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Meta-heuristic algorithm-based human resource information management system design and development for industrial revolution 5.0

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Abstract

Nowadays, all enterprises have adopted the means of informatization for enterprise management to adapt to the development of society. With the advent of the information age, enterprise transformation has become an inevitable trend. The management efficiency of enterprises is effectively improved, and the optimal scheduling and efficient management of personnel are realized to design and develop a human resource management (HRM) information system to meet the actual needs of enterprises. By studying the current problems of intelligent enterprise system and HRM information system, based on Java programming language, spring model–view–controller (MVC) web application system is combined with browser/server (B/S) framework, and construction is realized on an intelligent enterprise HRM information system. Aiming at the complexity of enterprise HRM, the meta-heuristic algorithm is adopted to optimize the human resource optimization scheduling module. Through the specific example data, the system implementation and model performance comparison experiments are carried out to further verify the effectiveness of the intelligent enterprise HRM information system proposed here. The results show that the HRM information system based on intelligent enterprise system realizes the effective collection and sorting of data, the running system meets the expected research objectives, and different modules can effectively perform specific functions; the algorithm based on meta-heuristic can realize the reasonable scheduling of personnel, and its model performance is significantly higher than the latest algorithm model. With the continuous increase in the number of events, what is improved is the optimal solution ability of the algorithm. Moreover, it decreases with the increase in the number of iterations, converging around 80 times, and the optimization efficiency reaches 86.35%; the system can find the optimal solution in a shorter time under the same number of iterations. Besides, after the system clustering, the accuracy of employee performance reaches 92%. The intellectualization of enterprise HRM greatly improves the office efficiency.

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References

  • Almeida F, Silva P, Araújo F (2019) Performance analysis and optimization techniques for oracle relational databases. Cybern Inform Technol 19(2):117–132

    Google Scholar 

  • Anwar C, Riyanto J (2019) Perancangan sistem informasi human resources development pada pt semacom integrated. Int J Edu Sci Technol Eng 2(1):19–38

    Article  Google Scholar 

  • Bali AS (2019) An analytical study of applications of human resource information system in modern human resources management. Int J Sustain Agric Manag Inform 5(4):216–229

    Google Scholar 

  • Barišić AF, Poór J, Pejić Bach M (2019) The intensity of human resources information systems usage and organizational performance. Interdiscip Descr Complex Syst: INDECS 17(3-B):586–97

    Article  Google Scholar 

  • Basheer M, Siam M, Awn A, Hassan S (2019) Exploring the role of TQM and supply chain practices for firm supply performance in the presence of information technology capabilities and supply chain technology adoption: a case of textile firms in Pakistan. Uncertain Supply Chain Manag 7(2):275–288

    Article  Google Scholar 

  • Bo H, Han P, Lu B, Zhao C, Wang X (2021) Online monitoring and collaborative scheduling method for wheelset cyber-physical production system: a wheelset manufacturing system case study from a Chinese high-speed train enterprise. Adv Eng Inform 47:101210–101216

    Article  Google Scholar 

  • Bowden JA, Ulmer CZ, Jones CM, Koelmel JP, Yost RA (2018) NIST lipidomics workflow questionnaire: an assessment of community-wide methodologies and perspectives. Metabolomics 14(5):1–11

    Article  Google Scholar 

  • Chaudhary R (2020) Green human resource management and employee green behavior: an empirical analysis. Corp Soc Responsib Environ Manag 27(2):630–641

    Article  Google Scholar 

  • Duan Q, Quynh NV, Abdullah HM, Almalaq A, Do TD, Abdelkader SM, Mohamed MA (2020) Optimal scheduling and management of a smart city within the safe framework. IEEE Access 8:161847–161861

    Article  Google Scholar 

  • Jahannoosh M, Nowdeh SA, Naderipour A, Kamyab H, Davoudkhani IF, Klemeš JJ (2021) New hybrid meta-heuristic algorithm for reliable and cost-effective designing of photovoltaic/wind/fuel cell energy system considering load interruption probability. J Clean Prod 278:123406

    Article  Google Scholar 

  • Jawad WK (2020) Design and implementation of e-human resource manaement system for IT company. Int J Sci Res Eng Develop 3(1):124–131

    Google Scholar 

  • Jean AT, Wang X, Suntu S (2020) Corporate social responsibility in Madagascar: an investigation on Chinese companies. Int J Constr Manag 20(1):29–38

    Google Scholar 

  • Kamaludin K, Kamaludin KZ (2017) User acceptance of the human resource information system: a study of a private hospital in Malaysia. Int Rev Manag Mark 7(2):207–217

    Google Scholar 

  • Kianto A, Sáenz J, Aramburu N (2017) Knowledge-based human resource management practices, intellectual capital and innovation. J Bus Res 81:11–20

    Article  Google Scholar 

  • Li C, Li J, Chen H, Heidari AA (2021) Memetic harris hawks optimization: developments and perspectives on project scheduling and QoS-aware web service composition. Expert Syst Appl 171:114529–114536

    Article  Google Scholar 

  • Liu P, Qingqing W, Liu W (2021) Enterprise human resource management platform based on FPGA and data mining. Microprocess Microsyst 80:103330–110336

    Article  Google Scholar 

  • Ma Z, Wang S, Shen J, Li S, Shi Y (2019) Design of multi-energy joint optimization dispatching system for regional power grids based on B/S architecture. Energy Procedia 158:6236–6241

    Article  Google Scholar 

  • Margatama L (2017) Employee self service-based human resources information system development and implementation. Case Stud: BCP Indones J Inform 11(1):52–60

    Google Scholar 

  • Masum AKM, Beh L-S, Azad MAK, Hoque K (2018) Intelligent human resource information system (i-HRIS): a holistic decision support framework for HR excellence. Int Arab J Inf Technol 15(1):121–130

    Google Scholar 

  • Papa A, Dezi L, Gregori GL, Mueller J, Miglietta N (2018) Improving innovation performance through knowledge acquisition: the moderating role of employee retention and human resource management practices. J Knowl Manag 24(3):212–231

    Google Scholar 

  • Paredes MA, del Pilar Salas-Zárate M, Colomo PR, Gómez-Berbís JM, Valencia-García R (2018) An ontology-based approach with which to assign human resources to software projects. Sci Comput Program 156:90–103

    Article  Google Scholar 

  • Qadir A, Agrawal S (2017) HR transformation through human resource information system: review of literature. J Strateg Human Res Manag 6(1):30–36

    Google Scholar 

  • Samsai T, Praveena S, Kowshika S (2018) A study on demand analysis of farm machineries and equipments in Nilgiris district. Int J Commer Bus Manag 11(1):59–68

    Article  Google Scholar 

  • Shahreki J (2019) The use and effect of human resource information systems on human resource management productivity. J Soft Comput Decis Support Syst 6(5):1–8

    Google Scholar 

  • Shirvani MH (2020) A hybrid meta-heuristic algorithm for scientific workflow scheduling in heterogeneous distributed computing systems. Eng Appl Artif Intell 90:103501–103511

    Article  Google Scholar 

  • Skobelev P, Simonova E, Smirnov S, Budaev D, Voshchuk GY, Morokov A (2019) Development of a knowledge base in the “smart farming” system for agricultural enterprise management. Procedia Comput Sci 150:154–161

    Article  Google Scholar 

  • Tantoh HB, Simatele D (2018) Complexity and uncertainty in water resource governance in Northwest Cameroon: reconnoitring the challenges and potential of community-based water resource management. Land Use Policy 75:237–251

    Article  Google Scholar 

  • Wang T (2020) Intelligent employment rate prediction model based on a neural computing framework and human–computer interaction platform. Neural Comput Applic 32:16413–16426

    Article  Google Scholar 

  • Yang B, Wang J, Zhang X, Yu T, Yao W, Shu H, Zeng F, Sun L (2020) Comprehensive overview of meta-heuristic algorithm applications on PV cell parameter identification. Energy Convers Manage 208:112595–112603

    Article  Google Scholar 

  • Zhao W, Wang L, Zhang Z (2019) Artificial ecosystem-based optimization: a novel nature-inspired meta-heuristic algorithm. Neural Computing and Appl, 1–43

  • Zhu J, Sun Y (2020) Dynamic modeling and chaos control of sustainable integration of informatization and industrialization. Chaos, Solitons Fractals 135:109745–109753

    Article  MathSciNet  Google Scholar 

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Funding

This work was supported by the Natural Science Foundation of China (Grant No. 72002095) and the Jiangsu University Philosophy and Social Science Foundation of China (Grant No. 2020SJA0025) and The Fundamental Research Funds for the Central Universities (Grant No. 30921012203) in China.

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Authors and Affiliations

  1. School of Economics & Management, Nanjing University of Science and Technology, Nanjing, 210094, Jiangsu, China

    Sixuan Chen

  2. Jiangsu Institute of Talent Development Strategy, Nanjing, 210094, Jiangsu, China

    Sixuan Chen

  3. School of Marketing and Logistics Management, Nanjing University of Finance and Economic, Nanjing, 210023, Jiangsu, China

    Huan Xu

Authors
  1. Sixuan Chen
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  2. Huan Xu
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Contributions

Sixuan Chen contributed to the writing and proposed the research direction. Huan Xu was involved in the analysis of the experimental data; all correspondence regarding this article.

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Correspondence to Huan Xu.

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The authors declare that there is no conflict of interest with any financial organizations regarding the material reported in this manuscript.

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Communicated by Deepak kumar Jain.

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Chen, S., Xu, H. Meta-heuristic algorithm-based human resource information management system design and development for industrial revolution 5.0. Soft Comput 27, 4093–4105 (2023). https://doi.org/10.1007/s00500-021-06650-z

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