距離に依存せずに多様性を制御するＧＡによる高次元関数最適化

• 木村 周平

  理化学研究所 ゲノム科学総合研究センター

• 小長谷 明彦

  理化学研究所 ゲノム科学総合研究センター

書誌事項

タイトル別名

• A Genetic Algorithm with Distance Independent Diversity Control for High Dimensional Function Optimization.
• キョリ ニ イゾン セズ ニ タヨウセイ オ セイギョ スル GA ニ ヨル コウジゲン カンスウ サイテキカ

抄録

For genetic algorithms, it is important to maintain the population diversity. Some genetic algorithms have been proposed, which have an ability to control the diversity. But these algorithms use the distance between two individuals to control the diversity. Therefore, these performances become worse on ill-scaled functions. In this paper, we propose a new genetic algorithm, DIDC(a genetic algorithm with Distance Independent Diversity Control), that does not use a distance to control the population diversity. For controlling the diversity, DIDC uses two GAs that have different natures. For realizing different natures, one GA uses a crossover operator as a search operator, and the other GA uses a mutation operator in DIDC. By applying DIDC to several benchmark problems, we show that DIDC has a good performance on high dimensional, multimodal, non-separable and ill-scaled problems. Finally, we show that the control parameter of DIDC has the same effect on the search with the number of generating children n_c.

収録刊行物

• 人工知能学会論文誌

  人工知能学会論文誌 18 193-202, 2003

  一般社団法人 人工知能学会

キーワード

• genetic algorithm
• real-coded GA
• function optimization
• adaptation

詳細情報

• CRID: 1390282680085905152
• NII論文ID: 10022004464
• NII書誌ID: AA11579226
• DOI: 10.1527/tjsai.18.193
• ISSN: 13468030
• ISSN: 13460714
• NDL書誌ID: 7264339
• Web Site: https://ndlsearch.ndl.go.jp/books/R000000004-I7264339
• Web Site: http://www.jstage.jst.go.jp/article/tjsai/18/4/18_4_193/_pdf
• 本文言語コード: ja
• データソース種別:
  • JaLC
  • NDL
  • Crossref
  • CiNii Articles
• 抄録ライセンスフラグ: 使用不可