mass_transit_COVID

Mass Transit algorithm that optimized distance between passengers using seat assignment

Problem

Carriers are burning through between $10 and $12 billion a month due to travel halt. National average of roughly one passenger for every 20 seats on Airlines. There is no lack of legislation in regards to a mass transit passenger placement safety protocol. Currently, passenger safety is up to discretion of the flight attendant and digital selection of seats when purchasing a ticket. The CDC, WHO, TSA, and Airlines for America can fill this gap with by using an algorithm such as this.

Solution

Using input of rows, columns, and passengers, the algorithm can determine the optimal passenger placement.

Troubles / Bugs

I had trouble dealing with handling and merging 2D arrays. Furthermore, in its current state, the algorithm has flaws with dynamically adjusting to extra rows.

Future Improvements

I look to update the algorithm using shortest path/graph theory algorithms such as Floyd-Warshall algorithm or Dijkstra's algorithm. Moreover, when I began the project, I knew graph theory and dynamic programming would be a better route to a solution but am excited to work towards their implantation after the HealthHack.

Built With

• python