Better Delivery/Pick Up Routes in the Presence of Uncertainty

This report examines the Courier Delivery Problem, a variant of the Vehicle Routing Problem with time windows in which customers appear probabilistically and their service times are uncertain. The authors use scenario-based stochastic optimization with recourse for uncertainty in customers and robust optimization for uncertainty in service times. A model is proposed which generates a master plan and daily schedules. The model maximizes the coverage of customers and the similarity of routes in each scenario and minimizes the total time spent by the couriers and the total earliness and lateness penalty. For the large scale problem instance, the authors develop a two-phase insertion based approximate solution procedure known as Master And Daily Scheduler (MADS) to balance these different objectives. The authors then provide simulation results and show that their heuristic improves the similarity of routes and the lateness penalty at the expense of increased total time spent when compared to a solution by independently scheduling each day. Results from experiments also demonstrate improvements over a real-life solution.