Optimization of the Cross Section of a Concrete Gravity Dam with Shuffled Frog Leaping Algorithm (SFLA)

Optimizing the dimensions of concrete gravity dams can reduce the volume of concrete needed to build these structures and thus the material and construction cost of these projects. In this study, dimensions of a concrete gravity dam were optimized by the use of Shuffled Frog Leaping Algorithm (SFLA). The dam chosen as the subject of the case study was the Koyna dam in India. The dimensions of this dam were optimized subject to stability and stress constraints. The results were compared with the actual dimensions of the dam and the results of similar optimization methods. Using SFLA, the volume of concrete needed to build the dam was optimized to ۲۹۴۳m۲ per unit length, which is ۱۸.۹۹% lower than the actual amount used in the dam, ۱۱.۱۵% lower than the output of the Honey-Bee Mating Optimization algorithm (HMBO) and ۱۰.۲۲% lower than the result of the Imperialist Competitive Algorithm (ICA). These results demonstrate the excellent capability of SFLA in optimizing the cross-section of concrete gravity dams and its ability to outperform both HMBO and ICA in this application.