Minimizing average job completion time in a two-stage assembly flowshop with setup times
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CitationAllahverdi, A. ve Al-Anzi, F. S. (2009). Minimizing average job completion time in a two-stage assembly flowshop with setup times. Maltepe Üniversitesi. s. 80.
The two-stage assembly flowshop problem consist of two stages where there are m machines at the first stage while there is only a single assembly machine at the second stage. There are n jobs to be scheduled and each job has m + 1 operations. For each job, the first m operations are conducted at the first stage by m machines in parallel and a final operation in the second stage by the assembly machine. The last operation at the second stage may start only after all m operations at the first stage are completed. The two-stage assembly scheduling problem has many applications in industry, and hence, has received an increasing attention of researchers recently. We address the two-stage assembly scheduling problem with the objective of minimizing average job completion time. This objective is particularly important in real life situations where reducing inventory or holding cost is of primary concern. Setup times are treated as separate from processing times. This problem is NP-hard since its special case, when setup times are ignored and m = 1 (which is a regular two-machine flowshop problem), is NP-hard. Therefore, we present a dominance relation and present three heuristics. The heuristics are evaluated based on randomly generated data. One of the proposed heuristics is known to be the best heuristic for the case of zero setup times while another heuristic is know to perform well for such problems. A new version of the latter heuristic is proposed and shown to perform much better than the other two heuristics.
SourceInternational Conference of Mathematical Sciences
- Makale Koleksiyonu 
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