基于混合遗传算法的红兴隆分局水资源优化配置

针对区域水资源开发利用模式不合理、传统优化算法运行效率不高的问题，以红兴隆分局为例，对其水资源优化配置模型进行研究。基于大系统分解协调理论，以经济、社会、环境综合效益最大，考虑可供水量、用户需水量、水质为约束，构建了基于混合遗传算法的大系统多目标红兴隆分局规划年（2015年，2020年）水资源优化配置模型。结果表明:农业用水量是导致红兴隆分局水资源短缺的主要原因，应充分利用地表水和过境水，减少对当地地下水的开采，经过合理的优化配置，使得规划年缺水状况得到了改善。另外，优化后的水量较现实水量相比较显著减少，各目标效益也均呈现改善趋势，增加了配置结果的可信度；混合遗传算法克服了传统算法的不足，在运行速度上也有大幅度的提升。

Multi-objective Optimization of Hongxinglong Branch Bureau Water Resources Based on Mixed Genetic Algorithm

The water resources optimization model had been studied in terms of the uneven distribution of water resources of Hongxinglong branch bureau and the problems about low efficiency of the traditional optimization algorithm. By using the large system decomposition coordination theory, the multi-objective optimization of Hongxinglong branch bureau water resources had been established based on mixed genetic algorithm in different planning years(2015, 2020). The model tried to achieve the maximum economic, social, environmental benefits with water supply, water demand, water quality as the constraint conditions. Case study showed that agricultural water is the main reason for causing water resources shortage in Hongxinglong branch bureau, and should sufficiently utilizate the passing-by water and surface water, and reduce local groundwater exploitation.But the water shortages of planning years had been improved by the reasonable optimization. In addition, comparing with the quantity of water support without optimation, the optimized water support quantity had been significantly reduced and the target benefits also showed good improvement trends, which increased the credibility of the configuration result. The mixed genetic algorithm overcomes the weakness of the tradition optimization algorithm, so the efficiency had been greatly improved.