[1]LIU Jiao,LIU Dong.Multi-objective Optimization of Hongxinglong Branch Bureau Water Resources Based on Mixed Genetic Algorithm[J].Research of Soil and Water Conservation,2013,20(06):177-181.
Copy
Research of Soil and Water Conservation[ISSN 1005-3409/CN 61-1272/P] Volume:
20
Number of periods:
2013 06
Page number:
177-181
Column:
Public date:
2013-12-28
- Title:
-
Multi-objective Optimization of Hongxinglong Branch Bureau Water Resources Based on Mixed Genetic Algorithm
- Author(s):
-
LIU Jiao1, LIU Dong1,2,3
-
1. School of Conservancy & Civil Engineering, Northeast Agricultural University, Harbin 150030, China;
2. Key laboratory of Water-saving Agriculture of Ordinary University in Heilongjiang Province, Harbin 150030, China;
3. Key laboratory of Effective Utilization of Agricultural Water Resources of Agriculture Ministry, Harbin 150030, China
-
- Keywords:
-
water resources; optimal allocation; mixed genetic algorithm; Hongxinglong branch bureau
- CLC:
-
TV213.9
- DOI:
-
-
- Abstract:
-
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.