Optimization of water resources utilization by GA-PSO in the Pinshuo open pit combined mining area, China

The Pinshuo open pit combined mining area in China has multiple types of water sources and uses with various water quality requirements, and thus there is an urgent need to optimize the allocation of water resources to protect regional water resources and reduce water costs. Therefore, a genetic algorithm-particle swarm optimization (GA-PSO) was proposed and applied to allocate the water resources of different water demands in this region. The experimental results suggested that the GA-PSO algorithm could simultaneously obtain a promising solution and speed up the convergence. The configuration results of 95%, 100% and 120% water consumption scenarios could all achieve predefined environmental and economic goals. Specially, the configuration result of 100% water consumption scenario was much more economical and environmentally friendly than that of the actual operation in 2016. For example, the proportion of renewable water (80.74%) of the configuration scenario was higher than that in 2016 (67.58%). Meanwhile, the groundwater of Liujiakou water source was not allocated, and thus local water resources were protected. Besides, the percent of low price (<= 2.26 RMB/ton) water (76.12%) was also much larger than that (53.29%) in 2016, indicating low water costs of the configuration scheme. Moreover, reliability and uncertainty analysis indicated that the final results were all reliable and resilient and had low uncertainty and vulnerability.