Airplane Optimizer

Inspiration

Wanted to do something with quantum computing and was interested in quantum hybrid algorithms

What it does

Applies the traveling salesman problem to the airplane industry and uses a quantum computer to compute the optimal solution

How we built it

• I took a list of airports, found their latitude/longitude to create a distance matrix
• Created a graph and mapped the distance matrix to the graph
• Mapped it to the Ising model then sent it to the quantum algorithm to optimize
• Take the answer and determined which path to take

Challenges we ran into

• Figuring out what the functions do and what the variables do in the Qiskit tutorial
• Trying to read and understand the Qiskit documentation
• Constant trial and error

Accomplishments that we're proud of

• Getting the distance matrix from the airports mapped onto the real graph for the quantum algorithm
• Getting the code to work

What we learned

• How the math/theory works for the algorithm
• How to create a distance matrix from scratch

What's next for Airplane Optimizer

• Create parameters and airspace limits (ie. can't fly over White House, etc.)
• Have it work for more airports (more nodes)

Built With

• python
• qiskit