- Urban Logistics
Improving efficiency and sustainability in logistics and transportation has been a strategic priority for companies and countries as they compete in the era of globalization. However, how to optimize the container transportation and improve container turnaround has become an increasing challenge for the industry, especially in the growing trade imbalances and more frequent disruptions. To overcome this challenge, container triangulation offers remarkable opportunities to the carriers to reduce the transportation of the empty containers, and therefore, improve the turnaround. Container triangulation can be identified as the reuse of the import containers for export. Despite a number of potential benefits of container triangulation may offer, it is challenging to scale-up in China due to the fragmented market and the lack of accurate location data. To focus on this challenge, this research investigates the digitalization of container triangulation as an alternative solution, where matching decisions are automated in a digital platform. This research examines the current process and challenges of automating container triangulation in China for Maersk and explores how to optimize and accelerate this solution. With this motivation, we conducted expert meetings, analyzed data, and applied machine learning algorithms and mixed-integer linear programming to enable container triangulation routing optimization on the company's digital platform. The result showed a trucking cost savings from 11% - 14%, a transportation lead time reduction from 8% - 10%, and a reduction in CO2 emissions from 8% - 10%. However, the savings would be further reduced with more restrictive conditions for execution. To scale up the solution, we recommend the cooperation of different parties of the container transport industry to share the incentives and adopt the digital solution.