关键词: 多目标优化, 加工参数, NSGA-II算法, 改进算法

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