SAPFOCS：成组技术中零件族形成问题的元启发式方法
SAPFOCS: a metaheuristic based approach to part family formation problems in group technology
摘要：
本文讨论了在成组技术（GT）中被认为是在多项式时间内解决的中等复杂的零件族形成问题。在过去的文献研究人员调查，零件族形成技术主要是基于生产流程分析（PFA），通常考虑操作要求，顺序和时间。零件编码分析（PCA）被认为是识别零件族的有效方法。PCA通过基于它们在以下方面的相似性将它们分配到不同的族来对部件进行分类：（1）设计特征，例如形状和尺寸，和/或（2）制造特征（加工要求）。一种新的方法，即SAPFOCS模拟退火的基础上，在这项研究中采用开发有效的部分家庭利用PCA技术。其后田口的正交设计方法来解决的关键问题上的参数选择的建议元启发式算法。因此，在大小为5 { \times } 9至27 { \times } 9的5个不同数据集上测试所采用的技术，并将所获得的结果与C-连锁聚类技术进行比较。实验结果表明，所提出的元启发式算法是非常有效的，在获得的解决方案的质量，并在大多数情况下优于C-联动算法。
英文摘要：
This article deals with Part family formation problem which is believed to be moderately complicated to be solved in polynomial time in the vicinity of Group Technology (GT). In the past literature researchers investigated that the part family formation techniques are principally based on production flow analysis (PFA) which usually considers operational requirements, sequences and time. Part Coding Analysis (PCA) is merely considered in GT which is believed to be the proficient method to identify the part families. PCA classifies parts by allotting them to different families based on their resemblances in: (1) design characteristics such as shape and size, and/or (2) manufacturing characteristics (machining requirements). A novel approach based on simulated annealing namely SAPFOCS is adopted in this study to develop effective part families exploiting the PCA technique. Thereafter Taguchi's orthogonal design method is employed to solve the critical issues on the subject of parameters selection for the proposed metaheuristic algorithm. The adopted technique is therefore tested on 5 different datasets of size 5 {\times} 9 to 27 {\times} 9 and the obtained results are compared with C-Linkage clustering technique. The experimental results reported that the proposed metaheuristic algorithm is extremely effective in terms of the quality of the solution obtained and has outperformed C-Linkage algorithm in most instances.
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