Hybrid Teaching-Learning Based Optimization with Harmony Search for Engineering Optimization Problems

被引:0
|
作者
Ouyang, Haibin [1 ]
Ma, Ge [1 ]
Liu, Guiyun [1 ]
Li, Zhifu [1 ]
Zhong, Xiaojing [1 ]
机构
[1] Guangzhou Univ, Sch Mech & Elect Engn, Guangzhou 510006, Guangdong, Peoples R China
关键词
teaching-learning-based optimization; harmony search algorithm; learning operation; PARTICLE SWARM OPTIMIZATION; ALGORITHM; DESIGN;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In order to improve the performance of teaching-learning-based optimization algorithm, a hybrid teaching-learning-based optimization algorithm is presented in this paper. The hybrid approach combine with the strength of harmony search algorithm and teaching-learning-based optimization algorithm, which is aim to enhance the global search ability and local exploitation cababillity. Moreover, A new learning operation is used in learning phase for improving learning efficiency. Several classic engineering cases are selected to evaluate the performance of the proposed algorithm. Results reveal that the proposed algorithm outperforms TLBO and some other promising approachs.
引用
收藏
页码:2714 / 2717
页数:4
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