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The encyclopedia · Engineering & Operations · Operational decision · 2017–2018

BNSF's Crew Decision Assist optimizes the human side of rail ops

A tailored crew-scheduling model handles extra crew, joint moves and schedule uncertainty — replacing manual planning with millions in yearly savings.

BNSF Railway

the move

Crew costs — wages plus repositioning and lodging away from home — are a significant slice of a railroad's operating expenses, and rail moves about 40 percent of U.S. freight by ton-miles. BNSF wanted to replace manual crew planning with a systematic approach.

With the University of Texas at Austin, BNSF built Crew Decision Assist (CDA): a tailored optimization model that captures what standard crew-scheduling models miss — the option to use extra crew and policies that jointly reposition engineers and conductors — and accounts for uncertainty in train schedules.

CDA pulls data from existing systems and quickly generates effective deployment plans, and is expected to yield cost savings of several million dollars per year.

The work was a finalist for the 2017 INFORMS Daniel H. Wagner Prize for Excellence in Operations Research Practice.

why it works

  • Manual planning cannot weigh all crew options and schedule uncertainty at once.
  • Joint engineer-conductor moves and extra-crew options are where the savings hide.
  • Fast plan generation makes optimization usable by dispatchers daily.
  • Millions in expected yearly savings justified the build.
the payoffModel the crew pool, not just the trainclever

what transfers

On a railroad, people are a big variable cost; treating crew assignment as a real optimization problem converts a manual daily grind into a fast, auditable plan worth millions a year.

what came after

BNSF deployed Crew Decision Assist for crew scheduling on single-ended districts; the system generates deployment plans quickly from existing data with several million dollars of expected annual savings, and the project was a 2017 Wagner Prize finalist.

references

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