic procedure is also presented which is based on repeated solutions of a continuous approximation of the combinatorial problem. Numerical results for two small scale test networks are presented. Both methods perform satisfactory on the two networks. Comparing the two methods, the iterative approximation procedure is the one which shows the best results. The results are compared to solutions obtained by an exhaustive search.