首页 | 本学科首页   官方微博 | 高级检索  
     

基于概率模型的混合多目标算法
引用本文:刘洋,肖宝秋,戴光明. 基于概率模型的混合多目标算法[J]. 计算机应用, 2011, 31(9): 2555-2558. DOI: 10.3724/SP.J.1087.2011.02555
作者姓名:刘洋  肖宝秋  戴光明
作者单位:中国地质大学(武汉) 计算机学院,武汉 430074
基金项目:国家自然科学基金资助项目(60873107)
摘    要:对传统多目标算法NSGA-Ⅱ及模型多目标算法RM-MEDA进行了分析,并指出了二者的不足。在此基础上,提出基于概率模型的混合多目标算法,并设计了相应的建模准则用于实现两种算法的结合,使得提出的算法能够充分发挥两种算法的优势。将提出的算法与NSGA-Ⅱ算法和RM-MEDA算法在10个测试函数进行了实验对比,结果证实了算法在全局收敛性及多样性等方面有着较好的效果。

关 键 词:NSGA-Ⅱ算法  RM-MEDA算法  概率模型  建模准则  
收稿时间:2011-03-07
修稿时间:2011-04-18

Hybrid multi-objective algorithm based on probabilistic model
LIU Yang,XIAO Bao-qiu,DAI Guang-ming. Hybrid multi-objective algorithm based on probabilistic model[J]. Journal of Computer Applications, 2011, 31(9): 2555-2558. DOI: 10.3724/SP.J.1087.2011.02555
Authors:LIU Yang  XIAO Bao-qiu  DAI Guang-ming
Affiliation:School of Computer, China University of Geosiences, Hubei Wuhan 430074, China
Abstract:The traditional multi-objective algorithm named NSGA-Ⅱ and the multi-objective algorithm based model named RM-MEDA were analyzed. Meanwhile, the deficiencies of these two algorithms were pointed out. On the basis of that, a hybrid multi-objective algorithm based on probabilistic model was proposed and the corresponding model metric for mixing the two algorithms was designed. The proposed algorithm could take advantage of the mentioned two algorithms. The algorithm was contrasted with NSGA-Ⅱ and RM-MEDA on 10 test functions. The experimental results show that the proposed algorithm has a good performance on global convergence and diversity.
Keywords:NSGA-Ⅱ algorithm   RM-MEDA algorithm   probabilistic model   model metric
本文献已被 CNKI 等数据库收录!
点击此处可从《计算机应用》浏览原始摘要信息
点击此处可从《计算机应用》下载全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号