Blog

MILP Ch.10: Approach 1 Branch And Bound Methods For Solving MIP Problems Part II

Transform your complex business challenge into an optimized plan of action—powered by Gurobi’s world-leading solver technology.

Blog

MILP Ch.10: Approach 1 Branch And Bound Methods For Solving MIP Problems Part II

Transform your complex business challenge into an optimized plan of action—powered by Gurobi’s world-leading solver technology.

Blog

MILP Ch.10: Approach 1 Branch And Bound Methods For Solving MIP Problems Part II

Transform your complex business challenge into an optimized plan of action—powered by Gurobi’s world-leading solver technology.

Access the Jupyter Notebook Modeling Notebooks in this course

Click on the links below to access the examples in Google Colab, which is a free, online Jupyter Notebook environment that allows you to write and execute Python code through your browser. Since these are now in Google Colab, they look might differ slightly from the tutorials. Please see 'How to Run the Jupyter Notebook Modeling Examples' for instructions below.

  1. RAP Problem 001 Jupyter Notebook

  2. RAP Problem 002 Jupyter Notebook

  3. RAP Problem 003 Jupyter Notebook

View All Tutorial Chapters

  1. Chapter 1: Why Mixed-Integer Programming (MIP)

  2. Chapter 2: Resource Assignment Problem

  3. Chapter 3: Linear Programming Formulations

  4. Chapter 4: Linear Programming Formulation With Gurobi Python API

  5. Chapter 5: Jupyter Notebook-1 Resource Assignment Problem Formulation

  6. Chapter 6: Perfect Formulation Resource Assignment Problem (RAP)

  7. Chapter 7: Jupyter Notebook-2 Perfect Formulation Resource Assignment Problem

  8. Chapter 8: Methods for Solving MIP Problems

  9. Chapter 9: Approach 1 Branch And Bound Methods For Solving MIP Problems Part 1

  10. Chapter 10: Approach 1 Branch And Bound Methods For Solving MIP Problems Part II

  11. Chapter 11: Approach 2 Cutting Planes Methods For Solving MIP Problems

  12. Chapter 12: Jupyter Notebook-3 - Why MIP Is Better than Simple Heuristics

  13. Summary & Conclusion: Mixed Integer Linear Programming

How to Run the Jupyter Notebook Modeling Example

  1. To run the example the first time, choose “Runtime” and then click “Run all”.

  2. All the cells in the Jupyter Notebook will be executed.

  3. The example will install the gurobipy package, which includes a limited Gurobi license that allows you to solve small models.

  4. You can also modify and re-run individual cells.

  5. For subsequent runs, choose “Runtime” and click “on “Restart and run all”.

  6. 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.

Start Solving with Gurobi

Try Gurobi on your own optimization models and see how it performs on real decision problems.

Start Solving with Gurobi

Try Gurobi on your own optimization models and see how it performs on real decision problems.

Start Solving with Gurobi

Try Gurobi on your own optimization models and see how it performs on real decision problems.