This paper presents a new burst detection and location technique for pressurized pipelines based on an extension of the Differential Evolution (DE) algorithm. The proposed approach addresses the burst location problem as an optimization task, by considering the dynamic model that describes the behavior of a fluid through a pipeline and the presence of fluid losses produced by a burst. The optimization problem relies on finding suitable estimations related to the burst parameters, i.e. magnitude, pressure and position of a burst, while a defined cost function is minimized. In order to deal with this problem, three strategies are proposed to extend and adapt the DE algorithm: (i) an informed definition of the physical restrictions of the problem according to the pipeline characteristics; (ii) a training stage of the algorithm that allows to find the appropriate synthesis parameters; (iii) a multi-start structure, in order to track dynamical variations of the problem. Experiments on a pipeline prototype illustrate the results obtained by the proposed algorithm on the estimation of the burst parameters, comparing its performance with an algorithm based on the Extended Kalman Filter, which is widely used in the literature.