Data-Driven Optimal Scheduling Algorithm of Human Resources in Colleges and Universities
At present, the development process of human resource management in Colleges and universities in China has gone through a period of time. In the whole process, the mode of human resource management in colleges and universities is gradually maturing, but there are also some problems. In this paper, d...
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| Vydáno v: | Scientific programming Ročník 2022; s. 1 - 10 |
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| Hlavní autor: | |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
New York
Hindawi
22.03.2022
John Wiley & Sons, Inc |
| Témata: | |
| ISSN: | 1058-9244, 1875-919X |
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| Abstract | At present, the development process of human resource management in Colleges and universities in China has gone through a period of time. In the whole process, the mode of human resource management in colleges and universities is gradually maturing, but there are also some problems. In this paper, data-driven stochastic optimal scheduling algorithm and robust optimal scheduling algorithm are used to model and analyze the human resources. Then, the two models are applied to the human resource management of Nanjing University and Southeast University. The data optimization results show that the robust optimal scheduling algorithm is helpful to the management of new teachers, while the random optimal scheduling algorithm can improve the management of teachers who have been in service for a long time, but there are still some disadvantages. If the combination of two data-driven scheduling algorithms is adopted, it can manage the human resources of colleges and universities well. In short, this paper provides some theoretical and experimental support for the specific application of data-driven human resources optimal scheduling algorithm in colleges and universities. |
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| AbstractList | At present, the development process of human resource management in Colleges and universities in China has gone through a period of time. In the whole process, the mode of human resource management in colleges and universities is gradually maturing, but there are also some problems. In this paper, data-driven stochastic optimal scheduling algorithm and robust optimal scheduling algorithm are used to model and analyze the human resources. Then, the two models are applied to the human resource management of Nanjing University and Southeast University. The data optimization results show that the robust optimal scheduling algorithm is helpful to the management of new teachers, while the random optimal scheduling algorithm can improve the management of teachers who have been in service for a long time, but there are still some disadvantages. If the combination of two data-driven scheduling algorithms is adopted, it can manage the human resources of colleges and universities well. In short, this paper provides some theoretical and experimental support for the specific application of data-driven human resources optimal scheduling algorithm in colleges and universities. |
| Author | Liu, Cong |
| Author_xml | – sequence: 1 givenname: Cong orcidid: 0000-0001-6562-8075 surname: Liu fullname: Liu, Cong organization: Department of Business AdministrationWeifang University of Science and TechnologyShandong 262700Chinawfust.edu.cn |
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| Cites_doi | 10.1007/s42835-020-00594-4 10.1109/TSG.2018.2792322 10.1007/s00521-021-06415-7 10.1109/jas.2021.1004174 10.17265/2159-5836/2019.12.013 10.1109/tste.2019.2915049 10.1016/j.compchemeng.2017.12.002 10.1109/tpds.2020.2992073 10.1016/j.ijepes.2019.105393 10.1109/TPWRS.2017.2699121 10.1016/j.scs.2021.102945 10.1016/j.sysarc.2021.102050 10.1109/tpwrs.2019.2893296 10.1016/j.jprocont.2020.09.004 10.1109/TSTE.2018.2847419 10.1049/iet-gtd.2018.5239 10.1016/j.jlp.2020.104148 10.1109/TPWRS.2018.2881359 10.1002/aic.15792 10.1016/j.compchemeng.2017.12.015 10.1016/j.compchemeng.2019.03.034 |
| ContentType | Journal Article |
| Copyright | Copyright © 2022 Cong Liu. Copyright © 2022 Cong Liu. This is an open access article distributed under the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. https://creativecommons.org/licenses/by/4.0 |
| Copyright_xml | – notice: Copyright © 2022 Cong Liu. – notice: Copyright © 2022 Cong Liu. This is an open access article distributed under the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. https://creativecommons.org/licenses/by/4.0 |
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| SubjectTerms | Algorithms Colleges & universities Decision making Feedback Fuzzy sets Human resource management Learning Methods Optimization Performance appraisal Probability distribution Problem solving Random variables Resource scheduling Robustness Scheduling Teachers Teaching |
| Title | Data-Driven Optimal Scheduling Algorithm of Human Resources in Colleges and Universities |
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