Container shipping network analysis
There has long been a need to understand how cargo flows are structured within the global container shipping market, which accounts for over 90% of non-bulk worldwide cargo, and has been instrumental in the rise of globalisation and modern economy.
While previous studies have resolved to the use of simulation, research by TSL and our collaborators has led to the development of a linear container flow assignment model that can obtain results quickly, with minimal data requirements and a wide range of applications.
Liner services tend to be circural (ie. start and end in the same port) and visit several ports throughout their journey, and at any time carry many different groups of containers, each with a different combination of origins and destinations.
The hub-and-spoke structure adopted by the container shipping industry have been central to the success of the sector, as it facilitates the quick and efficient routing of containers between ports that are not directly connected.
The modelling framework developed by TSL can be used to predict the flows of full and empty containers across a given set of services, taking into account market demand, operational costs, vessel and port capacities. An example is shown in the figure below, based on a case study that we used in a recent article.
Our models have been used to determine optimal service configurations and predict demand container traffic in new container terminals.
Game-theoretic analysis of the interaction between competing liner shipping operators, and determine succesful market strategies.
Detection of network vulnerabilities and design of strategies to reduce the impact of natural disasters, strikes or conflicts.
Liner shipping network resilience
In response to emerging geopolitical tensions in the Arabian Peninsula and the South-East Asia Sea, TSL developed a modelling framework for the analysis of disruptions to container shipping services. This research was featured in two recent publications.
Structured as an attacker-defender model, our algorith can identify potential disruption targets, using the cost of container flow rerouting over other parts of the network. The outputs of our proposed framework can be used to inform the design of future services, and investment decisions by port operators who wish to increase the overall resilience of their operations.