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A two-stage stochastic program for multi-shift, multi-analyst, workforce optimization with multiple on-call options

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  • Douglas S. Altner

    (The MITRE Corporation)

  • Anthony C. Rojas

    (The MITRE Corporation)

  • Leslie D. Servi

    (The MITRE Corporation)

Abstract

Motivated by a cybersecurity workforce optimization problem, this paper investigates optimizing staffing and shift scheduling decisions given unknown demand and multiple on-call staffing options at a 24/7 firm with three shifts per day, three analyst types, and several staffing and scheduling constraints. We model this problem as a two-stage stochastic program and solve it with a column-generation-based heuristic. Our computational study shows this method only needs 3 min to produce solutions within 6% of a true lower bound of the optimal for 99% of over 150 test cases.

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  • Douglas S. Altner & Anthony C. Rojas & Leslie D. Servi, 2018. "A two-stage stochastic program for multi-shift, multi-analyst, workforce optimization with multiple on-call options," Journal of Scheduling, Springer, vol. 21(5), pages 517-531, October.
    • Handle: RePEc:spr:jsched:v:21:y:2018:i:5:d:10.1007_s10951-017-0554-9
    DOI: 10.1007/s10951-017-0554-9
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    Cited by:

    1. Douglas S. Altner & Erica K. Mason & Les D. Servi, 2019. "Two-stage stochastic days-off scheduling of multi-skilled analysts with training options," Journal of Combinatorial Optimization, Springer, vol. 38(1), pages 111-129, July.
    2. Shoufeng Ma & Hongming Li & Ning Zhu & Chenyi Fu, 2021. "Stochastic programming approach for unidirectional quay crane scheduling problem with uncertainty," Journal of Scheduling, Springer, vol. 24(2), pages 137-174, April.

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