摘要
针对NSGA-Ⅱ算法种群收敛分布不均匀,全局搜索能力差,易陷入局部最优等不足,引入正交交叉策略与混合变异算子,提出一种改进的NSGA-Ⅱ算法。在测试函数上对改进NSGA-Ⅱ算法与传统NSGA-Ⅱ算法同时进行性能测试,结果表明改进的NSGA-Ⅱ算法无论是在收敛性还是多样性上均优于NSGA-Ⅱ算法。将改进算法与传统NSGA-Ⅱ算法同时应用于6061铝合金精密车削加工参数多目标优化设计中,研究结果表明改进NSGA-Ⅱ算法收敛精度更高,收敛速度更快,优化结果更加逼近全局最优解,在求解切削加工参数多目标优化问题时更加有效。
As some deficiencies such as uneven distribution of convergence in population, poor global searching ability,easily to run into partial optimization appeared in classic non-dominated sorting genetic algorithm Ⅱ(NSGA-Ⅱ), this paper proposes an improves algorithm by introducing orthogonal crossover strategy and hybrid mutation operator into the NSGA-Ⅱ. The experiments on a series of test functions show that the improved NSGA-Ⅱ has better performance than NSGA-Ⅱ both in convergence and diversity. The research about optimization of processing parameters of 6061 aluminum alloy in precision turning based on improved algorithm and classic NSGA-Ⅱ, reveal that the improved algorithm has better convergence rate and accuracy than the classic NSGA-Ⅱ, which means the improved algorithm is more effective in solving the multi-objective optimization problems of machining parameters.
出处
《计算机工程与应用》
CSCD
北大核心
2017年第13期227-234,共8页
Computer Engineering and Applications
基金
科技部国家火炬计划(No.2012GH040610)
南京农业大学教改项目(No.2015G01)
关键词
多目标优化
加工参数
NSGA-Ⅱ算法
改进算法
multi-objective optimization
processing parameters
NSGA-Ⅱ algorithm
improved algorithm
