Green logistics of crude oil transportation: A multi-objective optimization approach

Crude oil logistics activities, which are mostly carried out using ships, are one of the contributors to greenhouse gas (GHG) emissions. GHG emissions from logistics activities are predicted to increase significantly by 2050, so they need to be controlled with the right logistics planning strategy. This study aims to apply the green logistics concept in crude oil transportation that considers multiple depots and heterogeneous fleets by using multi-objective optimization (MOO). This study investigates a case study of crude oil logistics to a refinery unit in 6 scenarios with single-objective optimization (SOO) and MOO cases. Each of the scenarios differs in objective functions and ship's fuel type (i.e. diesel and LNG). Optimization is performed to select the best option of crude oil supply sources and the type of ships that carry crude oil to the refinery unit in each scenario. The results show that in MOO scenarios, the use of LNG fueled ships and optimized routes can reduce CO₂ emissions and logistic costs by 27.8% and 50.6% compared to average current crude oil logistic cases. MOO scenarios with LNG ships also performed better compared to the diesel-fueled option, it can reduce CO₂ emissions by 18.5% without a significant increase in total logistic cost. Furthermore, the SOO and MOO comparison shows the effect of applying green logistics by using MOO, resulting in less GHG emissions with unnoticeable change in cost.