A newhybrid meta-heuristic for optimum design of frame structures

Meta-heuristic methods provide powerful means to optimize frame structures and hybridizing these methods seems to be unavoidable to improve the properties of the algorithms. This paper provides a new hybrid advanced algorithm by using the abilities of heuristic particle swarm ant colony optimization (HPSACO) and a hybrid big bang-big crunch algorithm (HBB-BC). The advantages of the HPSACO and HBB-BC are combined to improve the performance of the resulted algorithm. In the present approach, there are three main steps as global searching step, local searching step and location controlling step. These steps all together improve the exploration and exploitation abilities of the algorithm. The proposed method is tested on frame structures from the literature. The results of the optimum design obtained by the present study are compared to those of some existing optimization methods to verify the suitability of the new method.