Abstract: The problem of machining path optimization is a special Traveling Salesman Problem（TSP），to solve this problem，the machining paths are sorted into a series of machining elements such as point，line segment，curve and close curve，and an approach for it’s optimization based on variable-length genome genetic algorithm is presented.In this algorithm，each machining element is represented by some points which are encoded into a combination of an index and its attribute，and some kinds of lines can be cut and spliced by the crossover and mutation operation，thus the machining paths can be further optimized.Simulation results show that this approach is effective for the problem of machining paths optimization，it can dramatically shorten machining paths.

Key words: machining path optimization, variable-length genome, Genetic Algorithm（GA）, Traveling Salesman Problem（TSP）, NC machining

摘要： 加工路径优化问题属于一类特殊的旅行商问题（TSP），针对此问题将加工路径细分为点、线段、曲线段及闭合曲线等加工要素，并提出一种基于变长度染色体遗传算法的优化方法。该方法将每个点编码为一个二元组用以表示各种加工要素，其交叉和变异操作能对一些线进行分割和合并，使加工路径能得到更大程度的优化。仿真结果表明，该方法具有良好的优化效果，可以显著地缩短辅助运动路径的长度。

关键词: 加工路径优化, 变长度染色体, 遗传算法, 旅行商问题, 数控加工