Searching optimal resequencing and feature assignment on an automated assembly line
Searching optimal resequencing and feature assignment on an automated assembly line
复制标题
在自动化装配线上搜索最佳重新排序和特征分配
DOI：
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发表时间：
2005
期刊：
影响因子：
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通讯作者：
Zhou Xu
中科院分区：
文献类型：
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作者：
A. Lim;Zhou Xu
重新排序和特征分配问题（RFAP）出现在装配线的作业中，尤其是在汽车行业。装配线上的每个作业都必须从其可行的特征集中分配一个特征。然而，在具有不同特征的两个连续作业之间会产生转换成本。为了最小化总转换成本，需要重新安排作业顺序，但重新安排仅限于离线缓冲区的数量。事实证明，RFAP 在强意义上是困难的。基于波束搜索启发式生成最佳解决方案的上限，我们提出了一种迭代搜索方案，对于与实际大小一样大的情况，可以在相当短的时间内获得最佳解决方案。大量的实验表明我们的方法在解决方案质量和时间效率方面都取得了非常有利的结果。
The resequencing and feature assignment problem (RFAP) appears among jobs in the assembly line, especially in the automotive industry. Each job in the assembly line must be assigned a feature from its feasible feature set. However, a changeover cost is incurred between two consecutive jobs with different features. To minimize the total changeover cost, the job sequence needs to be rearranged, but the rearrangement is restricted to the number of offline buffers. The RFAP turns out to be ??-hard in the strong sense. Based on a beam search heuristic to generate upper bounds of optimum solutions, we have proposed an iterative search scheme which can achieve optimum solutions in a reasonably short time, for cases sized as large as that in reality. Extensive experiments have shown very favourable results for our methods in terms of both the solution quality and the time efficiency.