UM
Brick-up metaheuristic Algorithms
Song Q.; Fong S.
2016-08-31
Source PublicationProceedings - 2016 5th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2016
Pages583-587
AbstractMetaheuristic algorithms have been a very important topic in computer science since the start of evolutionary computing the Genetic Algorithms 1950s. By now these metaheuristic algorithms have become a very large family with successful applications in industry. A challenge which is always pondered on, is finding the suitable metaheuristic algorithm for a certain problem. The choice sometimes may have to be made after trying through many experiments or by the experiences of human experts. As each of the algorithms have their own strengths in solving different kinds of problems, in this paper we propose a framework of metaheuristic brick-up system. The flexibility of brick-up (like Lego) offers users to pick a collection of fundamental functions of metaheuristic algorithms that were known to perform well in the past. In order to verify this brickup concept, in this paper we propose to use the Monte Carlo method with upper confidence bounds applied to a decision tree in selecting appropriate functional pieces. This paper validates the basic concept and discusses the further works.
KeywordAI Brick-up system Metaheuristic algorithms Monte Carlo tree UCT
DOI10.1109/IIAI-AAI.2016.100
URLView the original
Language英語
全文获取链接
引用统计
被引频次[WOS]:1   [WOS记录]     [WOS相关记录]
Document TypeConference paper
专题University of Macau
AffiliationUniversidade de Macau
推荐引用方式
GB/T 7714
Song Q.,Fong S.. Brick-up metaheuristic Algorithms[C],2016:583-587.
个性服务
推荐该条目
保存到收藏夹
查看访问统计
导出为Endnote文件
Google Scholar
中相似的文章 Google Scholar
[Song Q.]的文章
[Fong S.]的文章
Baidu academic
中相似的文章 Baidu academic
[Song Q.]的文章
[Fong S.]的文章
Bing Scholar
中相似的文章 Bing Scholar
[Song Q.]的文章
[Fong S.]的文章
相关权益政策
暂无数据
收藏/分享
所有评论 (0)
暂无评论
 

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。