A novel simulation–optimization strategy for stochastic‐based designing of flood control dam: A case study of Jamishan dam
This study presents a novel stochastic simulation–optimization approach foroptimum designing of flood control dam through incorporation of varioussources of uncertainties. The optimization problem is formulated based on twoobjective functions, namely, annual cost of dam implementation and damovertopping probability, as those are the two major concerns in designing floodcontrol dams. The nondominated solutions are obtained through a multi-objective particle swarm optimization (MOPSO) approach. Results indicatethat stochastic sources have a significant impact on Pareto front solutions. Thedistance index (DI) reveals the rainfall depth (DI = 0.41) as the most significantfactor affecting the Pareto front and the hydraulic parameters (DI = 0.02) asthe least. The dam overtopping probability is found to have a higher sensitivityto the variability of stochastic sources compared to annual cost of dam imple-mentation. The values of interquartile range (IQR) indicate that the dam over-topping probability is least uncertain when all stochastic sources areconsidered (IQR = 0.25%). The minimum annual cost of dam implementation(2.79 M$) is also achieved when all stochastic sources are consi dered in optimi-zation process. The results indicate the potential of the proposed method to beused for better designing of flood control dam through incorporation of allsources of uncertainty.