Optimal load and resistance factor design of geometrically nonlinear steel space frames via tabu search and genetic algorithm

In this paper, algorithms are presented for the optimum design of geometrically nonlinear steel space frames using tabu search and genetic algorithm. Tabu search utilizes the features of short-term memory facility (tabu list) and aspiration criteria. Genetic algorithm employs reproduction, crossover and mutation operators. The design algorithms obtain minimum weight frames by selecting suitable sections from a standard set of steel sections such as American Institute of Steel Construction (AISC) wide-flange (W) shapes. Stress constraints of AISC Load and Resistance Factor Design (LRFD) specification, maximum drift (lateral displacement) and interstorey drift constraints, size constraints for columns were imposed on frames. The algorithms were applied to the optimum design of three space frame structures. The designs obtained using tabu search were compared to those where genetic algorithm was considered. The comparisons showed that the former algorithm resulted in lighter structures.