Best-Possible Online Algorithms for Single Machine Scheduling to Minimize the Maximum Weighted Completion Time

Xing Chai (), Lingfa Lu, Wenhua Li () and Liqi Zhang ()
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Xing Chai: School of Mathematics and Statistics, Zhengzhou University, Zhengzhou, Henan 450001, P. R. China
Lingfa Lu: School of Mathematics and Statistics, Zhengzhou University, Zhengzhou, Henan 450001, P. R. China
Wenhua Li: School of Mathematics and Statistics, Zhengzhou University, Zhengzhou, Henan 450001, P. R. China
Liqi Zhang: College of Information and Management Science, Henan Agricultural University, Zhengzhou, Henan 450003, P. R. China

Asia-Pacific Journal of Operational Research (APJOR), 2018, vol. 35, issue 06, 1-11

Abstract: In this paper, we consider the online single machine scheduling problem to minimize the maximum weighted completion time of the jobs. For the preemptive problem, we show that the LW (Largest Weight first) rule yields an optimal schedule. For the non-preemptive problem, Li [Li, W (2015). A best possible online algorithm for the parallel-machine scheduling to minimize the maximum weighted completion time. Asia-Pacific Journal of Operational Research, 32(4), 1550030 (10 pages)] presented a lower bound 2, and then provided an online algorithm with a competitive ratio of 3. In this paper, we present two online algorithms with the best-possible competitive ratio of 2 for the non-preemptive problem.

Keywords: Scheduling; online algorithm; best-possible; competitive ratio (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (2)

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DOI: 10.1142/S0217595918500483

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