Bio-Inspired Algorithms for Optimal Design of Trusses

Abstract

Trusses are one of the major civil engineering structural articulations that are studied for optimized design. However, application of bio-inspired algorithms for the design of planar trusses is found to be scanty. In this paper, four bio-inspired algorithms namely, Elitism based genetic algorithm (EBGA), Ant colony optimization (ACO), Artificial honey bee optimization (AHBO), and Particle swarm optimization (PSO) algorithms have been implemented for the optimization of size of the members of planar trusses. For this purpose, 4-planar trusses have been considered. The results show that the said algorithms vary marginally as far as the optimized weights are concerned. However, the differences are seen in terms of number of iterations required for convergence and standard deviation of weights. In this context, PSO and EBGA, converged quickly for all the four examples considered. Both the algorithms also showed lower values of standard deviation with respect to the optimized overall weight of the trusses.