为解决复杂的区域水资源优化配置问题，以区域缺水率最小和污染物排放量最小为目标函数建立了水资源优化配置模型，并以汾河下游谷地供水区为例，预测其在规划水平年20％、50％、75％和95％来水频率下的供需水量。针对飞蛾扑火算法（MFO）存在的搜索耗时较长、易陷入局部最优的问题，改进其烛火更新公式及对数螺旋函数。通过对群智能算法中常用的测试函数做仿真实验，对比分析了改进前后MFO算法的寻优结果，并采用改进的MFO算法对模型进行求解。实例结果表明，所构建的区域水资源优化配置模型合理有效，改进的飞蛾扑火算法收敛速度快，寻优性能优越，可用于水资源优化配置领域。

The water resource optimization allocation model is established with the minimum regional water shortage rate and the minimum pollutant emission as the objective function． Taking the valley in the lower reaches of the Fenhe Ｒiver as an example，this paper predicts the water supply and demand in 2025 on condition of 20%，50%，75% and 95% rainfall frequency． Aiming at the problem that the calculation of Moth－Flame Optimization algorithm takes a long time and is easy to fall into local optimum，the adaptive formula for the number of flames and the logarithmic spiral formula are improved． Through the simulation experiment of the test function commonly used in swarm intelligence algorithm，the optimization results of Moth－Flame Optimization algorithm before and after the improvement are compared and analyzed． The improved Moth－Flame Optimization algorithm is used to solve the model，and the results show that the water resource optimization allocation model is reasonable and effective，and the improved Moth－Flame Optimization algorithm has fast convergence rate and optimal performance， which can be used for an analysis of optimal allocation of water resources．