Generative design is the alteration of an object's shape to optimize its function. Currently, the scope of generative design is limited in the structural civil engineering field. Structural design still follows conventional methods compatible with conventional construction processes. These processes restrict the flexibility in design resulting in structural elements having excess materials to satisfy critical structural capacity requirements. This introduces additional costs and higher environmental impacts. New tools, such as concrete and steel 3D printers, are emerging to enable more complex geometries in construction allowing higher flexibility in design options. Inspired by the above, this paper aims at developing a design engine that provides optimal design solutions to reinforced concrete beams with sufficient structural capacities while using less materials and resources. Based on ACI code design guidelines, a cantilever beam was structurally analyzed to relate geometry parameters to structural capacity. Optimization was achieved by minimizing the depth and the steel reinforcement ratio at each segment along its length. Hence, concrete and steel at each location would take their optimal quantities. This results in lighter and more economic structures conforming to the structural capacities required by the codes. The engine is based on three objective functions that solve for the minimum values of beam depth and reinforcement at each section which optimize cost and CO2 emissions individually or simultaneously. MATLAB was used to design the optimized beam and to calculate the percentage decrease in cost and CO2 emissions between the optimized and conventional beam. A significant reduction ranging between 40% and 52% of cost and between 39% and 51% of CO2 emissions per beam is achieved. If the design engine developed was utilized in parallel with the 3D printing construction method, structures with optimized quantities, materials, and shapes would be developed. Thus, minimizing drastic effects on the environment and achieving reduced costs.

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