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Constraint Programming Scheduling

Constraint Programming Scheduling

 / 

Constraint Programming Scheduling

Constraint Programming Scheduling

A rail transport company engaged Blackbook.ai to streamline and scale their constraint programming project to improve train scheduling.

Technology Stack

predictive analytics

Predictive Analytics

Challenge

Yard Controllers for a rail transport company had no way of planning, simulating, optimising or visualising Day Of Operations (DOO) train movements through the yard. 

This was due to it is extremely difficult to do manually, there are no dedicated staff and static plans were quickly invalidated by DOO changes. Without some form of intelligent decision support that can react to DOO changes, yard coordinators were left to fend for themselves.

Solution

Blackbook was engaged to assist on the internal project that uses constraint programming to create the ‘optimal’ schedule for a train yard including entry, exit and unload as its main KPI points.

We provided Data Science and MLOps consulting to enable the client to streamline and scale the project to other sites quickly. This included scheduling a multi-kilometre coal train down to a segment of track, while taking into account track geometry constraints, operating constraints, vehicle constraints and user inputs for maintenance.

Outcome

As a result of Blackbook work on the project, the client was able to scale the project out to other sites resulting in insights or expertise gained by a controllers to be transferred to colleagues or new staff much more efficiently to improve traffic flow.

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