Robust scheduling of liner shipping under disruption scenarios

This research proposes a new recovery model for addressing issues with container ship disruptions. To minimize the negative impact of these disruptions, the model formulates a mixed-integer programming approach that simultaneously considers three recovery strategies, namely vessel speeding-up, port skipping, and alternative routes.
The study clusters call-ports and utilizes port hubs to minimize transshipment costs while considering factors such as port capacity, queuing time for loading/unloading, and the economic value of cargo to identify the optimal port hubs.
The nonlinear problem is initially linearized using precise methods and then solved using CPLEX software. The results are anticipated to demonstrate a reduction in disruption losses. To account for the uncertainty in delay duration and disruption location, the study uses a robust optimization approach as a two-stage stochastic programming methodology.

Faculty Supervisor:

Hamid Afshari

Student:

Partner:

ISEN

Discipline:

Engineering

Sector:

Transportation (excluding aerospace); Sustainability & the Environment; Ocean Tech

University:

Dalhousie University

Program: