A sailing control strategy based on NSGA II algorithm to reduce ship carbon emissions

Abstract

This study aims to develop effective control strategies for the shipping industry under the carbon-neutral scenario. In this paper, two mainly control strategies is considered for ships to reduce carbon emissions: one is to levy a tax on ship carbon emissions (TSCE), and the other is multi-objective speed guidance services (MOSG). The above two strategies can be supervised and implemented by government departments, such as maritime safety administration. Then, taking the ship’s sailing speed as the decision variable, the two mathematical models based on TSCE and MOSG scenarios are established. It should be noted that the goal of TSCE model is to minimize the sailing cost, and for the MOSG model, the goal is to simultaneously minimize sailing costs and CO2 emissions. The above the models are solved by Nondominated Sorting Genetic algorithm-II (NSGA-II) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) algorithms. The proposed models are applied a voyage along the coast of China, the results show that compare to CE, MOSG can reduce CO2 emissions by more than 10%, and sailing costs also can be reduced by more than 1.5%. Moreover, the existing Emission Control Area (ECA) regulations are also be considered in the proposed models, and the results show that simultaneously implementing both ECA and TSCE may result in the “1+1<2” phenomenon, that is, ECA and TSCE will limit each other’s emission reduction effect. Therefore, compare with TSCE, MOSG is a more effective decarbonization approach for the shipping industry.