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Two-stage workforce planning under demand fluctuations and uncertainty

Author

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  • X Zhu

    (Virginia Polytechnic Institute and State University)

  • H D Sherali

    (Virginia Polytechnic Institute and State University)

Abstract

We address a multi-category workforce planning problem for functional areas located at different service centres, each having office-space and recruitment capacity constraints, and facing fluctuating and uncertain workforce demand. A deterministic model is initially developed to deal with workforce fluctuations based on an expected demand profile over the horizon. To hedge against the demand uncertainty, we also propose a two-stage stochastic program, in which the first stage makes personnel recruiting and allocation decisions, while the second stage reassigns workforce demand among all units. A Benders’ decomposition-based algorithm is designed to solve this two-stage stochastic mixed-integer program. Computational results based on some practical numerical experiments are presented to provide insights on applying the deterministic versus the stochastic programming approach, and to demonstrate the efficacy of the proposed algorithm as compared with directly solving the model using its deterministic equivalent.

Suggested Citation

  • 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.
    • Handle: RePEc:pal:jorsoc:v:60:y:2009:i:1:d:10.1057_palgrave.jors.2602522
    DOI: 10.1057/palgrave.jors.2602522
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    References listed on IDEAS

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    Cited by:

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    4. Jingbo Huang & Jiting Li & Yonghao Du & Yanjie Song & Jian Wu & Feng Yao & Pei Wang, 2023. "Research of a Multi-Level Organization Human Resource Network Optimization Model and an Improved Late Acceptance Hill Climbing Algorithm," Mathematics, MDPI, vol. 11(23), pages 1-19, November.
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