Comparison of multi-objective particle swarm algorithms for truss design optimization
Palavras-chave:
Multi-objective truss optimization, Particle Swarm Optimization, Structural optimizationResumo
Multi-objective structural optimization problems (MOSOPs) with two or more objectives are extensively
considered in the literature. Due to the great interest in solving these types of problems, several Multi-objective
Evolutionary Optimization Algorithms (MOEAs) have been developed. They are applied to problems in several
fields, mainly engineering. This paper compares multi-objective optimization algorithms based on swarm intel-
ligence and applies them to solve structural optimization problems concerning three objectives. The objective
functions are the weight, the natural frequencies of vibration, and the maximum nodal displacement, considering
stress constraints. The design variables, discrete or continuous, are the cross-sectional areas of the bars. Some
traditional benchmark problems in the literature in structural engineering applications were performed. Finally,
Pareto sets are presented where a Multi Tournament Decision (MTD) method is adopted to extract the desired
solutions from these problems.
