In the traditional design methods for mechatronic systems, different subsystems are designed sequentially. It must be mentioned that due to complicated interactions between the subsystems in a mechatronic system, optimum operation of the connected subsystem resulted by using traditional design methods is under question. In recent mechatronic design literature, it is proposed that these systems need a concurrent and integrated design methodology in order to achieve the optimum operational features. There have been efforts for automation of the design process, and to incorporate more intelligence in the new proposed methods for concurrent design of mechatronic systems. In this work, an automatic design methodology, which is resulted from the integration of bond graphs and genetic programming is utilized for the concurrent optimum design of the topology and parameters of mechatronic systems. First, the fundamentals of the integration of bond graphs and genetic programming, and the procedure of the composition of the first random generation of the solutions are explained. Also, different steps and required elements for solving a design problem with this integrated tool are defined. In order to improve this optimization method, a memory scheme is incorporated in exploration tool. Similar topologies that may be created during the design process can be recognized by this mean. By eliminating the repetitive topologies from the next levels of design (i.e. simulation, derivation of the state space equations and optimization of the parameters for each created solution), the time needed for the design process is reduced effectively. In the next step, in order to represent a more intelligent tool, the dynamic tuning capability for the fundamental parameters in the fitness evaluation is developed. Thus, further modifications that are needed for the evaluation of fitness for each created solution are implemented automatically during the design process, and as a result, all the operational criteria and conditions that are considered for the system design are concurrently optimized. The idea of dynamic tuning is applicable on different evolutionary algorithms. This capability is utilized for the concurrent design of a 3-DOF pick and place robotic manipulator using genetic algorithm. The structural parameters, controller gains and the desired trajectory equations for this robot are optimized concurrently. The dynamic tuning capability is used in order to adjust the changing range of the several involved criteria in the fitness function. Optimizing the parameters and topology concurrently for mechatronic systems is a higher level of automatic design for these systems. In the last step, the mechatronic design methodology using the integration of bond graph and genetic programming is utilized for the first time to automatically evolve and synthesis the topology and sizing of a hydraulic engine mount. As the result, several novel hydraulic engine mount models are proposed that the notch frequency and the amount of dynamic stiffness in this frequency are kept unchanged, while the peak frequency is eliminated. Because of these remarkable improvements in the operational behavior of the new models, two solutions have been chosen as the best ones according to practical criteria, and the proper physical models are proposed for these models. Keywords: Mechatronic systems, Automatic and concurrent design, Bond graph, Genetic programming, Genetic algorithm, Hydraulic engine mount.