郑州大学学报（工学版）2011，Vol.32Issue(6)：54-57,4.
基于遗传模拟退火算法的钢桁架结构优化设计
Optimal Design of Steel Truss Structure Based on Genetic Simulated Annealing Algorithm
摘要
Abstract
To combine Genetic Algorithm ( GA) with Simulated Annealing Algorithm ( SA) that the Genetic Simulated Annealing Algorithm ( SAGA ) was proposed . It had the global searching ability of GA together with the local fast converging ability of SA. It was applied to the steel truss structural optimization with discrete variables and this paper provided the comparison between SAGA experiments and other optimal results. The experiments showed that the searching optimization probability of SAGA was 100% and the average evolved generations is 35 , which indicated that SAGA was more stable and had better seeking efficiency than improved GA. The SAGA improved the local searching ability and overcame evolution slowness defect of GA through applying local searching annealing method. The SAGA is an effective method to seek the optimal design of steel trusses with discrete variables.关键词
遗传算法/模拟退火算法/优化设计Key words
genetic algorithm/ simulated annealing algorithm/ optimal design分类
建筑与水利引用本文复制引用
赵艳敏,霍达..基于遗传模拟退火算法的钢桁架结构优化设计[J].郑州大学学报（工学版）,2011,32(6):54-57,4.基金项目
国家自然科学基金资助项目(50378007) （50378007）
