Note: Dr. Randall further explains the benefits of combining simulation and optimization in the cover article of the current issue of Analytics Magazine.
North American railroads have invested billions of dollars in recent years on terminals and infrastructure to improve rail intermodal, the transportation of containers and trailers on flat cars, which accounts for a quarter of major railroad revenue. In some cases, these investments have included the development of advanced technologies and analytics to assist speed and service and to ensure that intermodal remains an essential transportation strategy for shippers.
Intermodal terminals, where containers are transferred from one mode of transportation to another (truck, rail, ship, air), vary greatly in their size, physical characteristics and complexity. A Class I railroad-owned intermodal terminal, where rail is one of the modes, is a critical operational hub and a focal point for a region’s freight. It may cover more than 100 acres and process as many as 200,000 container transfers per year.
A rail intermodal terminal includes an intermodal yard, where trains are loaded and unloaded by cranes or lifts. Typically, hostlers bring containers trackside or to a storage area. Containers are transferred by rail-mounted gantry cranes that can straddle several tracks. The storage area acts as a buffer between the drayage system and the intermodal yard. Often, containers are directly transferred to a chassis waiting to be picked up for delivery. At the gate, truck drivers present proper documentation for pick up or delivery and inspection is done. There are also areas dedicated to maintenance and chassis storage.
As they continually improve efficiency and velocity, leaders of multiple rail intermodal terminals sought the ability to answer strategic and operational questions and evaluate policy changes and different scenarios. Rigorous analytics are required to support process changes at a terminal because they are so expensive and often entail additional resources and equipment.
For strategic evaluations, the leaders wanted to assess expected changes in KPIs based on changes in anticipated inbound gate traffic, number of express and regular lanes, cutoff times, train schedules, parking profiles, and terminal and gate hours of operation. They sought to consider the impact of compressing traffic into a smaller time-window on resource planning, dwell time, and on cranes and hostlers. Another representative change to evaluate was rescheduling drivers to pick up on weekends or at night.
Operationally, it was important to understand when a train would be ready to release or finish unloading, and to understand the result of adding or removing hostlers or cranes or otherwise changing the resource plan, and how would that impact loading and unloading times. Other representative issues included the effect of changes in work assignment on loading and unloading times, and the impact of early or delayed train arrivals and other disruptions.
Leadership also requested a system to test operational software under development in a realistic, dynamic environment. One such software solution was a custom tool to dynamically assign optimal parking spots to container, trailer, and chassis entering the yard via the gate or train to maximize resource productivity.
The company retained Princeton Consultants to build a rail intermodal terminal simulation solution, a computer model that realistically imitates the operation of a real-world process or system over time and accounts for resources and constraints, as well as the way entities interact as time passes. By changing the parameters of the simulation, executives would be able to predict the behavior of the system under certain conditions. A simulation solution incorporates real-life randomness, so its results will differ each time; users run a simulation many times to average out different runs to achieve expected results.
To create base use cases, functional requirements and functional design, our team visited several terminals, conducted time and motion studies, interviewed resources and management, and observed hostler and crane operators. It was necessary to account for the many sources of uncertainty at a terminal, such as late trains, power or network outages, equipment malfunctions, inclement weather, and terminal congestion.
In developing a highly customized solution using advanced simulation software, the team worked iteratively with the business users and subject matter experts to validate progress leveraging the visual component of the simulation to allow users to understand the simulation behavior, and benchmark against baseline terminal operations.
Since its completion in 2017, the custom simulation solution has run many analyses for business leaders and managers of multiple terminals. The solution has calculated ROI and provided confirmation for decisions such as adding in-gate lanes to reduce queue times.
Current work entails “optimization-simulation” in which the simulator calls the parking optimization solution to test and adjust its solutions over months of simulated operations. The optimization solution requires extensive testing, which is not feasible in a real-world terminal setting.
The company’s leaders and terminal managers will continue to use the simulation solution to assist high-value strategic and operational decisions, and to test next-generation optimization-powered software tools that will accelerate improvements in efficiency and throughput.
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