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.
|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 14 → 2013 9 17
|Other||2013 52nd Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2013|
|Period||13/9/14 → 13/9/17|
ASJC Scopus subject areas
- コンピュータ サイエンスの応用