Balancing flexibility and inventory in workforce planning with learning

We examine the problem of assigning workers to tasks, seeking to maximize profits, while taking in consideration learning through experience and stochasticity in demand. As quantitative descriptions of human learning are non-linear, we employ a reformulation technique that uses binary and continuous variables and linear constraints and is mathematically equivalent in nearly all cases. Similarly, as demand is not assumed to be known with...