关键词: 离散变量, 结构优化, 改进遗传算法, 混合遗传算法

Abstract:

In the iterative process of the standard genetic algorithm (SGA)，there often appear premature conver-gence,oscillation,over-randomization and low iterative speed.To solve these problems. some improved measures including transgenic operator and one-parent genetic operator are proposed.and a three-equal-partition algorithm (TEPA)fbr the structural optimization with discrete variables is provided.This algorithm is then combined with genetic algorithm(GA)in the process of primal colony forming and colony evolving.Thus,the two algorithms inde-pendently operate,mutually harmonize and jointly play their roles.Moreover,on the basis of practical structure de-signs in engineering,a model of structural optimization with discrete variables is established bv sufficienflv consi.dering the constraint conditions stipulated by the BODTI and the demands f0r various engineering standards. The opti-mized results obtained by different algorithms show that the improved hybrid genetic algorithm is of the advantages of saving time,high efficiency. good local searching ab ility and excellent global convergence property.

Key words: discrete variable, structural optimization, improved genetic algorithm , hybrid genetic algorithm