Technician Routing and Scheduling Problem

In this Technician Routing and Scheduling Problem (TRSP), you will formulate a multi-depot vehicle routing problem with the Gurobi Python API

 

Technician Routing & Scheduling Problem

In this Technician Routing and Scheduling Problem, you will learn how to formulate a multi-depot vehicle routing problem with time windows constraints using the Gurobi Python API. To fully understand the content of this notebook, the reader should be familiar with object-oriented-programming.

This modeling example is at the intermediate level, where we assume that you know Python and are familiar with the Gurobi Python API. In addition, you have some knowledge about building mathematical optimization models.

 


 

Request a Gurobi Evaluation License or Free Academic License

Modeling examples are coded using the Gurobi Python API in Jupyter Notebook. In order to use the Jupyter Notebooks, you must have a Gurobi License. If you do not have a license, you can request an Evaluation License as a Commercial User or download a free license as an Academic User.

 

Commercial Users: Free Evaluation Version Academic Users: Free Academic Version

 


 

Access the Jupyter Notebook Modeling Example

Click on the button below to be directed to GitHub where you can download the repository for the Cell Tower Coverage Jupyter Notebook modeling example.

 

Technician Routing and Scheduling Problem

 


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