Due to difficulty installing pyconcorde, we used Gurobi's method for solving TSP, which is publicly available at https://www.gurobi.com/resource/traveling-salesman-problem/ , and it assisted us in finding the best answers.

Simply put, by. We used this way to install the "gurobipy" library with the command percent pip install gurobipy.

We tried writing a few parts of code from scratch because of the problem's complexity, but due to time constraints, we used references from the GitHub repository of the person who implemented the paper “Learning to Solve NP-Complete Problems -- A Graph Neural Network for the Decision TSP" by M. Prates, P. Avelar, H. Lemos, L. Lamb and M. Vardi “ and the link to their repository is https://github.com/machine-reasoning-ufrgs/TSP-GNN

Traveling Salesman Problem - Jupyter Notebook Modeling Example

In this traveling salesman problem, the goal is to find the shortest possible route that visits each city once and returns to the original city.