Abstract: 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.

Key words: multi-objective optimization, processing parameters, NSGA-II algorithm, improved algorithm

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。

关键词: 多目标优化, 加工参数, NSGA-II算法, 改进算法