COST OPTIMIZATION OF TRAPEZOIDAL FOUNDATIONS IN REINFORCED CONCRETE

This study investigates the optimization of a reinforced concrete foundation for buildings, focusing specifically on a trapezoidal footing, using a Nonlinear Programming (NLP) model. The objective of the model is to minimize the consumption of concrete and steel in the construction of this structural system, according to Brazilian standards to ensure the safety of the building. The model solution determines the optimal dimensions of the footing and the amount of steel required, respecting the construction and regulatory constraints. The proposed model is feasible for practical implementation and was developed in Python, using specific libraries to solve non-linear programming problems.