Green Logistics of Crude Oil Transportation: A Multi-objective Optimization

The transportation of crude oil from production sites to refineries plays a crucial role in the petroleum industry. The present study focuses on implementing green logistics in crude oil transportation by employing multi-objective optimization. It aims to minimize logistics costs and CO2 emissions by selecting optimal parameters, taking into account different depots and fleets with diesel and liquefied natural gas (LNG) fuel types. Real data from a logistics case study involving crude oil reported in the literature is utilized to determine the quantity of crude oil to be transported from various oil fields to the refinery unit. Initially, a mathematical model is developed with two objectives namely minimization of CO2 emissions and logistics cost of fuel transportation. By using non-dominated sorting genetic algorithm (NSGA-II), a set of Pareto optimal solutions is obtained for both LNG and diesel-fueled ships. The obtained solutions provide valuable insights into the possible combinations of factors for achieving efficient logistic cost while minimizing CO2 emissions.