Robust maritime disruption management with a combination of speedup, skip, and port swap strategies

Abstract

A large volume of global transportation is carried out annually by liner shipping companies and it includes a large portion of global trade. Accordingly, due to the countless number of these voyages, precise planning in this field is vital to prevent severe loss. One of the noticeable issues that occur during the voyage can be natural or human disruption which is interpreted as a “delay” in the liner shipping services. Therefore, there is a need to reschedule the pre-established plan to compensate for the delays and reduce the costs including the penalties and exceeding fuel consumption. In this paper, a novel recovery model is proposed for container ship problems. This mixed-integer programming model with the use of speedup, skip, and swap ports strategies not only attempts to mitigate the dire financial consequence of the disruption but also reduces the carbon footprint. Furthermore, to ensure customer satisfaction, the alternative transshipment decision for the skipped ports cargo is considered in the model. The nonlinear model is linearized through the exact techniques, then solved in CPLEX software. As a result, the primary deterministic model could act as a “wait-and-see” solution to reduce disruption losses by up to 66% using simultaneous recovery strategies of speedup, skip and swap. However, a robust optimization approach is proposed owing to the uncertainty in delay time, type, severity, and point of disruption. This approach enables the model to face a wide variety of disruptions (that are predicted under different scenarios each of which is associated with an occurrence probability) and recommends an augmented schedule that guarantees to be feasible, optimal, and resistant. The robust model is applied in a real case from the maritime industry, and the value of robustness is reported. The results demonstrate the superiority of this model compared with others.