TSVPS

Python script to solve a NP-hard problem in combinatorial optimization similar to the Traveling-Salesman Problem for a specific dataset that can be connected to the MapBox API. This algorithm uses the Miller–Tucker–Zemlin formulation approach.

Getting Started

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.

Prerequisites

You will need Gurobi Optimization library, you can try it out with a free trial here.

https://www.gurobi.com/free-trial/

Running

The published script comes ready to run with automatic generation of its dataset.

py main.py

Configuration

Further configuration can be achieved by adding a MapBox API Key and enabling XRouter in the router module.

Built With

• Gurobi - Python optimization library
• MapBox - Map & Location API

Authors

• @nbcl - Python Algorithm & Mathematical Optimization Model

• Matías Fuentealba - Mathematical Optimization Model

• Sebastián Benitez - Mathematical Optimization Model

• Mauricio Alvarez - Mathematical Optimization Model

• Felipe Machuca - Mathematical Optimization Model

License

This project is licensed under the MIT License - see the LICENSE.md file for details