Oil Product Distribution Planning Via Robust Optimization

This paper approaches the tactical distribution planning in the downstream oil supply chain (DOSC) under uncertain market conditions by using robust optimization (RO). The tactical RO model makes use of general polyhedral uncertainty sets, which encompass the so-called ramping constraints. These restrain the maximum variation in the random parameters, so that the time correlation present in the input time series can be captured, as well as the level of conservatism of the robust solutions can be adjusted. Additionally, autoregressive integrated moving average (ARIMA) techniques and Monte Carlo simulation are used in order to determine the parameters of the uncertainty sets. An example based on the Portuguese DOSC is studied so as to confirm both the applicability and adequacy of the developed RO models to real-world problems.