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Modelling recruitment training in mathematical human resource planning

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  • A. C. Georgiou
  • N. Tsantas

Abstract

This paper deals with mathematical human resource planning; more specifically, it suggests a new model for a manpower‐planning system. In general, we study a k‐classed hierarchical system where the workforce demand at each time period is satisfied through internal mobility and recruitment. The motivation for this work is based on various European Union incentives, which promote regional or local government assistance programs that could be exploited by firms not only for hiring and training newcomers, but also to improve the skills and knowledge of their existing personnel. In this respect, in our augmented mobility model we establish a new ‘training/standby’ class, which serves as a manpower inventory position for potential recruits. This class, which may very well be internal or external to the system, is incorporated into the framework of a non‐homogeneous Markov chain model. Furthermore, cost objectives are employed using the goal‐programming approach, under different operating assumptions, in order to minimize the operational cost in the presence of system's constraints and regulations. Copyright © 2002 John Wiley & Sons, Ltd.

Suggested Citation

  • A. C. Georgiou & N. Tsantas, 2002. "Modelling recruitment training in mathematical human resource planning," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 18(1), pages 53-74, January.
    • Handle: RePEc:wly:apsmbi:v:18:y:2002:i:1:p:53-74
    DOI: 10.1002/asmb.454
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    Cited by:

    1. Marie Doumic & Beno^it Perthame & Edouard Ribes & Delphine Salort & Nathan Toubiana, 2016. "Toward an integrated workforce planning framework using structured equations," Papers 1607.02349, arXiv.org, revised Dec 2016.
    2. Dimitriou, V.A. & Georgiou, A.C. & Tsantas, N., 2013. "The multivariate non-homogeneous Markov manpower system in a departmental mobility framework," European Journal of Operational Research, Elsevier, vol. 228(1), pages 112-121.
    3. Tim De Feyter & Marie-Anne Guerry & Komarudin, 2017. "Optimizing cost-effectiveness in a stochastic Markov manpower planning system under control by recruitment," Annals of Operations Research, Springer, vol. 253(1), pages 117-131, June.
    4. A Filinkov & M Richmond & R Nicholson & M Alshansky & J Stewien, 2011. "Modelling personnel sustainability: a tool for military force structure analysis," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(8), pages 1485-1497, August.
    5. Tim Feyter, 2007. "Modeling mixed push and pull promotion flows in Manpower Planning," Annals of Operations Research, Springer, vol. 155(1), pages 25-39, November.
    6. Marie Doumic & Benoît Perthame & Edouard Ribes & Delphine Salort & Nathan Toubiana, 2017. "Toward an integrated workforce planning framework using structured equations," Post-Print hal-01343368, HAL.
    7. Marie Doumic & Benoît Perthame & Edouard Ribes & Delphine Salort & Nathan Toubiana, 2016. "Toward an integrated workforce planning framework using structured equations," Working Papers hal-01343368, HAL.
    8. Mariel Lavieri & Martin Puterman, 2009. "Optimizing nursing human resource planning in British Columbia," Health Care Management Science, Springer, vol. 12(2), pages 119-128, June.
    9. X Zhu & H D Sherali, 2009. "Two-stage workforce planning under demand fluctuations and uncertainty," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(1), pages 94-103, January.
    10. E. O. Ossai & M. S. Madukaife & A. U. Udom & U. C. Nduka & T. E. Ugah, 2023. "Effects of Prioritized Input on Human Resource Control in Departmentalized Markov Manpower Framework," Methodology and Computing in Applied Probability, Springer, vol. 25(1), pages 1-19, March.
    11. Seyed Hossein Razavi Hajiagha & Jalil Heidary-Dahooie & Ieva Meidutė-Kavaliauskienė & Kannan Govindan, 2022. "A new dynamic multi-attribute decision making method based on Markov chain and linear assignment," Annals of Operations Research, Springer, vol. 315(1), pages 159-191, August.
    12. Georgiou, Andreas C. & Thanassoulis, Emmanuel & Papadopoulou, Alexandra, 2022. "Using data envelopment analysis in markovian decision making," European Journal of Operational Research, Elsevier, vol. 298(1), pages 276-292.

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