Here we approximate the order of deals we should visit using a modified TSP algorithm
This is an example map with a traffic heat map over-laid on it.
Here is a display of a completed path (colored green). The traffic map's dense areas are colored red.

Inspiration

This problem sparked our interest because it brings together many fascinating algorithms in computer science to solve a real-world problem.

What it does

This project takes a Walmart map, traffic heat map, and various deal locations as inputs and outputs an efficient path to reach all deals

How we built it

We built it using Python primarily. We made heavy use of a traveling salesman algorithm and an A* algorithm to find paths from deal to deal.

Challenges we ran into

The time constraint of 60 seconds presented many challenges as many of our solutions took 1-2 minutes to run.

Accomplishments that we're proud of

We're proud of the progress we made with minimal experience using the A* algorithm and solving the traveling salesman problem. We also stayed up all night. All night.

What we learned

We learned that sometimes it simply isn't practical to find the best possible solution, as is the case with the traveling salesman problem. Instead, accurate approximations based on statistics and data analysis are often the most realistic solutions to the complex problems encountered in the real world.