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Asymptotic analysis of online algorithms and improved scheme for the flow shop scheduling problem with release dates

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  • Danyu Bai

Abstract

This paper discusses the flow shop scheduling problem to minimise the total quadratic completion time (TQCT) with release dates in offline and online environments. For this NP-hard problem, the investigation is focused on the performance of two online algorithms based on the Shortest Processing Time among Available jobs rule. Theoretical results indicate the asymptotic optimality of the algorithms as the problem scale is sufficiently large. To further enhance the quality of the original solutions, the improvement scheme is provided for these algorithms. A new lower bound with performance guarantee is provided, and computational experiments show the effectiveness of these heuristics. Moreover, several results of the single-machine TQCT problem with release dates are also obtained for the deduction of the main theorem.

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  • Danyu Bai, 2015. "Asymptotic analysis of online algorithms and improved scheme for the flow shop scheduling problem with release dates," International Journal of Systems Science, Taylor & Francis Journals, vol. 46(11), pages 1994-2005, August.
    • Handle: RePEc:taf:tsysxx:v:46:y:2015:i:11:p:1994-2005
    DOI: 10.1080/00207721.2013.843736
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    Cited by:

    1. Tao Ren & Yan Zhang & Shuenn-Ren Cheng & Chin-Chia Wu & Meng Zhang & Bo-yu Chang & Xin-yue Wang & Peng Zhao, 2020. "Effective Heuristic Algorithms Solving the Jobshop Scheduling Problem with Release Dates," Mathematics, MDPI, vol. 8(8), pages 1-25, July.

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