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 three minutes to produce solutions within 6% of a true lower bound of the optimal for 99% of over 150 test cases.
Altner, D.S., Rojas, A.C. & Servi, L.D. Journal of Scheduling, to appear (2018). https://doi.org/10.1007/s10951-017-0554-9
View A Two-Stage Stochastic Program for Multi-shift, Multi-analyst, Workforce Optimization with Multiple On Call Options