计算机应用 ›› 2011, Vol. 31 ›› Issue (09): 2555-2558.DOI: 10.3724/SP.J.1087.2011.02555

• 典型应用 • 上一篇    下一篇

基于概率模型的混合多目标算法

刘洋,肖宝秋,戴光明   

  1. 中国地质大学(武汉) 计算机学院,武汉 430074
  • 收稿日期:2011-03-07 修回日期:2011-04-18 发布日期:2011-09-01 出版日期:2011-09-01
  • 通讯作者: 刘洋
  • 作者简介:刘洋(1987-),女,黑龙江齐齐哈尔人,硕士研究生,主要研究方向:多目标优化;
    肖宝秋(1988-),男,江西吉安人,硕士研究生,主要研究方向:多目标优化、科学计算可视化;
    戴光明(1964-),男,湖北武汉人,教授,博士生导师,主要研究方向:算法设计与分析、科学计算可视化。
  • 基金资助:
    国家自然科学基金资助项目(60873107)

Hybrid multi-objective algorithm based on probabilistic model

LIU Yang,XIAO Bao-qiu,DAI Guang-ming   

  1. School of Computer, China University of Geosiences, Hubei Wuhan 430074, China
  • Received:2011-03-07 Revised:2011-04-18 Online:2011-09-01 Published:2011-09-01
  • Contact: LIU Yang

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

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.

Key words: NSGA-Ⅱ algorithm, RM-MEDA algorithm, probabilistic model, model metric

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