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A methodology for life cycle cost minimization on a set of highway concrete bridges during a medium/long term period of time is presented in order to help on structures management decision process. This methodology takes into consideration the direct and indirect costs associated to different kinds of interventions during bridges lifetime, uses some Markov Matrices as degradation model and applies a genetic algorithm to identify the optimized intervention plan, considering the available budget and the desired minimum performance level. Data’s uncertainty is treated in a probabilistic way and Monte Carlo Method simulation is used to highlight the most important parameters on the optimized solution identification.