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

Overview

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

This repository contains code released by Google Research.

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