摘要
对标准遗传算法进行了有益的改进,使得算法避免了早熟和陷入局部最优·采用混合编码的方法,使算法更适用于工程实际·设计的重组和筛选算子用于初始种群的形成使得初始解分布更加合理,有益于提高算法的计算效率和收敛性,在算法实现中遗传算子的选择采用了适用于二进制编码的单点交叉按位变异和适用于实数编码的算术交叉非均匀变异的混合算子,使得遗传算子能够适用于实数和二进制两种编码方式·并且尝试了将改进的遗传算法用于滑片式压缩机参数的优化,结果表明,经过改进的遗传算法有效可靠,经过优化的压缩机参数合理·
Based on conventional genetic algorithms, a beneficial modification is done in some aspects to enable them to avoid inherent prematurity and getting bogged down in local optimization. Hybrid encoding method is introduced to make the algorithm more practical. Recombination and screening operators used in forming virgin population will make the distribution of initial solutions more reasonably so as to benefit the improvement of computation efficiency and convergence of the algorithm. In the implementation of the algorithm the mixed genetic operators are selected suitable for both binary coding and real value coding. The modified genetic algorithm has been used in parametric optimization of a sliding-vane compressor, by which the result shows that the modified genetic algorithms is reliable and efficient, as proved by the reasonable parameters.
出处
《东北大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2005年第1期73-76,共4页
Journal of Northeastern University(Natural Science)
基金
辽宁省自然科学基金资助项目(20032038)
关键词
遗传算法
优化
混合编码
滑片压缩机
容积效率
genetic algorithms
optimization
hybrid encoding
sliding-vane compressor
volume efficiency
