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Optimal semi-online algorithms for preemptive scheduling problems with inexact partial information

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Abstract

In semi-online scheduling problems, we always assume that some partial additional information is exactly known in advance. This may not be true in some application. This paper considers semi-online problems on identical machines with inexact partial information. Three problems are considered, where we know in advance that the optimal value, or the largest job size are in given intervals, respectively, while their exact values are unknown. We give both lower bounds of the problems and competitive ratios of algorithms as functions of a so-called disturbance parameter r ∈[1, ∞). We establish for which r the inexact partial information is useful to improve the performance of a semi-online algorithm with respect to its pure online problem. Optimal preemptive semi-online algorithms are then obtained.

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Authors and Affiliations

  1. Faculty of Science, Key Laboratory of Advanced Textile Materials and Manufacturing Technology, Zhejiang Sci-Tech University, Hangzhou, 310018, People’s Republic of China

    Yiwei Jiang

  2. Department of Mathematics, Zhejiang University, Hangzhou, 310027, People’s Republic of China

    Yong He

Authors
  1. Yiwei Jiang
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  2. Yong He
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Correspondence to Yiwei Jiang.

Additional information

Research supported by Natural Science Foundation of China (10671177) and Natural Science Foundation of Zhejiang Province (Y605316) and its preliminary version appeared in proceedings of ISAAC’05.

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Jiang, Y., He, Y. Optimal semi-online algorithms for preemptive scheduling problems with inexact partial information. Acta Informatica 44, 571–590 (2007). https://doi.org/10.1007/s00236-007-0058-8

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  • DOI: https://doi.org/10.1007/s00236-007-0058-8

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