In this study, real size complex steel space frame structures are numerically designed to achieve optimal design weight. For this aim, standard cuckoo search algorithm is rectified through a newly proposed adaptive method over two fundamental algorithmic parameters of alien egg probability detection (Pa) and step size control (α) to overcome incompetency of trapping into local optima. Besides, to strengthen exploitation phase of newly proposed algorithm, it is boosted with greedy selection (GS). So, novel algorithm has more promising exploration and exploitation capabilities. An 8-story, 1024-member and a 20-story, 1860-member real size complex steel space frame structures are selected as design examples. Also, initially to verify the supremacy of novel algorithm, a well-known welded beam is optimized as a benchmark structural design problem. Afterwards, the steel space frame structures are optimally designed via novel algorithm. Since ready steel section lists are utilized as selection pool for design variables, discrete programming problem is come into existence. The dead, live, snow, and wind design loads acting on frame structures are calculated in direction of ASCE 7-05 provisions. Furthermore, the structural design constraints are determined from LRFD-AISC specifications. Eventually, the newly proposed adaptive cuckoo search algorithm boosted with GS presents outstanding algorithmic performance.
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CITATION STYLE
Carbas, S., & Tunca, O. (2024). Numerical design optimization of real size complex steel space frame structures using a novel adaptive cuckoo search method. International Journal for Numerical Methods in Engineering, 125(4). https://doi.org/10.1002/nme.7386