Space trusses optimization using metaheuristic methods: a review

Resumo

Space trusses are one of the most widely studied elements in structural optimization. Many
metaheuristics were used for this purpose over the years, ranging from established methods such as Genetic
Algorithms (GA) and Simulated Annealing (SA), through widespread population methods like Ant Colony
Optimization (ACO) and Particle Swarm Optimization (PSO) reaching the new generation of heuristic search
algorithms (Mine Blast Optimization (MBO), Bat-Inspired Algorithm (BA) and the Charged System Algorithm
(CSA), for example). In recent years, in addition to the appearance of numerous brand new search methodologies,
it has become extremely common the use of hybrid search methods - mixing two or more algorithms - for the
optimization of space trusses. With focus on the exponential increase in publications on the subject, the present
work reviews studies about the optimization of space trusses using heuristic methods, searching studies available
in scientific journals and classifying them using an own methodology. At the end of the article, an overview of the
topic is reported.