COST OPTIMIZATION OF TRAPEZOIDAL FOOTINGS IN REINFORCED CONCRETE WITH COMPUTATIONAL TOOLS

This work investigates the optimization of the design of trapezoidal reinforced concrete footings, aiming to minimize the costs of materials and execution through a Nonlinear Programming model. The model was implemented in Python, with the Pyomo library and the IPOPT solver, considering continuous geometric variables, such as shoe width, length and height. The objective function intrinsically contemplates the costs of concrete, steel, formwork and excavation. Constraints include stiffness checks, permissible ground tension, pitching, slippage, eccentricity, diagonal compression, and compression connecting rod. The results indicated reductions in the volume of concrete, in the steel area and in the volume of excavation, maintaining compliance with the safety criteria. It is concluded that computational optimization represents a viable and economically efficient alternative for the design of shallow foundations.