Metaheuristic optimization of structural sets of reinforced concrete

I. Negrin, A. Negrin, E. Chagoyén


This paper presents the economic structural optimization of the Casa Síndico project using an algorithm programmed through the CSi API functions SAP2000v19-MATLAB R2015a, applying metaheuristic techniques: Genetic Algorithms (GA) and Particle Swarm Optimization (PSO), in addition to hybridization between them. The results show that PSO has a better performance than GA for this type of optimization, although both, working with their simple methodologies, are not completely efficient, which is verified when creating and applying a hybridization between the two, using GA to create an initial swarm for PSO to carry out the optimization process, obtaining results of up to 10% better. Regarding the structural results, a direct cost of construction is obtained by 13% more economical when applying the proposed methodology, leaving, for the beams, heights of relation L / h between 15 and 17.5, for the columns, the use of sections with rectangularities of up to 1.35, in the direction that more flexion occurs, something similar to what happens for the foundations, where the rectangularity of these follows the previous criterion, obtaining values of up to 1.4


Structural optimization, structural set, Metaheuristics, Genetic Algorithms, Particle Swarm Optimization



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