Container Port Management—

Hong Kong International Terminals

Hong Kong International Terminals (HIT) is the largest privately owned container port operator in the world. The company asked CCRi to create a resource scheduler that would optimize container throughput for its sprawling Hong Kong facilities. At any one time, the resources at these facilities included 70,000 shipping containers, several hundred tractors, and 100 yard and quay cranes spread over six marshaling yards.

At one end of the terminal, quay cranes are working the ships, constantly offloading and unloading containers onto tractors, which move back and forth to the stacks. There, yard cranes take their containers and replace them with new ones. The tractors also service the trucks that transport goods to and from the port. Because space is at a premium, yard crane operators typically stack containers five or six high.

Scheduling A Real-World Conveyor Belt

The challenge for CCRi was to develop schedules for the yard and quay cranes that optimize container throughput. Essentially, this involves determining the best arrangement of containers in each stack at any one moment.

The challenge we faced was not simply one of maximizing speed or resource utilization—though those certainly were objectives. It also had to minimize the possibility of a snarl that, at critical moments, could bring the whole terminal to a standstill.

Optimizing Container Throughput

CCRi began by conferring with members of the HIT operations research department, observing their operations, and interviewing key employees. Based on these conversations, we developed a simulation of yard operations. We then optimized it to synchronize asset activities over a fixed time horizon while constantly monitoring for events, such as external tractor movements, that could result in schedule modifications.

When there is minimal tractor activity within the yard, the scheduler supports the use of yard cranes to reorder containers within a given stack to expedite their delivery to a ship or truck. CCRi contributed a number of key insights. First, not every container move needed to be an improving one as long as it set the stage for a better ultimate result. And the key parameter in scheduling was time, not number of moves. 

Taken together, CCRi's insight yielded container throughput improvement rates of between 10 and 20 percent. 

CCRi Capabilities

SIMULATION/OPTIMIZATION