Online scheduling to minimize maximum weighted flow-time on a bounded parallel-batch machine

Xing Chai, Wenhua Li () and Yuejuan Zhu
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Xing Chai: Zhengzhou University
Wenhua Li: Zhengzhou University
Yuejuan Zhu: Zhengzhou University

Annals of Operations Research, 2021, vol. 298, issue 1, No 5, 79-93

Abstract: Abstract An online scheduling problem on a bounded parallel-batch machine to minimize the maximum weighted flow-time is considered in this paper. Jobs arrive over time with the identical processing time. The maximum ratio between the weights of any two jobs is w. The parallel-batch machine can process at most b jobs simultaneously as a batch, and the jobs in a batch have the same starting time and the same completion time. For this problem, a deterministic online algorithm is presented. The algorithm is showed to be the best possible with a competitive ratio of $$\frac{\sqrt{4w+1}+1}{2}$$ 4 w + 1 + 1 2 when $$w\in [1,2]$$ w ∈ [ 1 , 2 ] , and to have a competitive ratio not greater than w when $$w\in (2,+\infty )$$ w ∈ ( 2 , + ∞ ) .

Keywords: Online scheduling; Batching; Maximum weighted flow-time; Competitive ratio (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (3)

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DOI: 10.1007/s10479-019-03352-6

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