摘要
分析了常用遗传算法选择算子的不足,发现没有能够有效避免局部最优解产生的选择算子。针对这一问题提出了改进的选择算子——自适应选择方法。利用改进的自适应选择遗传算法对船用柴油机关键件铣削参数进行了优化,建立了优化过程的数学模型,并通过计算机语言编程实现。分别采用4种选择算子对铣削参数进行优化。对优化结果进行对比分析,所提出的自适应选择算子的计算精确性和有效避免局部最优解的能力表明,该优化方法是科学有效的。
Some deficiencies were found in the commonly used selection operator of genetic algorithm. Actually, there wasn＇t one selection operator that can avoid the local optimum solution efficiently. Thus, a new improved selec- tion operator named adaptive selection was proposed. This new means was used to optimize the milling parameters of diesel engine parts. During the optimization, a mathematical model was built and the account was realized through the computer language. Four kinds of selection operators were used in the optimization. The comparative analysis proved the accuracy of the genetic algorithm based on the adaptive selection and the ability of avoiding the local optimum so- lution. It＇ s true that the method is scientific and effective.
出处
《机电一体化》
2014年第6期31-35,共5页
Mechatronics
关键词
选择算子
切削参数
遗传算法
selection operator cutting parameter genetic algorithm
