密集型多轮廓裁片的刀具空行程路径寻优  

Idle travel optimization of tool path on intensive multi-profile patterns

作　　者：李迅[1] 陈明[1] 

机构地区：[1]哈尔滨工业大学深圳研究生院,广东深圳518055

出　　处：《计算机应用》2014年第1期281-285,共5页journal of Computer Applications

基　　金：国家自然科学基金资助项目(61100088);广东省自然科学基金资助项目(S2011040000145);深圳创新基础研究基金资助项目(JC201105160526A)

摘　　要：服装行业中缩短刀具裁剪空行程对于高效裁剪布料具有重要意义。结合服装裁片排列具有轮廓形状复杂、分布密集的特点,将问题转化成广义旅行商问题。基于最大最小蚁群(MMAS)算法提出了一种新的用于裁片刀具空行程路径寻优的算法——密集多轮廓蚁群算法,该算法包括4步:1)用MMAS算法确定初步裁片顺序;2)由裁片顺序寻找各裁片入刀节点;3)将各裁片的入刀节点再次用MMAS进行顺序优化重组得到初步裁剪路径;4)反复迭代第2)步和第3)步以求得最优路径。实验验证了所提算法的有效性,对比现有的扫描算法以及双信息素蚁群(NACS)算法其结果分别提升了60.15%和22.44%,该算法在刀具空行程优化上具有明显优势。In the garment industry, shortening idle travel of tool path is important to efficiently cut these patterns from a piece of cloth. As these cutting patterns are of complex shapes and distributed intensively, it is not trivial to obtain the optimal cutting tool path via the existing algorithms. Based on MAX-MIN Ant System （ MMAS）, a new algorithm was proposed to optimize the idle travel of tool path. The algorithm consists of four steps： 1） using standard MMAS algorithm to define the pattern order; 2） seek the node as the tool entrance on each pattern; 3） optimize the node sequence with MMAS; 4） repeat the step 2） and 3） to achieve the optimal tool path. The experiments show that the proposed algorithm can effectively generate optimal tool path. Compared with the line-scanning algorithm and Novel Ant Colony System （NACS） algorithm, the result has been improved by 60.15% and 22.44% respectively.

关 键 词：密集型多轮廓裁片 空行程 路径寻优 广义旅行商问题 最大最小蚁群算法 

分 类 号：TP391.7[自动化与计算机技术—计算机应用技术]