Optimal Design of River Groynes using Meta-Heuristic Models

Abstract

So far, several researchers have conducted many studies on the effective parameters in the design of river breakwaters, which are mostly laboratory-based and are used for limited conditions. Therefore, the aim of the present studywas to optimal design of structure and to present analytical results of Zanjanrood river breakwaters (in terms of length and distance between two consecutive breakwaters) using two optimization meta-heuristic algorithms including the Gray Wolf Algorithm (GWO) and the Election Algorithm (EA). The results were compared with artificial neural network (ANN) method. The data used were randomly divided into two parts: 75% for calibration and 25% for test. The performance of the proposed methods was evaluated using the statistical indicators of coefficient of determination (R2), root mean square error (RMSE) and mean absolute error (MAE). The optimal length of the breakwaters according to the results of GWO and EA algorithms was 19.26 and 18.12 m, respectively. Moreover, the optimal distance between two consecutive breakwaters in the optimal state was calculated to be 52.56 m. On average, according to the results of the optimization, an increase of 28.4 and 35% in length and distance between two consecutive watersheds in Zanjanrood River should be done to be within the recommended design criteria. In comparison with two methods of EA algorithm and artificial neural network (ANN), based on statistical indicators, the results of GWO algorithm with values ​​of R2 = 0.96, RMSE 0.022 and MAE = 0.016 has a higher efficiency.

Keywords

• ann
• election algorithm
• grey wolf algorithm
• groyne
• optimization