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Critical chains and its randomness study for scheduling optimization

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Abstract

Affected by various uncertain factors, the critical chain is random. The article studies the critical chain and its randomness, and points out that when there is no buffer, the critical chain method and the critical path method have the same identity, and the central limit law of the same distribution can solve the randomness of the critical chain. This conclusion is mainly based on the following research: (1) The paper analyze the technical points of the critical chain, and points out that the setting of the buffer can be replaced by the operation time of the process; (2) The principles and expressions are proposed for determining the critical chain; (3) The influence factors of the randomness of the critical chain are analyzed; (4) The randomness of the random critical chain is determined based on the central limit law of the same distribution.

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Data availability

The data used to support the findings of this study are included within this article. Requests for more details should be made to the corresponding author.

Abbreviations

CPM:

Critical Path Methodology

CCM:

Critical Chain Method

ACTIM:

Activity Time(Heuristic Algorithm)

T:

Total Time

LF:

Late Fnish Date

EF:

Early Fnish Date

LS:

Late Start Date

R:

Resource

P:

Probability

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Acknowledgements

The authors thank the Editor, Associate Editor, and referees for their comments on the initial version of the manuscript.

Funding

This work was supported by the National Natural Science Foundation of China (51478384) and the Industrial Building Environment and Energy Conservation Innovation Team of China (2017KCT-14).

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Contributions

XH and WY conceptualized the main idea of this research project; WY and TL designed and conducted the experiments; WY checked the results; XH wrote the whole paper. All authors have read and agreed to the published version of the manuscript.

Corresponding author

Correspondence to Xiaokang Han.

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Han, X., Yan, W. & Liu, T. Critical chains and its randomness study for scheduling optimization. Int J Syst Assur Eng Manag 13, 844–854 (2022). https://doi.org/10.1007/s13198-021-01345-y

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  • DOI: https://doi.org/10.1007/s13198-021-01345-y

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