Optimization of Truss Structures by Using a Hybrid Population-Based Metaheuristic Algorithm

Structural engineering is a field with several optimization approaches. Concordantly, the goal in optimum design is the generation of the lightest, cheapest, or most sustainable engineering design for any type of structure or structural member. In this study, some optimization approaches were presented for structures including 25 and 72-bar space trusses. To find the smallest weights were ensured for both structures. Optimization approaches related to metaheuristics and modifications of them were developed by inspired by features of nature, abilities of lives and mechanisms of chemical/physical processes. The employed three techniques that are flower pollination algorithm, Jaya algorithm and the hybrid algorithm developed via them were compared to each other through some parameters by calculating different statistical expressions containing the best, average and standard deviation of the objective function. Also, the performance of whole metaheuristic versions is evaluated with some literature researches to find the most effective one to minimize the structural weights. These results have observed that the all versions of proposed metaheuristic algorithms are generally successful, and effective to minimize the objective function comparison to algorithms used in previous studies. Moreover, the best values of objective functions can be decreased at the 0.02-0.06 rates as minimum and maximum compared to the previous studies and algorithms, respectively.

Automated summary

This study presents optimization approaches for structural engineering, focusing on minimizing weight. Different metaheuristic algorithms were developed and compared, and the results showed that all versions of the proposed algorithms were successful in minimizing structural weight, outperforming previous studies and algorithms.