The orthorectification of very high resolution (VHR) satellite images is a fundamental process to ensure the interoperability of the spatial information obtained from them. Therefore, previous studies have used different types of inputs, including multiple sources of control points and digital elevation models (DEM) of all kinds, in addition to testing different optimization methods. This research aims to jointly use and evaluate the use of the evolutionary algorithm Particle Swarm Optimization (PSO), stereoscopic points from photogrammetric blocks and DEM from different sources, to obtain cartographic products of scale 1:10.000 comparing their results with those obtained by ordinary least squares from previous experiments. The methodological proposal includes the entire procedure for the estimation and selection of the coefficients of the Rational Functional Model (RFM) spatial arrangement model using Particle Swarm Optimization and the Feature Condition Analysis method together with all the flow necessary for the generation of the final orthoimage. As a result, it is observed that the use of the PSO improves on average by 3% the positional accuracy of the orthoimage, however its use requires high computational resources and also this type of optimization method is not available yet in specialized software, being difficult for massive implementation in cartographic production processes.