Application of Improved Genetic Algorithms in Solving the Portfolio Based on Constraining the Ratio

被引:0
|
作者
Cai, Fei [1 ]
Liu, Tie-Ying [1 ]
机构
[1] Inner Mongolia Univ, Coll Comp Sci, Hohhot, Peoples R China
关键词
Genetic Algorithms; combinatorial investment; profit; constraining investment;
D O I
暂无
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Genetic Algorithms can be applied to different portfolio areas. In order to better the decision-making of different models of investment, different Genetic Algorithms are required. In view of venture investment model for constraining investment, improving Genetic Algorithms is used to solve the global optimal solution of the model. The principles which are concerned with coding, selection, crossover and mutation of the Genetic Algorithms are studied in-depth and a new model is designed by combining with the areas of application. The process of genetic Algorithms is simulated in the new model and ultimately the optimal solution is given. The model works by using matlab tools and a large number of experimental data.
引用
收藏
页码:169 / 173
页数:5
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