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Particle Swarm Assisted Genetic Algorithm for the Optimal Design of Flexbeam Sections
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  • Particle Swarm Assisted Genetic Algorithm for the Optimal Design of Flexbeam Sections
  • Particle Swarm Assisted Genetic Algorithm for the Optimal Design of Flexbeam Sections
저자명
Dhadwal. Manoj Kumar,Lim. Kyu Baek,Jung. Sung Nam,Kim. Tae Joo
간행물명
International journal of aeronautical and space sciences
권/호정보
2013년|14권 4호|pp.341-349 (9 pages)
발행정보
한국항공우주학회
파일정보
정기간행물|ENG|
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이 논문은 한국과학기술정보연구원과 논문 연계를 통해 무료로 제공되는 원문입니다.
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기타언어초록

This paper considers the optimum design of flexbeam cross-sections for a full-scale bearingless helicopter rotor, using an efficient hybrid optimization algorithm based on particle swarm optimization, and an improved genetic algorithm, with an effective constraint handling scheme for constrained nonlinear optimization. The basic operators of the genetic algorithm, of crossover and mutation, are revisited, and a new rank-based multi-parent crossover operator is utilized. The rank-based crossover operator simultaneously enhances both the local, and the global exploration. The benchmark results demonstrate remarkable improvements, in terms of efficiency and robustness, as compared to other state-of-the-art algorithms. The developed algorithm is adopted for two baseline flexbeam section designs, and optimum cross-section configurations are obtained with less function evaluations, and less computation time.