Multiperiod vehicle loading with stochastic release dates

Production scheduling and vehicle routing problems are well-known topics in operations management. Although these tasks are consecutive in the supply chain, few optimization models tackle the associated issues. A most common situation, in practice, is actually that transportation management is disconnected from production planning: when production items or batches have been completely processed by the manufacturing plant, they become available for shipping, and they are consequently handled by the transportation managers. From a global managerial perspective, and with a view towards coordination of the product flows and customer satisfaction, this is not an ideal process. It is by far preferable, indeed, to set up an integrated production-transportation plan taking into account, among other constraints, the capacity of the plants and the customer due-dates. The present research proposes a methodology to investigate a multi-period vehicle loading problem with deterministic or stochastic information concerning items arrivals from production. Results from related optimization techniques are statistically compared and the benefits of the multi-period and stochastic modeling is demonstrated. Finally, an efficient heuristic is highlighted and is shown to be robust to the deviation from item arrival forecasts.