Structural Design Applications of the Two-Branch Tournament Genetic Algorithm

Abstract

Abstract The two-branch tournament Genetic Algorithm (GA) is a population-based search technique that generates a large number of designs to approximate the Pareto-optimal set of designs for problems with two objectives. The two-branch GA can accommodate problems with a mix of discrete and continuous design variables and problems with discontinuous and/or multimodal objectives. The two-branch GA was applied to several multiobjective structural design problems: a ten-bar truss, Golinski’s speed reducer, a multi-material ten-bar truss, and a stiffened composite panel. Where possible, GA results were compared to traditional multiobjective optimization results. The two-branch GA appears to have advantages over traditional approaches for problems with non-smooth Pareto fronts and / or combined variable types. The studies led to conclusions about the two-branch GA for multiobjective structural design.