Workforce Management and Optimization using Stochastic Network Models

We develop a model based on stochastic loss networks to characterize the dynamics and uncertainty in general workforce management and optimization. We formulate profit maximization problems with serviceability constraints under different assumptions on demand and supply. Though these optimization problems are in general nonlinear programming problems, we are able to observe some intrinsic properties of the functions that facilitate efficient computation of the optimal solution. Numerical results demonstrate that our model provides capacity planning decisions that yield better results than available in current practice.