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基于遗传模拟退火算法的钢桁架结构优化设计
引用本文: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(6).
作者姓名:赵艳敏  霍达
作者单位:北京京北职业技术学院;北京工业大学建筑工程学院;
基金项目:国家自然科学基金资助项目(50378007)
摘    要:将遗传算法(GA)的全局寻优性能好和模拟退火算法(SA)的局部搜索能力强的优点相结合,提出了用于钢桁架结构离散变量优化设计的遗传模拟退火算法(SAGA).以十杆桁架为例对此算法进行了数值实验,并将实验结果与其他优化方法相比较.算例结果表明,遗传模拟退火算法的寻优概率是100%,平均进化代数为35代,其稳定性和求解效率均高于改进的遗传算法.实验结果显示,遗传模拟退火算法在整体搜索同时,采用退火操作进行局部搜索,提高了算法的局部搜索能力,有效克服了遗传算法迭代缓慢的缺点,把遗传模拟退火算法用于钢桁架离散变量的优化设计中是行之有效的.

关 键 词:遗传算法  模拟退火算法  优化设计  

Optimal Design of Steel Truss Structure Based on Genetic Simulated Annealing Algorithm
ZHAO Yan-min,HUO Da.Optimal Design of Steel Truss Structure Based on Genetic Simulated Annealing Algorithm[J].Journal of Zhengzhou University: Eng Sci,2011(6).
Authors:ZHAO Yan-min  HUO Da
Affiliation:ZHAO Yan-min1,HUO Da2 (1.Northern Beijing Vocational Education Institute,Beijing 101400,China,2.Faculty of Architectural Engineering,Beijing University of Technology,Beijing 100022,China)
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 evolve...
Keywords:genetic algorithm  simulated annealing algorithm  optimal design  
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