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基于自适应小生境遗传算法的船型优化
引用本文:张宝吉.基于自适应小生境遗传算法的船型优化[J].计算机工程,2011,37(8):207-209.
作者姓名:张宝吉
作者单位:上海海事大学海洋环境与工程学院,上海,201306
基金项目:上海海事大学校基金资助项目
摘    要:自适应小生境遗传算法能够克服基本小生境遗传算法操作复杂和计算费时的缺陷,同时具有保持种群的稳定性,获取合适的子种群规模,从而更快地获得最优解的特点。为快速获得阻力性能优良的船型,以势流兴波阻力理论Rankine源法为基础,采用自适应小生境遗传算法并结合CAD技术进行船型优化设计。S60船型的优化算例结果表明,采用自适应小生境遗传算法进行船型优化具有可行性。

关 键 词:基本小生境遗传算法  自适应小生境遗传算法  Rankine源法  优化设计

Optimization of Hull Form Based on Adaptive Niche Genetic Algorithm
ZHANG Bao-ji.Optimization of Hull Form Based on Adaptive Niche Genetic Algorithm[J].Computer Engineering,2011,37(8):207-209.
Authors:ZHANG Bao-ji
Affiliation:ZHANG Bao-ji(College of Ocean Environment and Engineering,Shanghai Maritime University,Shanghai 201306,China)
Abstract:The Adaptive Niche Genetic Algorithm(ANGA) can overcome the deficiency of Sample Niche Genetic Algorithm(SNGA) such as complicated operation and time-consuming,maintain stability of the groups,and obtain appropriate scope of the individual,as to get optimal solution best.In order to obtain the hull form with the excellent resistance performance,an optimization design model of hull form is proposed based on the Rankine source method of potential flow theory.The adaptive niche genetic algorithm combined with the CAD technology to solve the problem.The optimization examples for S60 ships are provided,which confirm that the algorithm is reliable.
Keywords:Sample Niche Genetic Algorithm(SNGA)  Adaptive Niche Genetic Algorithm(ANGA)  Rankine source method  optimization design  
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