Refinery Planning Problem
In this example, we’ll demonstrate how you can use mathematical optimization to optimize the output of a refinery. You’ll learn how to generate an optimal production plan that maximizes total profit, while taking into account production capacity and other restrictions.
More information on this type of model can be found in example # 6 of the fifth edition of Modeling Building in Mathematical Programming by H. P. Williams on pages 258 and 306 – 310.
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 should have some knowledge about building mathematical optimization models.
Access the Jupyter Notebook Modeling Example
Click on the link 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.
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.
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