Green Container Shipping Schedule Design Considering Collaboration and Disruption Recovery

Abstract

Emission reduction ambition in shipping and efforts to provide measures to achieve zero emission in the industry is increasing in parallel to global environmental concerns. Designing container shipping schedules that create minimum emissions can help to achieve the zero-emission target. This study proposed a comprehensive green container shipping scheduling model considering port and sea passage disruption recovery i.e., speed adjustment, port skipping, and collaboration of carrier and terminal operators because using only speed increase as a disruption recovery measure results in increased emissions. A mixed-integer multi-objective robust programming model was developed and applied to a real-case container line service demonstrating its benefits regarding emissions and operational costs. The results showed that different instances of the model can be solved in a reasonable time by a generic solver. The experimental results demonstrated that the most effective disruption recovery measure in terms of both operational costs and emission tonnages is the time window collaboration. The insights gathered from the application of the model can benefit container lines that are willing to reduce their emissions and can help policymakers provide effective emission reduction policies by taxing emissions and ship fuel.