东北大学学报（自然科学版）

东北大学学报(自然科学版) ›› 2004, Vol. 25 ›› Issue (7): 689-691.DOI: -

• 论著 • 上一篇    下一篇

离散变量结构优化设计的复合形遗传算法

朱朝艳;刘斌;郭鹏飞   

  1. 东北大学资源与土木工程学院;东北大学资源与土木工程学院;辽宁工学院土木建筑系 辽宁沈阳　110004
  • 收稿日期:2013-06-24 修回日期:2013-06-24 出版日期:2004-07-15 发布日期:2013-06-24
  • 通讯作者: Zhu, C.-Y.
  • 作者简介:-
  • 基金资助:
    辽宁省高等学校科研项目(990821107)·

Genetic algorithm in compound form for structural optimization with discrete variables

Zhu, Chao-Yan (1); Liu, Bin (1); Zhang, Yan-Nian (1); Guo, Peng-Fei (2)   

  1. (1) Sch. of Resources and Civil Eng., Northeastern Univ., Shenyang 110004, China; (2) Dept. of Civil Eng., Liaoning Inst. of Technol., Jinzhou 121001, China
  • Received:2013-06-24 Revised:2013-06-24 Online:2004-07-15 Published:2013-06-24
  • Contact: Zhu, C.-Y.
  • About author:-
  • Supported by:
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摘要： 对离散复合形法提出了一种新的初始点产生办法,并基于满应力思想,对离散复合形法的优化结果进行进一步搜索,提高了离散复合形法的局部寻优能力·为了弥补遗传算法自身的不足,把改进的复合形算法作为复合形算子嵌入到遗传算法中,以提高遗传算法的局部寻优能力;同时对遗传操作过程做了改进,如在进化初期采用大的交叉率,以尽快筛选出最优个体;对最差个体采用大的变异率,使其向最优解逼近,从而建立了一种离散变量结构优化设计的混合遗传算法·算例表明这种混合遗传算法优于基本遗传算法和改进的复合形法,是可行和有效的·

关键词: 离散变量, 结构优化, 离散复合形法, 满应力, 遗传算法, 混合遗传算法

Abstract: An approach for the generation of initial point is proposed for discrete compound form. In view of the theory of imitative full-stress, the optimization results of discrete compound form are searched further, so as to improve fully the local searching capability of discrete compound form. A compound form operator is imbedded in genetic algorithm so as to improve the local searching capability of genetic algorithm to make up for the shortage of genetic algorithm. The operation of standard genetic algorithm is also improved, e.g., a high cross rate is taken in the early stage of evolution to pick out the best individual as fast as possible with a high mutation rate taken for the worst individual to approach to optimal solution. A hybrid genetic algorithm is set up for structural optimization with discrete variables. The results by exemplification show that the hybrid genetic algorithm, as an efficient optimal method having the advantages of both standard genetic algorithm and improved compound form approach without their disadvantages, is superior to either one.

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