Optimize scheduling of human resources and service vehicles - AB-034

Preferred Disciplines: Mathematics, Computer Science (Master, PhD or Post-Doc)
Project length: 4-6 months (1 unit) per intern
Desired start date: As soon as possible
Location: Airdrie, AB
No. of Positions: 2
Preferences: Biggest brains closest to Airdrie. Exact institution we are indifferent; just want to work with the smartest people available.
Company: Anonymous

About Company:

National fleet of service technicians working coast to coast to coast.  Servicing hundreds of thousands of assets across thousands of locations for hundreds of customers.

Project Description:

Organisation needs to route service vehicles across Canada on multi-day service trips; typically a 5 day to 15 day trip, servicing 1 to 12 different customers across 1 to 50 different job locations. 

  • Different service types
  • Different human skills / certifications available
  • Different service vehicles available
  • hundreds of thousands of service locations in Canada
  • thousands of service orders fulfilled annually

Not an easy puzzle

Lots of puzzles, caveats and constraints

Research Objectives/Sub-Objectives:

  • Objective is to apply deep learning / machine learning using historical trip data from the last 10 years to better identify efficiencies, rulesets and to ultimately use artificial intelligence for all future scheduling of human resources.
  • Build artificial intelligence to replace human scheduling process


  • Rapid Experimental Development
  • Many Iterations and Revisions

Expertise and Skills Needed:

  • Deep learning techniques / understanding
  • Algorithmic analysis / processing
  • Software development
  • Statistical analysis
  • All work is done on Ubuntu / Linux computers and servers


For more info or to apply to this applied research position, please

  1. Check your eligibility and find more information about open projects.
  2. Interested students need to get the approval from their supervisor and send their CV along with a link to their supervisor’s university webpage by applying through the webform or directly to Oba Harding at, oharding(a)mitacs.ca.