A two-stage stochastic program for multi-shift, multi-analyst, workforce optimization with multiple on-call options
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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.
KeywordsWorkforce optimization Shift scheduling Staffing Scheduling On-call options Stochastic programming Column generation Cybersecurity
- Altner, D. S., Mason, E. K., & Servi, L. D. (2017). Scheduling and training multi-skilled analysts under uncertainty with many job types (submitted).Google Scholar
- Baker, S. F., Palekar, U., Gupta, G., Kale, L., Langer, A., Surina, M., & Venkataraman, R. (2012). Parallel computing for DoD airlift allocation, MITRE Corporation Technical Report.Google Scholar
- Bertsimas, D., & Tsitsiklis, J. N. (1997). Introduction to linear optimization. Belmont, MA: Athena Scientific.Google Scholar
- Kall, P., & Wallace, S. W. (1994). Stochastic programming. New York: Wiley.Google Scholar