The Drayage Problem, That of Sequencing Deliveries of Empty and Full Containers on a Network

ABSTRACT

The drayage problem, that of sequencing deliveries of empty and full containers on a network of rail yards and customers, is a pressing issue in intermodal traffic, and particularly in the Chicago area, which is known for its congestion issues. We consider an arc-based formulation for the problem that furthers the published work in the field by addressing time windows. We show that even for small problems, the arc-based formulation results in very large models that require significant computation to solve. INTRODUCTION Chicago, with 26 operating rail yards and 25,000 container lifts per day, is a significant hub for intermodal transportation. However, the hub is congested; there are significant problems with traffic and pollution that have led Chicago to be known as the “black hole” of intermodal freight.

The problems at the interface of truck and rail include: lack of coordination by railroads on where containers should be lifted; lack of uniform equipment; schedules and takedown times vary; finally, the city has concerns over pollution, congestion, road damage, and safety.

This project, part of a larger study of intermodal rail in Chicago, focuses on the logistics problems faced by the trucking companies. The question we try to solve is: given a fleet of trucks and a set of container movements, what is the most efficient assignment and sequencing of moves to trucks? MODEL COMPONENTS

Customers Shippers – product moves from customer to railyard Consignees – product moves from railyard to customer

Customer behavior Stay With – driver arrives with an empty container; waits for it to be filled; then moves to the railyard (opposite for consignees) Drop and Pick – driver arrives without a container; picks up already-loaded container; delivers to railyard

Multiple railyards

Container yards (empty container storage)

Deadlines and release times for containers at railyard

Time windows for each customer

Dwell times to model wait at customer site