Affiliation:
1. Business School, Dalian University of Foreign Languages, Dalian 116044, China
2. Collaborative Innovation Center for Transport Studies, Dalian Maritime University, Dalian 116026, China
Abstract
In the post-pandemic era, the complexity of the international shipping situation, such as environmental policies, port congestion, and local conflicts, poses challenges to the stability of liner shipping, which requires strict adherence to schedules. This paper addressed the issue of schedule recovery for liner ships operating under Emission Control Areas (ECAs) regulations in the face of disruptive events. It established a bi-objective nonlinear programming model based on recovery costs and delay severity and designed a bi-objective particle swarm optimization algorithm based on two traversal of voyage leg path selection and port skipping decisions of feasible solutions to solve it. The effectiveness of the algorithm was validated through a case study of a 6000 TEU liner ship, summarizing the correlation laws of operational decisions such as port skipping, voyage leg path selection, and speed adjustment, and proposing the optimal recovery strategy for liner ships under long-term ECA constraints while ensuring short-term schedule resilience. The findings demonstrate that, in compliance with emission restrictions, ships operating within ECA are required to slow down to mitigate costs. In contrast, ships operating outside of ECA regions must accelerate their pace to adhere to established shipping schedules.
Funder
National Natural Science Foundation of China
National Key Research and Development Program of China
Foundation for Humanities and Social Sciences of Ministry of Education of China
Natural Science Foundation of Liaoning Province of China
Transportation Science and Technology Plan Project of Henan Province of China
Fundamental Research Funds for the Central Universities of China
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