Optimal construction of an open channel by considering different conditions and uncertainty: application of evolutionary methods

Abstract

In the present study, different evolutionary methods, namely the bat algorithm (BA), particle swarm optimization (PSO) and their hybrid (HBP), are employed for the design of trapezoidal open-channel cross-sections with minimum construction cost (concrete lining plus excavation costs). For this purpose, considering open channels with uniform and composite roughness, fixed and variable freeboard, and also velocity, Froude number and flooding probability constraints, eight models were defined. The performance of HBP in terms of convergence rate was investigated using 10 random runs, and the resulting coefficient of variation for different models was 0.00001–0.002. Solutions of HBP were also compared to those of other optimization algorithms. The results indicated that using HBP, compared to BA, PSO, LINGO, Lagrange multiplier method and shuffled frog-leaping algorithm, led to a 32% saving in construction cost. Therefore, HBP has high potential for the optimal design of open channels.