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The Route Machine: An Optimization Framework (Phase 1)

Start Date: April 2019
Funding: UW Medicine Department of Laboratory Medicine
Principal Investigator(s): Dr. Anne Goodchild

The University of Washington Department of Laboratory Medicine runs 12 routes per day moving lab specimens and conducting departmental business. These routes have been developed over time in an ad hoc fashion.

The Urban Freight Lab will primarily focus on the following objectives for optimization:

  1. Minimize expected lead time (from the time the specimens are ready for pick up to the time they are delivered to the lab for testing)
  2. Minimize the extent to which couriers work outside of their maximum shift durations

The decisions the ‘route machine’ optimization framework ideally should inform:

  1. Day-to-day (operational) decision-making: Given all of the current capacities (i.e., number of vehicles) can routes be improved through changing order of routes or destinations serviced in route?
  2. Tactical decision-making: What modifications to the current capacities (i.e., increasing the number of vehicles) will produce the greatest benefit? How will the optimal routes change if there are modifications to customer requirements?
  3. Strategic decision-making: If UW Medicine Department of Laboratory Medicine expands its operations how will routes and capacities need to change to accommodate the new situation? What should the workforce balance between full-time workers and contractors look like?

This analysis includes:

  • Phase 1: Evaluate the existing routes on a qualitative basis to judge whether there is sufficient opportunity for improvement, and strategies that show greatest opportunity for improvement
  • Phase 1: Conduct an inventory of off the shelf tools and determine their suitability for the application
  • Phase 2: Build the Route Machine tool, either using off-the shelf software tools, building the tool from scratch, or some combination of the two.