Revisión del estado del arte (no sistemática) sobre el uso de algoritmos genéticos en la calibración de modelos de micro simulación vehicular

Abstract

This paper proposes a state-of-the-art review from 2011 to the present (2022) on the use of genetic algorithms (GA) to calibrate vehicle microsimulation models. Calibration is nothing more than the optimization process of models under comparing experimental and real parameters. Genetic algorithms (GA) were selected because of their excellent robustness and ability to work with large amounts of data. A total of 19 articles were selected from recognized research sources such as IEE Xplore, ScienceDirect, Springer Link, and Scopus, respecting all the selection and filtering criteria to work only with those that provide an adequate update of the topic. The results show that thanks to the update on this topic, it was possible to verify that the use of GA (Genetic Algorithms) in the calibration of vehicle microsimulation models can improve and accelerate the calibration process, which will help future research and publications.