2021 Volume 77 Issue 2 Pages I_13-I_24
Swarm-based algorithms are a powerful family of optimization techniques inspired by forming flocks, colonies and swarms. Here we show that a superior performace in convergence and precision of cuckoo search algorithm and gley wolf optimizer, which are recently developed meta-heuristic algorithms, through benchmark functions. The numerical optimization problem in groundwater discipline was carried out to estimate the spatial distribution of hydraulic conductivity in a limestone region in subsurface dam. Identified groundwater levels through seepage analysis were good agreement with the observed data not only at monitoring wells but at pumping wells where observation data were not utilized in search computation. Subsequent solute transport simulations using random walk particle tracking linked with a spatial pollution risk by nitrate associated with seasonal variation of groundwater pumping, demonstrating a unique application derived from inverse analysis to a practical design in the field.
