Dynamical Multi-objective Optimization Using Evolutionary Algorithm for Engineering

被引:0
作者
Wang, Lingling [1 ]
Li, Yuanxiang [1 ]
机构
[1] Wuhan Univ, State Key Lab Software Engn, Wuhan 430072, Peoples R China
来源
ADVANCES IN COMPUTATION AND INTELLIGENCE | 2010年 / 6382卷
关键词
multi-objective optimization; multi-attribute classification; sum weighted; evolutionary algorithm;
D O I
10.1109/ACP.2010.5682555
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper deals with multi-attribute classification problem based on dynamical multi-objective optimization approaches. The matching of attribute is seen as objective of the problem and user preferences are uncertain and changeable. Traditional sum weighted method and simple evolutionary algorithm are employed for experimental study over practical industry product classification problems. A integrate system framework is proposed to realize the dynamical model for multi-objective optimization. The experimental results show that classification performance system can be improved under the dynamical system framework according to user preference.
引用
收藏
页码:304 / 311
页数:8
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