Comparative Optimization Study of an Isogrid Structure Using Sunflower Optimization and Genetic Algorithm

Resumo

Isogrid structure emerged in the early 1970s due the need for lightweight and high-performance model
in the aeronautical industry, however, over the years, several other branches that also need these characteristics
began to use this type of components. The present work aims to find the optimal design parameters for the lattice
structure in order to minimize the Tsai-Wu failure index and the mass of the structure under compression loads by
using two different metaheuristics algorithm: Genetic Algorithm (GA) and Sunflower Optimization (SFO). A
Response Surface Methodology (RSM) was used for the purpose of setting up a series of experiments for adequate

predictions of the responses and the generated models were used as objective functions for single and multi-
objective optimizations. Finally, the results of both algorithms were compared with finite element method and the

performance of the new meta-heuristics algorithm SFO was evaluated.