Method of reservoir optimal operation based on improved simulated annealing genetic algorithm

被引：0

作者：

Li, Chenming ^{[1
]}

Xu, Baohua ^{[2
]}

Gao, Hongmin ^{[1
]}

Yin, Xueying ^{[1
]}

Xu, Lizhong ^{[1
]}

机构：

[1] College of Computer and Information Engineering, Hohai University, Nanjing 211100, China

[2] Yangtze River Estuary Survey Bureau of Hydrology and Water Resource CWRC, Ministry of Water Resources, Shanghai 200136, China

来源：

Sensors and Transducers | 2013年 / 159卷 / 11期

关键词：

Genetic algorithms;

D O I：

暂无

中图分类号：

TG156 [热处理工艺];

学科分类号：

摘要：

According to the specific circumstances of Wanjiazhai Reservoir, establish a reservoir optimal scheduling nonlinear mathematical model with a maximum generation capacity target, this paper uses an improved simulated annealing genetic algorithm to solve the model. The algorithm is in view of the defects of the traditional simulated annealing genetic algorithm to improve the algorithm from three aspects: introducing the niche technology, using adaptive crossover and mutation strategy, using the elitist strategy during the selection. Through examples are calculated and compared with the traditional simulated annealing genetic algorithm, the improved algorithm effectively overcomes the stagnation phenomenon, to enhance the global search ability. Its optimization performance is better than that of the traditional simulated annealing genetic algorithm. © 2013 by IFSA.

引用

页码：160 / 166