面向STEP-NC基于混合式遗传算法的工艺路线优化

STEP-NC oriented process planning optimization based on hybrid genetic algorithm

为适应STEP-NC技术的发展需求,解决基于STEP-NC非线性工艺路线优化问题,在深入分析STEP-NC基于加工特征的数据模型基础上,探讨了工艺路线优化中存在的问题及其相关约束,提出采用基于操作优先图的智能搜索与遗传算法相结合的混合式算法。首先考虑加工操作排序中的强制性约束,采用基于操作优先图的智能搜索算法,获取多个可行的加工操作顺序,并将其作为遗传算法的初始化种群;然后综合考虑机床选择、刀具选择和刀具运动方向选择,以加工成本最低为目标函数,根据优化约束条件,通过遗传算法的复制、交叉和变异等操作实现有效工艺路线的优化决策,得到满足车间要求的最优或接近最优的工艺路线。通过实例,验证了该算法在面向STEP-NC加工特征的零件工艺路线优化上的可行性和有效性。

To meet the requirements of STEP-NC technology and to solve the non-linear process planning problem,the existing problems in process planning optimization and its related constraints were discussed on the basis of analyzing STEP-NC data model based on machining features.The hybrid algorithm was proposed by integrating intelligent search of operation precedence graph with genetic algorithm.The compulsive constraints were firstly considered in the sequence of operations,and the alternative operation sequences were acquired by intelligent search algorithm based on operation precedence graph.This algorithm was acted as the initial population for the next genetic algorithm.The selections of machine tool,tool and tool approach direction were all taken into account,by taking the lowest machining cost as optimization objective function,the effective process planning optimization decision was achieved through operation of genetic algorithm＇s copy,cross and variation according to optimization constraints.The optimal or near optimal process route which satified the workshop requirements was obtained.An example was used to demonstrate the feasibility and effectiveness of proposed algorithm in parts process planning optimization oriented to STEP-NC.