An exponential big bang-big crunch algorithm for discrete design optimization of steel frames

In the present study an enhanced variant of the big bang-big crunch (BB-BC) technique, namely exponential BB-BC algorithm (EBB-BC) is developed for code based design optimization of steel frame structures. It is shown that the standard version of the BB-BC algorithm is sometimes unable to produce reasonable solutions to problems from discrete design optimization of steel frames. Hence, through investigating the shortcomings of BB-BC algorithm, it is aimed to reinforce the performance of the technique for this class of problems in particular. The study provides numerical evidences of how the performance of a well-known metaheuristic technique (BB-BC) can significantly be improved through simple yet effective modifications in its formulation to achieve a more robust and reliable variant (EBB-BC). Further, a comparison of the optimum solutions with those of other well-known metaheuristics reveals that the EBB-BC algorithm can efficiently be used as a novel tool for code based design optimization of steel frames.

► Two weaknesses of standard BB-BC algorithm identified. ► A reformulation of BB-BC algorithm (EBB-BC) achieved for structural optimization. ► EBB-BC leads to an exceptional performance improvement of the technique. ► EBB-BC outperforms other metaheuristics in design optimization of steel frames.