Weight Optimization of Truss Structures by the Biogeography-Based Optimization Algorithms

The fundamental concepts of biogeography-based optimization (BBO), a meta-heuristic algorithm, have been inspired by the geographical distribution of animals. This algorithm does not need a starting point, and performs a random search instead of a gradient-based search. In this article, for the first time, the weights of 2D and 3D trusses with specific geometries and different stress and displacement constraints have been optimized by using the BBO approach. Also, in this work, the numerical results achieved by other researchers through various optimization techniques have been compared with the results obtained from the Particle Swarm Optimization (PSO), Differential Evolution (DE) and BBO algorithms. It has been demonstrated that the search and exploration capability of the BBO algorithm is superior to that of the DE and PSO algorithms, and that it achieves better results than the other optimization techniques considered in this paper. This superiority is due to the excellent exploration capability of the BBO algorithm and the fact that it achieves a favorable optimal solution in the initial iteration.