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On-line scheduling a batch processing system to minimize total weighted job completion time
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UNSPECIFIED (2004) On-line scheduling a batch processing system to minimize total weighted job completion time. JOURNAL OF COMBINATORIAL OPTIMIZATION, 8 (1). pp. 85-95. ISSN 1382-6905.
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Abstract
Scheduling a batch processing system has been extensively studied in the last decade. A batch processing system is modelled as a machine that can process up to b jobs simultaneously as a batch. The scheduling problem involves assigning all n jobs to batches and determining the batch sequence in such a way that certain objective function of job completion times C-j is minimized. In this paper, we address the scheduling problem under the on-line setting in the sense that we construct our schedule irrevocably as time proceeds and do not know of the existence of any job that may arrive later. Our objective is to minimize the total weighted completion time Sigmaw(j)C(j). We provide a linear time on-line algorithm for the unrestrictive model (i.e.,bgreater than or equal ton) and show that the algorithm is 10/3-competitive. For the restrictive model (i.e., b<n), we first consider the (off-line) problem of finding a maximum independent vertex set in an interval graph with cost constraint (MISCP), which is NP-hard. We give a dual fully polynomial time approximation scheme for MISCP, which leads us to a (4+ε)-competitive on-line algorithm for any ε>0 for the original on-line scheduling problem. These two on-line algorithms are the first deterministic algorithms of constant performance guarantees.
Item Type: | Journal Article | ||||
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Subjects: | Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software Q Science > QA Mathematics |
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Journal or Publication Title: | JOURNAL OF COMBINATORIAL OPTIMIZATION | ||||
Publisher: | KLUWER ACADEMIC PUBL | ||||
ISSN: | 1382-6905 | ||||
Official Date: | March 2004 | ||||
Dates: |
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Volume: | 8 | ||||
Number: | 1 | ||||
Number of Pages: | 11 | ||||
Page Range: | pp. 85-95 | ||||
Publication Status: | Published |
Data sourced from Thomson Reuters' Web of Knowledge
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