A HYBRID OPTIMIZATION METHOD BASED ON DIFFERENTIAL EVOLUTION AND HARMONY SEARCH

被引：2
|
作者：
Gao, X. [1 ]
Wang, X. [1 ]
Ovaska, S. [2 ]
Zenger, K. [1 ]
机构：
[1] Aalto Univ, Sch Elect Engn, Dept Elect Engn & Automat, Otaniementie 17, FI-00076 Aalto, Finland
[2] Aalto Univ, Sch Elect Engn, Dept Elect Engn & Automat, FI-00076 Aalto, Finland
来源：
INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE AND APPLICATIONS | 2014年 / 13卷 / 01期
基金：
芬兰科学院;
关键词：
Diffrerential evolution; harmony search; hybrid optimization methods; unconstrained optimization; constrained optimization; optimal wind generator design;
D O I：
10.1142/S1469026814500011
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The differential evolution (DE) and harmony search (HS) are two well- known nature- inspired computing techniques. Both of them can be applied to effectively cope with nonlinear optimization problems. In this paper, we propose and study a new DE method, DE-HS, by utilizing the fresh individual generation mechanism of the HS. The HS-based approach can enhance the local search capability of the original DE. Optimization of some unconstrained and constrained benchmark problems and a real-world wind generator demonstrate that our DE-HS has an improved convergence property.
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收藏
页数：23
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