Abstract
We consider batch processing jobs to minimize the mean completion time. A batch processing machine can handle up to B jobs simultaneously. Each job is represented by an arrival time and a processing time. Jobs processed in a batch have the same completion time, i.e., their common starting time plus the processing time of their longest job. For batch processing, non-preemptive scheduling is usually required and we discuss this case. The batch processing problem reduces to the ordinary uniprocessor system scheduling problem if B=1. We focus on the other extreme case B=+\infty. Even for this seemingly simple extreme case, we are able to show that the problem is NP-hard for the weighted version. In addition, we establish a polynomial time algorithm for a special case when there are only a constant number of job processing times. Finally, we give a polynomial time approximation scheme for the general case. © 2003 Springer-Verlag New York Inc.
| Original language | English |
|---|---|
| Pages (from-to) | 513-528 |
| Journal | Algorithmica (New York) |
| Volume | 38 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - Jan 2004 |
Bibliographical note
Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].Research Keywords
- Batch processing
- Mean completion time
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