Facility Location Problem

Facility Location Problem - Jupyter Notebook Modeling Example - Gurobi

Facility location problems can be commonly found in many industries, including logistics and telecommunications. In this example, we’ll show you how to tackle a facility location problem that involves determining the number and location of warehouses that are needed to supply a group of supermarkets. We’ll demonstrate how to construct a mixed-integer programming (MIP) model of this problem, implement this model in the Gurobi Python API, and then use the Gurobi Optimizer to find an optimal solution.

This modeling example is at the beginner level, where we assume that you know Python and that you have some knowledge about building mathematical optimization models.

 


 

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. 

 

Facility Location Problem

 

 

How to Run the 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 “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.


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