基于遗传算法的车削用量优化研究

为合理地选择切削用量，建立了基于遗传算法的切削用量优化系统框架结构，系统地研究了遗传算法及其相关内容。在约束、单优化目标函数数学建模的基础上，采用线性加权法建立的多目标优化函数；采用罚函数法改进目标函数，使约束直接表示在目标函数中，简化了切削用量的寻优过程。最后，应用遗传算法开发了一个车削用量优化器，对多约束条件下的切削用量优化结果进行了分析，总结了寻优过程中约束条件影响切削用量优化结果的规律。

Cutting parameters optimization in turning based on genetic algorithm

In order to select optimum cutting parameters,an optimization framework of cutting parameters based on Genetic Algorithm(GA) was constructed.Issues relevant to GA were also discussed in detail.Based on the mathematic models of constraints and single-objective functions,multi objective function was built by using the method of linear weighting addition.The constraints were expressed in objective function by formulating them as penalty functions so that the seeking process was simplified and sped up.An optimizer of cutting parameters based on GA was developed to optimize the cutting parameters and utilized to analyze the effects of constraints on the optimization results of cutting parameters in turning.Finally,constraints effects on optimization results of cutting parameters were concluded.