On the Improvement of Differential Evolution for Global Optimization

被引：0
|
作者：
Zhou, Zhigang [1 ]
机构：
[1] Dezhou Univ, Dept Comp Sci & Technol, Dezhou, Peoples R China
来源：
2010 2ND INTERNATIONAL CONFERENCE ON COMPUTER AND AUTOMATION ENGINEERING (ICCAE 2010), VOL 5 | 2010年
关键词：
differential evolution (DE); evolutionary algorithm; optimization;
D O I：
10.1109/ICCAE.2010.5451222
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Differential Evolution (DE) is a population-based search algorithm, which has shown good search abilities in many optimization problems. In this paper, we propose a novel DE algorithm, called IDE, to improve the performance of DE. In order to verify the performance of the proposed approach, we test IDE on eight well-known benchmark problems. The comparison results among IDE and two other improved versions of DE show that IDE outperforms them on majority of test problems.
引用
收藏
页码：390 / 393
页数：4
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