Metaheuristic algorithms in optimum design of reinforced concrete beam by investigating strength of concrete

Abstract

The locations of structural members can be provided according to architectural projects in the design of reinforced concrete (RC) structures. The design of dimensions is the subject of civil engineering, and these designs are done according to the experience of the designer by considering the regulation suggestions, but these dimensions and the required reinforcement plan may not be optimum. For that reason, the dimensions and detailed reinforcement design of RC structures can be found by using optimization methods. To reach optimum results, metaheuristic algorithms can be used. In this study, several metaheuristic algorithms such as harmony search, bat algorithm and teaching learning-based optimization are used in the design of several RC beams for cost minimization. The optimum results are presented for different strength of concrete. The results show that using high strength material for high flexural moment capacity has lower cost than low stretch concrete since doubly reinforced design is not an optimum choice. The results prove that a definite metaheuristic algorithm cannot be proposed for the best optimum design of an engineering problem. According to the investigation of compressive strength of concrete, it can be said that a low strength material are optimum for low flexural moment, while a high strength material may be the optimum one by the increase of the flexural moment as expected.