A Two-Stage Stochastic Shift Scheduling Model for Cybersecurity Workforce Optimization with On Call Options

This paper proposes a model and algorithm for optimizing staffing and shift scheduling decisions at a 24/7 cybersecurity operations center. We study a two-stage stochastic shift scheduling problem over a 14-day pay period with three shifts per day, several staffing and scheduling constraints, uncertain workloads and on call staffing options. We solve this problem with a heuristic simplification of branch-and-price whereby we only generate columns at the root node in the branch-and-bound tree. Our computational study shows this method quickly finds good quality solutions on instances with 10 independent workload scenarios for each shift and each day.