Designing optimal updating rule for differential evolution using genetic programming

Minoru Kanemasa, Eitaro Aiyoshi

研究成果: Conference contribution

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.

元の言語English
ホスト出版物のタイトルProceedings of the SICE Annual Conference
ページ1548-1549
ページ数2
出版物ステータスPublished - 2013
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
Japan
Nagoya
期間13/9/1413/9/17

Fingerprint

Genetic programming
Concretes

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Control and Systems Engineering
  • Computer Science Applications

これを引用

Kanemasa, M., & Aiyoshi, E. (2013). Designing optimal updating rule for differential evolution using genetic programming. : Proceedings of the SICE Annual Conference (pp. 1548-1549)

Designing optimal updating rule for differential evolution using genetic programming. / Kanemasa, Minoru; Aiyoshi, Eitaro.

Proceedings of the SICE Annual Conference. 2013. p. 1548-1549.

研究成果: Conference contribution

Kanemasa, M & Aiyoshi, E 2013, Designing optimal updating rule for differential evolution using genetic programming. : Proceedings of the SICE Annual Conference. pp. 1548-1549, 2013 52nd Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2013, Nagoya, Japan, 13/9/14.
Kanemasa M, Aiyoshi E. Designing optimal updating rule for differential evolution using genetic programming. : Proceedings of the SICE Annual Conference. 2013. p. 1548-1549
Kanemasa, Minoru ; Aiyoshi, Eitaro. / Designing optimal updating rule for differential evolution using genetic programming. Proceedings of the SICE Annual Conference. 2013. pp. 1548-1549
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