Adaptive pattern search for large-scale optimization

被引：0
作者：
Vincent Gardeux
Mahamed G. H. Omran
Rachid Chelouah
Patrick Siarry
Fred Glover
机构：
[1] EISTI Engineering School,Department of Computer Science
[2] Gulf University for Science & Technology,Department of Computer Science
[3] University of Paris-Est Creteil,LiSSi Laboratory
[4] University of Colorado,Leeds School of Business
来源：
Applied Intelligence | 2017年 / 47卷
关键词：
Pattern search; Scatter search; Optimization; Continuous; High-dimension; Large-scale; Adaptive methods;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
The emergence of high-dimensional data requires the design of new optimization methods. Indeed, conventional optimization methods require improvements, hybridization, or parameter tuning in order to operate in spaces of high dimensions. In this paper, we present a new adaptive variant of a pattern search algorithm to solve global optimization problems exhibiting such a character. The proposed method has no parameters visible to the user and the default settings, determined by almost no a priori experimentation, are highly robust on the tested datasets. The algorithm is evaluated and compared with 11 state-of-the-art methods on 20 benchmark functions of 1000 dimensions from the CEC’2010 competition. The results show that this approach obtains good performances compared to the other methods tested.
引用
收藏
页码：319 / 330
页数：11
相关论文
共 78 条
[1]  
Lee EK(2007)Large-scale optimization-based classification models in medicine and biology Ann Biomed Eng 35 1095-1 1109
[2]  
Larranaga P(2006)Machine learning in bioinformatics Brief Bioinform 7 86-112
[3]  
Levitsky V(2007)Effective transcription factor binding site prediction using a combination of optimization, a genetic algorithm and discriminant analysis to capture distant interactions BMC Bioinform 8 1-20
[4]  
Saeys Y(2007)A review of feature selection techniques in bioinformatics Bioinformatics 23 2507-2517
[5]  
Inza I(2016)Structured feature selection using coordinate descent optimization BMC Bioinform 17 158-11
[6]  
Larrañaga P(2004)Feature selection for splice site prediction: a new method using EDA-based feature ranking BMC Bioinform 5 1-12
[7]  
Ghalwash MF(2008)A review of estimation of distribution algorithms in bioinformatics BioData Mining 1 1-I231
[8]  
Saeys Y(2008)Identifying functional modules in protein-protein interaction networks: an integrated exact approach Bioinformatics 24 I223-292
[9]  
Armananzas R(2007)Multiobjective optimization in bioinformatics and computational biology IEEE/ACM Trans Comput Biol Bioinform 4 279-241
[10]  
Dittrich M(2010)Survey of modeling and optimization strategies to solve high-dimensional design problems with computationally-expensive black-box functions Struct Multidiscip Optim 41 219-45
12345678