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A Strategy-Selecting Hybrid Optimization Algorithm to Overcome the Problems of the No Free Lunch Theorem
- Kang, Jae-Woo;
- Park, Hyeon-Jeong;
- Ro, Jong-Suk;
- Jung, Hyun-Kyo
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20초록
When a conventional optimization algorithm is applied to diverse problems, the performance is not guaranteed because the optimization algorithm is tuned properly to a specific problem. To address this problem, a novel strategy-selecting hybrid optimization algorithm (SSHOA) is proposed. The proposed algorithm can autonomously and intelligently establish a strategy, which offers a better fitting algorithm according to a varying problem situation. The efficiency, accuracy, and reliability of the SSHOA are verified via mathematical test functions. To confirm electromagnetic performance capabilities, the proposed algorithm is applied to the optimization of an outer rotor permanent magnet machine.
키워드
Design optimization; finite-element analysis; genetic algorithms (GAs); learning artificial intelligence (AI); MOTOR
- 제목
- A Strategy-Selecting Hybrid Optimization Algorithm to Overcome the Problems of the No Free Lunch Theorem
- 저자
- Kang, Jae-Woo; Park, Hyeon-Jeong; Ro, Jong-Suk; Jung, Hyun-Kyo
- 발행일
- 2018-03
- 유형
- Article
- 권
- 54
- 호
- 3
- 출판사
- IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
- 발행국가
- 미국
- ISSN
- E 1941-0069
P 0018-9464