Optimización del Diseño de Estructuras Metálicas mediante Inteligencia Artificial y Algoritmos.

Abstract

This research examines the incorporation of advanced computational methods to enhance the design process of metallic structures, identifying the shortcomings of traditional procedures which, although ensuring structural safety, limit the development of more cost-effective alternatives in terms of material usage and environmental impact. This study analyzes the use of evolutionary computational techniques, artificial neural processing architectures, and automated learning systems as complementary tools aimed at improving quality, optimization, and accuracy in structural engineering project development, thereby overcoming the limitations presented by traditional methods. The present work aims to develop a methodology that integrates advanced technologies through the use of indicators of structural, economic, and sustainability effectiveness, in order to demonstrate the capability of these systems to automate complex calculations, predict the behavior of structural elements, and provide optimized solutions that consider multiple variables while complying with current regulations. The scope of this research encompasses a review of theoretical foundations and steel design codes, as well as normative guidelines, extending to practical application, analysis of results obtained from computational models, and the theoretical basis for the critical implementation of new technologies in the field of structural engineering. The primary purpose is to promote a more coordinated, ecological, and intelligent design ethic for modern construction systems and their operations, significantly contributing both to the body of knowledge and to the practice of advanced computational design methodologies in metallic structures.