遺伝的アルゴリズムにおける年齢構造の導入とその収束性 Introduction of Age Structure to Genetic Algorithm and Its Convergence

この論文にアクセスする

この論文をさがす

著者

抄録

In this paper, the new genetic algorithm is proposed by introducing the age structure. The genetic algorithm (GA) simulating the process of natural evolutions is an optimization method composed of genetic operators: selection, crossover and mutation. The GA has recently been demonstrated its effectiveness in the scheduling, planning and other optimization issues, but the GA has problems of premature local convergence and the bias by genetic drift, which arise from a loss of diversity in the population of the algorithm. Therefore, first, in this paper, to improve these problems of the GA we propose the genetic algorithm introducing the age structure (ASGA) which is a continuous generation model. Second, the ASGA is applied to the knapsack problem which is one of combinatorial optimization problems and compared with the simple GA (SGA). The results of numerical experiments show the effectiveness of the ASGA better than the SGA. Further, in the ASGA the relation between the lethal age and the rate of crossover is investigated through numerical experiments.

収録刊行物

  • 計測自動制御学会論文集  

    計測自動制御学会論文集 31(5), 560-568, 1995-05-31 

    The Society of Instrument and Control Engineers

参考文献:  22件

参考文献を見るにはログインが必要です。ユーザIDをお持ちでない方は新規登録してください。

被引用文献:  3件

被引用文献を見るにはログインが必要です。ユーザIDをお持ちでない方は新規登録してください。

各種コード

  • NII論文ID(NAID)
    10002484159
  • NII書誌ID(NCID)
    AN00072392
  • 本文言語コード
    JPN
  • 資料種別
    ART
  • ISSN
    04534654
  • NDL 記事登録ID
    3607099
  • NDL 雑誌分類
    ZM11(科学技術--科学技術一般--制御工学)
  • NDL 請求記号
    Z14-482
  • データ提供元
    CJP書誌  CJP引用  NDL  J-STAGE 
ページトップへ