| 改进的多目标量子遗传算法在南水北调东线工程江苏段水资源优化调度中的应用 |
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| 引用本文： | 方国华,郭玉雪,闻昕,黄显峰. 改进的多目标量子遗传算法在南水北调东线工程江苏段水资源优化调度中的应用[J]. 水资源保护, 2018, 34(2): 34-41 |
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| 作者姓名： | 方国华 郭玉雪 闻昕 黄显峰 |
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| 作者单位： | 河海大学水利水电学院; |
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| 基金项目： | 江苏省水利科技项目(2014012)；江苏省研究生培养创新工程(2016B03257) |
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| 摘 要： | 构建南水北调东线工程江苏段水资源优化调度模型,采用改进的多目标量子遗传算法(multiobjective quantum genetic algorithm,MOQGA),运用组合赋权方法对非劣解集进行多属性决策,提出南水北调东线工程江苏段水资源优化调度方案。在平水年、枯水年和特枯水年3种典型年来水条件下,相对于常规调度,优化调度的受水区总缺水量分别减少了0.89亿m3、0.87亿m3和0.08亿m3,系统总抽水量分别减少21.04亿m3、39.14亿m3和50.76亿m3。该优化调度方案能够充分利用湖泊的调蓄能力,提高各用水户的需水满足度,降低抽水成本。
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| 关 键 词： | 多目标优化 南水北调东线工程江苏段 改进的多目标量子遗传算法 水资源优化调度 |
| 收稿时间： | 2017-07-31 |
Appliacation of improved multi-objective quantum genetic algorithm on water resources optimal operation of Jiangsu Section of South-to-North Water Transfer East Route Project |
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| FANG Guohu,GUO Yuxue,WEN Xin and HUANG Xianfeng. Appliacation of improved multi-objective quantum genetic algorithm on water resources optimal operation of Jiangsu Section of South-to-North Water Transfer East Route Project[J]. Water Resources Protection, 2018, 34(2): 34-41 |
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| Authors: | FANG Guohu GUO Yuxue WEN Xin HUANG Xianfeng |
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| Affiliation: | College of Water Conservancy and Hydropower Engineering, Hohai University, Nanjing 210098, China,College of Water Conservancy and Hydropower Engineering, Hohai University, Nanjing 210098, China,College of Water Conservancy and Hydropower Engineering, Hohai University, Nanjing 210098, China and College of Water Conservancy and Hydropower Engineering, Hohai University, Nanjing 210098, China |
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| Abstract: | A water resources optimal operation model of Jiangsu Section of South-to-North Water Transfer East Route Project was developed in this study. The improved multi-objective quantum genetic algorithm was adopted and the multiple attribute decision making method of Pareto optimal set was applied based on a combination weighting approach. In the conditions of normal, dry, and extremely dry, compared with the conventional operation, the water shortage could be reduced by 0. 89 billion m3, 0. 87 billion m3, and 0. 08 billion m3, respectively, and the pumping amount of the system could be reduced by 20. 14 billion m3, 39. 14 billion m3 and 50. 76 billion m3, respectively, with the optimal operation. It shows that the optimal operation can make full use of the regulation and storage capacity of lakes, improve the satisfaction of water users, and reduce the cost of pumping. |
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| Keywords: | multi-objective optimization Jiangsu Section of South-to-North Water Transfer East Route Project improved multi-objective quantum genetic algorithm water resources optimal operation |
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