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Strategic workforce planning for the Australian Defence Force

Author

Listed:
  • Mark E T Horn

    (CSIRO Digital Productivity and Services Flagship, Sydney, Australia)

  • Tarek Elgindy

    (Carnegie-Mellon University, Pittsburgh, USA)

  • Antonio Gomez-Iglesias

    (The University of Texas at Austin, Austin, USA)

Abstract

This paper presents a mixed integer linear programming (MILP) model to aid in planning a large, hierarchically structured workforce. The workforce (eg, all Army commissioned officers) is classified by occupational group and rank and modelled in yearly intervals. Personnel and their movements are modelled as stocks and flows, subject to constraints representing employment conditions and resource limitations. The task is to estimate personnel numbers and flows so as to minimize a composite cost function. The model’s detailed fidelity to actual conditions, and hence its value in practice, clearly exceed previous efforts in the workforce planning domain. To overcome computational challenges that arose when an MILP solver was applied directly, the authors developed an iterative solution approach, which has yielded an attractive combination of solution quality and computational performance.

Suggested Citation

  • Mark E T Horn & Tarek Elgindy & Antonio Gomez-Iglesias, 2016. "Strategic workforce planning for the Australian Defence Force," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 67(4), pages 664-675, April.
    • Handle: RePEc:pal:jorsoc:v:67:y:2016:i:4:p:664-675
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    Citations

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    Cited by:

    1. Oussama Mazari-Abdessameud & Filip Van Utterbeeck & Guy Van Acker & Marie-Anne Guerry, 2020. "Multidimensional military manpower planning based on a career path approach," Operations Management Research, Springer, vol. 13(3), pages 249-263, December.
    2. Cardoso-Grilo, Teresa & Monteiro, Marta & Oliveira, Mónica Duarte & Amorim-Lopes, Mário & Barbosa-Póvoa, Ana, 2019. "From problem structuring to optimization: A multi-methodological framework to assist the planning of medical training," European Journal of Operational Research, Elsevier, vol. 273(2), pages 662-683.

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