Abstract: To solve the measuring sequence planning problem of contact point,the equivalent Traveling Salesman Problem (TSP) model was built,and the firefly algorithm was used to solve this model.The discrete operation for Firefly Algorithm (FA) was made,and a new distance pattern was created to represent the distance between two fireflies.The iteration and random rules of Discrete Firefly Algorithm (DFA) were improved,and a kind of Improved DFA (IDFA) was obtained.To implement the algorithm,the fitness function including path length,path smoothness and rotate distance of probe was constructed.A leaf-type part was taken as the example to make the contrast test of DFA and IDFA,and the results showed that the proposed algorithm was efficiency and the fitness function was feasible.The contrast experiment on IDFA and Genetic Algorithm (GA) was conducted for measuring planning of another free-form surface,and the results showed that the performance of IDFA was significantly better than GA.

Key words: measuring sequence planning, discrete firefly algorithm, fitness function model, traveling salesman problem

摘要： 为了解决接触式测量序列规划问题,建立了该问题的等效旅行商模型,并利用萤火虫算法对该模型进行求解。对萤火虫算法进行了离散化操作,提出一种新的萤火虫距离表征方法适用于测量序列规划问题,同时对离散萤火虫算法迭代规则和随机搜索方式进行改进,得到一种改进型离散萤火虫算法|建立了综合路径长度、路径光滑度和触头旋转距离三个评价指标的适应度函数,并以叶片型零件为例,进行了离散萤火虫算法和改进型离散萤火虫算法对比实验,验证了改进型离散萤火虫算法的有效性以及适应度函数的合理性|最后以另一自由曲面零件为例,将改进型离散萤火虫算法和遗传算法进行对比,结果表明了改进型离散萤火虫算法的优越性。

关键词: 测量序列规划, 离散萤火虫算法, 适应度函数模型, 旅行商问题