Performance Comparison of Modern Methods in Optimization of Reinforced Concrete Structures Using a Case Study

The overall objective of this research is to optimize the design process of a fixed-endreinforced concrete beam under assumed loading using five algorithms (interior-point, genetic,exterior penalty function with interior-point, pattern search, exterior penalty function withsimulated annealing algorithms). The significant increase in construction material prices alongwith considerable developments in computer science has led to the emergence of variousoptimization techniques and their application in structural engineering. Therefore, evaluatingthe efficiency of novel optimization methods in reinforced concrete structures design is ofnoteworthy importance, which is investigated in this study. The findings indicate that utilizingthe mentioned optimization algorithms in designing the beam reduces the construction cost by۲۲% on average, with the interior-point algorithm decreasing the cost by ۳۵% as the mostefficient one, furthermore the average time required to achieve optimal designs isapproximately ۶ seconds, with the pattern search algorithm requiring as little as ۱ second theshortest duration needed.

کلیدواژه ها:

optimization of structures ، reinforced concrete structures ، machine learningmethods ، interior-point ، genetic ، exterior penalty function ، pattern search ، simulated annealingalgorithms