Designing optimal updating rule for differential evolution using genetic programming

Minoru Kanemasa, Eitaro Aiyoshi

研究成果: Paper査読

抄録

The rapid increase of computer power enabled us to solve many real world problems using optimization algorithms. However, the recent novel metaheuristic algorithms do not stand on concrete ground like traditional algorithms did. Therefore, there should be many rooms to improve those algorithms, and one of the way is to alter the formula of an algorithm. In this study, we define algorithm designing as an optimization problem, and use genetic programming to find new mutation schemes for differential evolution. In addition, we evaluate the generated mutation schemes using several benchmarks to verify that the proposed methods and the generated algorithms are effective ones.

本文言語English
ページ1548-1549
ページ数2
出版ステータスPublished - 2013 1 1
イベント2013 52nd Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2013 - Nagoya, Japan
継続期間: 2013 9 142013 9 17

Other

Other2013 52nd Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2013
国/地域Japan
CityNagoya
Period13/9/1413/9/17

ASJC Scopus subject areas

  • 制御およびシステム工学
  • コンピュータ サイエンスの応用
  • 電子工学および電気工学

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