Pseudo-hill climbing genetic algorithm (PHGA) for function optimization

研究成果: Conference contribution

10 被引用数 (Scopus)

抄録

In general, one of the shortcomings in GAs as search methods is their lack of local search ability. The main objective of this paper is to combine the ideas of Simplex method with the genetic algorithms (GAs). In order to give a hill-climbing ability to the conventional GAs, like neural networks, we propose a new GA named PHGA Genetic Algorithm (PHGA) for function optimization. Computer simulation results using De Jong's five-function test bed are shown. According to our simulation, all of the results by the proposed PHGA are better than those by the conventional GAs.

本文言語English
ホスト出版物のタイトルProceedings of the International Joint Conference on Neural Networks
出版社Publ by IEEE
ページ713-716
ページ数4
ISBN(印刷版)0780314212, 9780780314214
出版ステータスPublished - 1993 12 1
イベントProceedings of 1993 International Joint Conference on Neural Networks. Part 1 (of 3) - Nagoya, Jpn
継続期間: 1993 10 251993 10 29

出版物シリーズ

名前Proceedings of the International Joint Conference on Neural Networks
1

Other

OtherProceedings of 1993 International Joint Conference on Neural Networks. Part 1 (of 3)
CityNagoya, Jpn
Period93/10/2593/10/29

ASJC Scopus subject areas

  • ソフトウェア
  • 人工知能

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