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Abstract
En 中文
The distributed flow shop scheduling problem (DFSP) has become widespread due to the increasing advantages of multi-factories manufacturing in recent years. The distributed assembly blocking flow shop scheduling problem (DABFSP), which aims at minimizing the maximum assembly completion time, is considered in this paper. A knowledge-driven constructive heuristic (KDH) algorithm is proposed to address the above problem. Three different kinds of neighborhood knowledge are refined by analyzing the characteristic of the problem and quantified to design the KDH algorithm. The jobs belonging to the same production are assigned to the different factories to advance the starting time of assembly, which is quantified as knowledge 1. The assembly sequence of the product is determined according to the processing sequence of the job in the processing factory, which is defined as knowledge 2. The jobs belonging to the same product are distributed together in each processing factory, which is quantified as knowledge 3. The performance of the KDH algorithm is verified on the benchmark instance, which comprises 900 small-scale instances and 810 large-scale instances. The experimental results demonstrate that the KDH algorithm is superior to state-of-the-art algorithms in the aspect of addressing DABFSP.
Keywords:
Distributed assembly blocking flow shop
scheduling problem
Constructive heuristic
Assembly completion time
Knowledge-driven constructive heuristic
algorithm
Journal
IF:
7.5
Papers:
3.0W
Citations:
10.2W
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