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作 者:夏露[1] 李朗[1] 王亮[1] Xia Lu Li Lang Wang Liang(School of Astronautics, Northwestern Polytechnical University, Xi'an 710072, China)
出 处:《西北工业大学学报》2016年第5期767-773,共7页Journal of Northwestern Polytechnical University
基 金:国家自然科学基金(11172242)资助
摘 要:为了平衡智能优化算法的全局与局部搜索能力,对布谷鸟算法和寄生算法进行了探讨与分析,将布谷鸟算法中的莱维搜索加入到改进的寄生算法中,在增加收敛速度的同时保证个体多样性,进而发展得到了基于莱维搜索的寄生算法。通过函数测试及气动算例验证了新算法优越的寻优性能。将基于莱维搜索的寄生算法应用于翼型的气动优化设计中,取得了良好的效果,从而表明提出的算法准确有效,具有良好的实用性。In order to balance the global and local search ability of intelligent optimization algorithm,the cuckoo search algorithm and simulated parasitic algorithm is discussed and analyzed. The mechanism of simulated parasitism model and cuckoo search is much alike,so the Levy flight search strategy of cuckoo search is introduced into the former model. So we get a optimization algorithm which is named Levy simulated parasitism algorithm.Function tests and aerodynamics problem prove that improved algorithm has better searching ability. Applying the Levy simulated parasitism algorithm to the airfoil aerodynamic optimization design,we achieve good results,which show that the proposed algorithm is effective and practical.
分 类 号:V211.4[航空宇航科学与技术—航空宇航推进理论与工程]
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