Analytical Tools for Modeling and Forecasting Global Maritime Cargo Flows under Changing and Uncertain Conditions

Global maritime shipping is a backbone of logistic operations for global seaborne trade. These systems are complex, containing hundreds of ports and thousands of shipping routes. Understanding and forecasting the system’s behavior given uncertainty in operational conditions due to weather, climate change impacts, workforce fulfillment levels, new opportunities for crossing the globe, disaster events, and more is important to businesses, shippers, carriers, port stakeholders, regions, and others. This dissertation proposes mathematical models and solution algorithms for estimating and forecasting flows through the maritime system and the system’s performance under changing and uncertain conditions. These conditions arise both from new opportunities, such as the potential to employ Arctic passageways with limited special equipment, and existing and new risks, such as from increased wave heights due to climate change, increased occurrence of disaster events, and concerns about workforce availability. These advancements contribute to an ability to maintain a reliable and resilient global maritime shipping network and the supply chains they support.This dissertation contributes to these modeling and forecasting capabilities in three key areas. Specifically, it presents: (1) A high-fidelity and updatable containerized and bulk cargo shipping network representation with 161 seaports covering 52 countries constructed on publicly available, updatable data sources and mixed-integer linear strategic cargo routing model with combined gradient descent and relax-and-fix decomposition solution methods for estimating global seaborn trade flows. (2) A risk-constrained maritime cargo flow model with exact Benders-branch-and-cut and data-driven Bayesian network solution methodologies for predicting changes in global cargo vessel traffic across a maritime network incorporating Arctic ports and passageways under future reduced-ice shipping scenarios. (3) Quantification of the maritime network’s performance under different disaster events ranging from port-related workforce shortages to natural disasters through a capacity-constrained maritime cargo flow optimization model with workforce level-related scenarios and an Equilibrium Program with Equilibrium Constraints (EPEC) formulation for making coalition-based cross-port investments under natural disaster scenarios, respectively. These analytical tools provide modeling and forecasting capabilities needed to, not only give insights to stakeholders involved in global seaborne trade, but to understand the ramifications of changing trade flows, climate conditions and opportunities on economies, local peoples, the environment, and more.

Author

• Li, Wenjie

Identifier

hdl:1920/14021

OAI identifier oai:identifier

oai:MARS:1920/14021