摘要
提出一种离散变量结构优化设计的单向搜索算法并与标准遗传算法结合成混合遗传算法,即发挥了单向搜索算法省时、高效、局部搜索能力强的特点,又发挥了遗传算法全局性好的特点。算例结果表明,该方法能直接计算具有应力约束和截面尺寸约束的离散变量结构优化设计问题,也能处理同时具有稳定约束和位移约束的多工况、多约束、多变量的离散变量结构优化设计问题。这种混合遗传算法优于标准遗传算法和单向搜索算法,是兼二者之长,弃二者之短的高效的理想优化设计方法。
A hybrid genetic algorithm (HGA) composed of the standard genetic algorithm (SGA) and the unidirectional searching algorithm(USA)is proposed, not only taking their advantages of time saving, high efficiency and powerfully local searching capability of unidirectional searching algorithm, but also having the advantages of globally searching capability of genetic algorithm(GA). The results of examples expatiate that this method can be used directly to work out the structural optimum design with discrete variables, which involves the stress constraints and cross-section size constraints, and to deal with the structural discrete optimization with multi-loading, multi-constraints and multi-variables. HGA, which is an efficient optimal method having advantages of both algorithms and eliminating the disadvantages of both, is superior to SGA and USA.
出处
《辽宁工学院学报》
2003年第6期58-61,共4页
Journal of Liaoning Institute of Technology(Natural Science Edition)
关键词
混合遗传算法
建筑结构
单向搜索算法
标准遗传算法
个体适应度
应力约束
截面尺寸约束
global optimum
discrete variables
structure optimization
unidirectional searching algorithm
genetic algorithm
standard genetic algorithm
hybrid genetic algorithm
