亚洲一区欧美在线,日韩欧美视频免费观看,色戒的三场床戏分别是在几段,欧美日韩国产在线人成

多鄰域結(jié)構(gòu)多目標(biāo)遺傳算法
作者:
作者單位:

作者簡(jiǎn)介:

通訊作者:

中圖分類號(hào):

基金項(xiàng)目:

國(guó)家自然科學(xué)基金資助項(xiàng)目(51275274)


Multi-neighborhood Structure Based Multi-objective Genetic Algorithm
Author:
Affiliation:

Fund Project:

  • 摘要
  • |
  • 圖/表
  • |
  • 訪問統(tǒng)計(jì)
  • |
  • 參考文獻(xiàn)
  • |
  • 相似文獻(xiàn)
  • |
  • 引證文獻(xiàn)
  • |
  • 資源附件
  • |
  • 文章評(píng)論
    摘要:

    為了解決應(yīng)力約束類桁架結(jié)構(gòu)的尺寸優(yōu)化多目標(biāo)問題,提出一種多領(lǐng)域結(jié)構(gòu)的多目標(biāo)遺傳算法應(yīng)用于尺寸優(yōu)化設(shè)計(jì)。利用個(gè)體之間歐氏距離信息,將種群劃分為多個(gè)領(lǐng)域以形成多個(gè)小生境種群。該算法為每個(gè)個(gè)體提供一定數(shù)量的鄰居個(gè)體,并規(guī)定只能同鄰居個(gè)體進(jìn)行交叉變異操作,通過實(shí)驗(yàn)分析了不同鄰居規(guī)模對(duì)算法性能的影響。將新算法與其他經(jīng)典算法在18個(gè)標(biāo)準(zhǔn)測(cè)試函數(shù)上進(jìn)行了仿真分析,結(jié)果表明,所得到的Pareto前端分布更加均勻且更加逼近真實(shí)Pareto前端,具有良好的收斂性和多樣性。將該算法應(yīng)用于經(jīng)典的25桿空間桁架結(jié)構(gòu)優(yōu)化的求解,獲得Pareto前端更均勻,收斂性更好,相對(duì)于其他的優(yōu)化算法具有更好的優(yōu)化效果。該算法在程序設(shè)計(jì)、求解空間及其方法通用性等方面表現(xiàn)出良好的性能,并且簡(jiǎn)單、實(shí)用,更加適合于工程實(shí)際應(yīng)用。

    Abstract:

    In order to solve the problem of multi-objective size optimization of truss structures with stress constraints, a multi-objective optimization algorithm with multi-neighborhood was proposed. Based on the Euclidean distance between individuals, the population was divided into multi-neighborhood to form several niche populations. A number of individuals were assigned to each cell as neighborhood by the proposed algorithm. The individuals were only allowed interacting with each other within its neighborhood and generating offspring. The influence of different sizes of neighbors on the performance was analyzed through simulation experiments. The test results on 18 benchmarks revealed that the proposed algorithm outperformed some state-of-the-art algorithm in terms of covered area and diversity, which showed good uniformity and diversity. The obtained Pareto front showed good uniformity and diversity when solving the classic multi-objective optimization problem of 25-bar truss structure. The algorithm showed good performance in program design, solution space and generality and so on, which was very simple, practical and suitable for engineering practice.

    參考文獻(xiàn)
    相似文獻(xiàn)
    引證文獻(xiàn)
引用本文

朱大林,詹騰,張屹,鄭小東,張燈皇,余竹瑪.多鄰域結(jié)構(gòu)多目標(biāo)遺傳算法[J].農(nóng)業(yè)機(jī)械學(xué)報(bào),2015,46(4):309-315,324. Zhu Dalin, Zhan Teng, Zhang Yi, Zheng Xiaodong, Zhang Denghuang, Yu Zhuma. Multi-neighborhood Structure Based Multi-objective Genetic Algorithm[J]. Transactions of the Chinese Society for Agricultural Machinery,2015,46(4):309-315,324.

復(fù)制
分享
文章指標(biāo)
  • 點(diǎn)擊次數(shù):
  • 下載次數(shù):
  • HTML閱讀次數(shù):
  • 引用次數(shù):
歷史
  • 收稿日期:2014-06-18
  • 最后修改日期:
  • 錄用日期:
  • 在線發(fā)布日期: 2015-04-10
  • 出版日期: 2015-04-10
文章二維碼