Skip to content

miclindahl/tsp-streamlit

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

4 Commits
 
 
 
 
 
 

Repository files navigation

tsp-streamlit

Animation of solving the traveling salesman problem to optimality using mixed-integer programming and iteratively eliminating sub tours. The optimization is done using gurobi and the visualization is made using streamlit

Install streamlit and run with this command: streamlit run tsp-app.py

The traveling salesman problem is a NP-hard problem where the goal is to find the shortest tour that visits all points in the graph. Here we solve it using a mixed-integer programming model that only states that every point has to be visited once, which can result in multiple sub-tours instead of a single one. There are exponentially many of these sub-tours, so it would be very computational expensive to add them all from the beginning. But instead, we iteratively remove the sub-tours that occur by adding additional constraints to the model that removes them.

Disclaimer: All optimization code is made by https://www.gurobi.com/ . I only made some minor tweaks and added the visualization layer

Solving TSP using subtour elimination constraints

About

Animation of solving the traveling salesman problem to optimality using mixed-integer programming and iteratively eliminating sub tours

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages