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This paper presents a novel multimodal evolutionary optimization algorithm for the complex problem of concurrent and integrated design of a mechatronic system, with the objective of realizing the best topology and the best parameters from a multicriteria viewpoint and with different preferences. The associated search space can be large and complex due to the existence of different classes of configurations, possible topologies, and the parameter values of the elements. The proposed algorithm efficiently explores the search space to find several elite configurations for different preferences, with more detailed competition by incorporating the domain knowledge of experts and considering some criteria that are not included in the course of regular evolutionary optimization. The developed approach consists of a two-loop optimization. For each topology, a genetic algorithm-based optimization is performed to find an elite representative of the topology. The elites will compete with each other to become the best design. A strategy of restricted competition selection is employed in the competition of topologies, with the aim of finding alternative elites from which the one that best satisfies the customer preference may be chosen. The designer may incorporate a higher level competition between elites in order to obtain the global optimum.