Abstract
Engineers usually use trial-and-error approaches for dealing with design problems where they need to find the most economical design of a structural element in terms of its material cost while satisfying all the safety requirements imposed by the design codes. In this study, we employ a genetic algorithm (GA) with a dominance-based tournament selection technique for dealing with this design challenge. The methodology is applied in the design of reinforced concrete rectangular-shaped isolated footings in accordance with the American Concrete Institute ACI 318-19. First, the footing is encoded into a set of decision variables and an objective function is defined to compute the total cost based on the different construction materials. Then, the compliance of the design with the ACI 318-19 code is enforced by a constraint function that takes into consideration all the demand–capacity ratios for the different resistance requirements such as the allowable bearing pressure of the supporting soil, and the shear and flexural capacities of the footing, among others. Two numerical examples are presented where the results show a significant advantage in terms of material-cost and design-time reduction in comparison with the commonly used trial and error approach, proving the applicability of optimization algorithms (OAs) into the everyday design routine of the structural engineer.
Highlights
With the development of modern computing, optimization algorithms (OAs) have emerged as powerful design tools in practically all fields of engineering
One of the reasons for this is that the design of these elements usually requires fast, reliable, and sometimes on-the-go solutions for which the complexity of an optimization algorithm seems to be not worth the benefits obtained compared to traditional trial-and-error approaches, which take advantage of the experience of the engineer
The motivation for using modern computational techniques to optimize the structural design of a construction comes as an answer to the fact that the construction industry consumes a huge amount of resources, which contributes to a high amount of greenhouse gas emissions
Summary
With the development of modern computing, optimization algorithms (OAs) have emerged as powerful design tools in practically all fields of engineering. One of the reasons for this is that the design of these elements usually requires fast, reliable, and sometimes on-the-go solutions for which the complexity of an optimization algorithm seems to be not worth the benefits obtained compared to traditional trial-and-error approaches, which take advantage of the experience of the engineer. This conception is changing rapidly nowadays with the development of ready-to-use optimization tools and libraries that require either a small amount of coding or are based on a user-friendly interface that takes the coding complexity away. Buildings and construction generate nearly 40% of global CO2 emissions according to the 2019 Global Status
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