电子学报 ›› 2016, Vol. 44 ›› Issue (1): 87-94.DOI: 10.3969/j.issn.0372-2112.2016.01.013

• 学术论文 • 上一篇    下一篇

基于正交设计的元胞多目标遗传算法

张屹, 万兴余, 郑小东, 孙莉莉   

  1. 三峡大学机械与动力学院, 湖北宜昌 443002
  • 收稿日期:2014-04-23 修回日期:2014-07-21 出版日期:2016-01-25
    • 作者简介:
    • 张 屹 男,1976年12月出生,甘肃兰州人,博士、副教授、硕士生导师、国家自然科学基金委机械学科评审专家.分别于2000年、2005年在中国科学技术大学获工学学士学位和工学博士学位;2006年至2008年在中国科学技术大学工程学院力学博士后流动站从事博士后研究,主要研究方向为机电系统现代设计方法、智能计算等.E-mail:jxzhangyi1976@126.com 万兴余 男,1988年12月出生,湖北黄冈人,2012年获三峡大学工学学士学位,现为三峡大学机械电子工程硕士研究生,主要从事多目标优化方面的研究. E-mail:wanxingyuhui@163.com
    • 基金资助:
    • 国家自然科学基金 (No.51275274); 三峡大学研究生科研创新基金 (No.2013CX029)

Cellular Genetic Algorithm for Multiobjective Optimization Based on Orthogonal Design

ZHANG Yi, WAN Xing-yu, ZHENG Xiao-dong, SUN Li-li   

  1. College of Mechanical and Power Engineering, China Three Gorges University, Yichang, Hubei 443002, China
  • Received:2014-04-23 Revised:2014-07-21 Online:2016-01-25 Published:2016-01-25
    • Supported by:
    • National Natural Science Foundation of China (No.51275274); Postgraduate Research Innovation Fund of China Three Gorges University (No.2013CX029)

摘要:

元胞多目标遗传算法在求解两目标优化问题时是比较高效的.但是,初步实验显示其在求解三目标优化问题(例如DTLZ系列)时,表现不是十分令人满意.为了进一步提高算法的性能,引入了正交设计的思想,提出了基于正交设计的多目标元胞遗传算法.在改进算法的迭代过程中,先对父代个体进行分段,之后按照正交表来对这些片段进行重新组合产生多个子代个体,然后从这些子代个体中找出适应度较优的进入下一代种群.实验结果表明,引入正交设计思想能够提高算法性能,与其他优秀算法进行比较的结果说明,改进算法求解三目标问题(DTLZ系列)也是具有竞争力的.

关键词: 多目标, 元胞遗传算法, 正交设计, 函数优化

Abstract:

Multi-objective cellular genetic algorithm has proven to be effective in solving bi-objective MOPs.However, preliminary experiments have revealed that it has difficulties when dealing with three-objective MOPs(the DTLZ problem family).In order to enhance the performance, the orthogonal design idea is introduced and a new cellular genetic algorithm called cellular genetic algorithm for multi-objective optimization based on orthogonal design is proposed.In the progress of iteration of improved algorithm, the parent individuals are divided into many segments, and then several offsprings are produced by recombining the segments according to the orthogonal table, finally, choose the individuals which have better fitness value from the offsprings to the next population.The experiments show that the performance is improved after introducing the orthogonal design.Compared with several state-of-the-art multi-objective metaheuristics, the obtained results show that the improved algorithm is competitive for DTLZ problem family, too.

Key words: multi-objective, cellular genetic algorithm, orthogonal design, function optimization

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