Large extragalactic surveys have contributed enormously to  our understanding of cosmology and the formation of galaxies in the last decades.

Currently, with the advent of revolutionary knowledge projects such as Euclid and the Large Synoptic Survey Telescope (LSST), cosmological simulations play a fundamental role both in the design of these surveys and in the interpretation of the data that will be collected. These are required to establish the theoretical predictions, to generate catalogs that allow quantifying systematic observational and selection effects, to perform  data analysis and to optimize observation strategies. Among the types of simulations used to understand the evolution of galaxies, the semi-analytical  models of galaxy formation and evolution acquire strategic importance given their advantage in low computational cost and theoretical predictability.

We present results of the semi-analytical code SAG, which was modified and adapted to the dark matter only MultiDark simulation MDPL2 with the aim of generating galaxy catalogs of large-scale. We have improved particular aspects of the physical model that allow  us to generate populations of galaxies with properties more  consistent with observed ones.