Shift scheduling problem in same-day courier industry

This paper deals with the problem of minimizing the staffing cost of a same-day courier company subject to service-level requirements. The problem has been modeled as an integer program with nonlinear probabilistic constraints. We have devised a heuristic procedure to explore the search space efficiently through an approximated neighborhood evaluation (ANE) model, relying on the estimation (via simulation) of a reduced number of parameters. Computational results show that, compared to traditional neighborhood search procedures, the ANE approach provides significant cost reductions in a typical same-day courier setting.