Scheduling decision model of liner shipping considering emission control areas regulations

Abstract

Several Emission Control Areas (ECAs) have been established to limit sulfur emissions from ships, thus influencing ship voyage planning. In this study, we used a mixed integer nonlinear programming model (MINLP) to reschedule ports-of-call sequences, ship route, speed, and bunkering strategy to minimize total sailing costs, defined as the sum of bunkering costs, time costs, and carbon emissions costs. An improved genetic algorithm, which introduced many strategies (Multi-layer coding strategy, Pre-search and tabu search strategy, Crossover strategy with a correction method, Mutation strategy based on 2-opt method, Elite strategy and Dynamic programming strategy) is designed to solve the proposed model. The proposed model was then applied to ECAs in North America under different fuel prices. The results show that the proposed method can reduce total sailing costs and help shipping companies effectively cope with fuel price fluctuations.