Sizing, layout and topology design optimization of truss structures using the Jaya algorithm

Abstract

A very recently developed metaheuristic method called Jaya algorithm (JA) is implemented in this study for sizing and layout optimization of truss structures. The main feature of JA is that it does not require setting algorithm-specific parameters. The algorithm has a very simple formulation where the basic idea is to approach the best solution and escape from the worst solution. The original JA formulation is modified in this research in order to improve convergence speed and reduce the number of structural analyses required in the optimization process. The suitability of JA for truss optimization is investigated by solving six classical weight minimization problems of truss structures including sizing, layout and large-scale optimization problems with up to 204 design variables. Discrete sizing/layout variables and simplified topology optimization also are considered. The test problems solved in this study are very common benchmarks in structural optimization and practically describe all scenarios that may be faced by designers. The results demonstrate that JA can obtain better designs than those of the other state-of-the-art metaheuristic and gradient-based optimization methods in terms of optimized weight, standard deviation and number of structural analyses.