Orthogonal dynamic hill-climbing algorithm for dynamic optimization problems

被引：0
|
作者：
Zeng, Sanyou [1 ,2 ]
Shi, Hui [1 ]
Chen, Guang
De Garis, Hugo
Kang, Lishan [3 ]
Ding, Lixin [3 ]
机构：
[1] China Univ Geosci, Dept Comp Sci & Technol, Wuhan 430074, Peoples R China
[2] Hunan Univ Technol, Dept Comp Sci, Hunan 412008, Peoples R China
[3] Wuhan Univ, State Key Lab Software Engn, Wuhan 430072, Peoples R China
来源：
2006 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1-6 | 2006年
基金：
中国国家自然科学基金; 中国博士后科学基金;
关键词：
climbing algorithm; dynamic optimization; orthogonal design;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
An orthogonal hill-climbing algorithm for dynamic optimization problems with continuous variables (labeled ODHC is proposed in present paper. The local peak climber is not a solution x, but rather a "niche", a small hyperrectangle. An orthogonal design method is employed on the niches for the niche to climb a potentially peak fast. An archive is used to store the latest found higher peaks for the ODHC algorithm learning from the past search. The randomly creating niches implement the global search. Numerical experiments show that the ODHC algorithm performs a lot better than the SOS (Self Organizing Scouts) algorithm [1].
引用
收藏
页码：1316 / +
页数：3
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