Elitist Differential Evolution for solving Numerical Optimization Problems

被引：0
|
作者：
Hsieh, Sheng-Ta [1 ]
Wu, Huang-Lyu [1 ]
Su, Tse [1 ]
机构：
[1] Oriental Inst Technol, Dept Commun Engn, New Taipei, Taiwan
来源：
PROCEEDINGS OF THE EIGHTEENTH INTERNATIONAL SYMPOSIUM ON ARTIFICIAL LIFE AND ROBOTICS (AROB 18TH '13) | 2013年
关键词：
Differential Evolution; elitist; optimization; population; GLOBAL OPTIMIZATION;
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 this paper, an elitist strategy is proposed for enhancing solution searching performance of Differential Evolution (DE). Also, a new variant of mutation for DE is proposed to improved population's exploration and prevent particles form fall into local optimum. In the experiments, 10 hybrid composition functions of CEC 2005 test functions are selected for testing performance of proposed method and compare it with 4 DE variants. From the results, it can be observed that the proposed method exhibits better than related works.
引用
收藏
页码：609 / 612
页数：4
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