Optimization Modelling of Irrigation Channel Considering Flooding Conditions and Uncertainty

In the present study, for the first time, metaheuristic Bat Algorithm (BA) is proposed for design of irrigation-channel cross section with minimum construction costs and taking into account flood probability as a constraint and uncertain parameter. For this purpose, considering cross section of the channel with uniform and composite roughness and fixed and variable freeboard, three models are defined as: a) uniform roughness+ fixed freeboard, b) composite roughness+ fixed freeboard, and c) composite roughness+ variable freeboard. The proposed algorithm is implemented for the first to third models, based on the results of sensitivity analysis. Coefficient of variation and convergence speed of the 15 random runs of the mentioned algorithm is compared for 0.36flood probability. At last, results of the mentioned algorithm for different flood probabilities have been compared with the results of Lingo software, Lagrange multiplier, sequential minimal programming and Particle Swarm Optimization Algorithm. Results of the random runs showed that coefficient of variation for the first to third models is 0.00049, 0.00019 and 0.00023, respectively, which are acceptable. Also, all three models converged after 500 iterations. Other results showed that using BA, with respect to other methods, increased optimization results up to 13.97 %. Furthermore, this algorithm estimated the global optimum up to 0.51% less than Lingo software. Among the three proposed models, using the third model saved construction costs by 59.6 and 53.87 percent, as compared to the first and second models, respectively.