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Jupyter Notebook Model

Milk Collection Problem

This is an example of a capacitated vehicle routing problem and it is formulated as a binary optimization problem using the Gurobi Python API and solved with the Gurobi Optimizer
 

In this example, you’ll discover how mathematical optimization can be leveraged to solve a capacitated vehicle routing problem: the Milk Collection Problem. With only one tanker truck with limited capacity, you will need to determine the best possible route for the tanker to take to collect milk every day from a set of farms. It’s a complicated problem to solve, but mathematical optimization will help show you the way!

This model is example 23 from the fifth edition of Model Building in Mathematical Programming by H. Paul Williams on pages 278-281 and 336-337.

This modeling example is at the advanced level, where we assume that you know Python and the Gurobi Python API and you have advanced knowledge of building mathematical optimization models. Typically, the objective function and/or constraints of these examples are complex or require advanced features of the Gurobi Python API.

Access the Jupyter Notebook Modeling Example

Click on the button below to access the example in Google Colab, which is a free, online Jupyter Notebook environment that allows you to write and execute Python code through your browser. 

Milk Collection Problem

How to Run the Jupyter Notebook Modeling Example

  • To run the example the first time, choose “Runtime” and then click “Run all”.
  • All the cells in the Jupyter Notebook will be executed.
  • The example will install the gurobipy package, which includes a limited Gurobi license that allows you to solve small models.
  • You can also modify and re-run individual cells.
  • For subsequent runs, choose “Runtime” and click “on “Restart and run all”.
  • The Gurobi Optimizer will find the optimal solution of the modeling example.

Check out the Colab Getting Started Guide for full details on how to use Colab Notebooks as well as create your own.