Inspiration

Our inspiration came from the challenge itself -- how can we maximize profits from insurance package offerings with different combinations of coverages? As the number of coverages increases, the number of possible combinations of coverages in packages increases exponentially--with just 20 coverages and 10 packages, there are 2^200 possibilities for profit outcomes! This would take an eternity on classical computers--thus, we are experimenting with quantum optimization algorithms, QAOA and DQI, to see if we can a) speed up the process and b) find higher quality solutions for maximized profit, especially with an increasing number of coverages.

What it does

How we built it

Challenges we ran into

Accomplishments that we're proud of

What we learned

What's next for A Unique Method to do Optimization

Built With

  • guppy
  • helios
  • jupyter
  • pulp
  • python
  • selene
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