Congestion Reduction through Efficient Empty Container Movement

  • Principal Investigator Maged Dessouky, Ph.D.
  • University of Southern California
The researchers created a model to solve the "Empty Container Problem" of freight operations. They tested the model using data from the Port of Los Angeles and the Port of Long Beach.
Project Status

Congestion Reduction Through Efficient Empty Container Movement Under Stochastic Demand

Research Product Type
Research Report
n this work, the authors developed a scheduling assignment for loaded and empty containers that builds on earlier models but incorporates stochastic (random) future demand. This report shows that the truck miles needed to satisfy the demand at all locations is reduced by about 4-7% when considering future stochastic demand as opposed to only considering today’s demand.

Congestion Reduction via Personalized Incentives

  • Principal Investigator Genevieve Giuliano, Ph.D.
  • University of Southern California
The purpose of this research is to develop real-time algorithms to reduce traffic congestion and improve routing efficiency via offering personalized incentives to drivers.
Project Status
In Progress