Green maritime: a routing and speed multi-objective optimization strategy

Abstract

The purpose of this paper is to develop a ship routing and speed multi-objective optimization model that considers ECA (Emission Control Area) regulations, which can realize the minimization of both shipping costs and emissions. This proposed model can help maritime regulators, such as those who work in maritime departments, to trade-off shipping costs for the minimization of CO2 and SOx emissions by selecting appropriate routes and speeds. The total costs are the sum of the fuel costs, fixed time costs, and cargo inventory costs. The difference between the significance of SOx emissions inside and outside ECAs was considered. The Non-dominated Sorting Genetic Algorithm II (NSGAII) was used to obtain the Pareto-optimal set of the multi-objective optimization model and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) was used to find the trade-off solution from the Pareto-optimal set. The model was applied for a case study of a service route from Halifax, Nova Scotia, Canada to Brunswick, Georgia, United States. Compared to an actual scenario without any optimization, the results show that the model can simultaneously reduce a ship’s total costs and emissions, as well as avoid increase in the total costs that accompany increase in fuel prices. Moreover, the model can provide different optimal routes and speeds for different levels of ship emissions (CO2 and total SOx inside ECAs).