elena-ecn / benders-decomposition

Bender's decomposition for solving Mixed Integer Linear Programs (MILPs).

Benders decomposition

Implementation of the Benders decomposition method for solving Mixed-Integer Linear Programs (MILPs) of the following form:

$$ \begin{aligned} \min_{x,y} \quad & c^Tx + f^Ty \\\ \textrm{s.t.} \quad & Ax + By \ge b\\\ & Dy \ge d \\\ & x \ge 0 \\\ & y \ge 0 \\\ & y \text{ integer} \end{aligned} $$

About

The idea behind Benders decomposition is to take advantage of the problem's block structure and decompose it to simpler problems (divide-and-conquer technique) in order to solve very large optimization problems efficiently. The way this method works is by dividing the variables into two subsets such that a Master problem (MP) is solved over the first set of variables and a sub-problem (SP) is solved over the second set of variables given the solution of the Master problem. It is an iterative method that utilizes duality to solve the sub-problems and at each iteration either adds an optimality or a feasibilty cut to the MP, until the upper and lower bounds of the objective function converge.

Example

The following problem can be written in the above form and thus solved by this solver.

$$ \begin{aligned} \min_{x,y} \quad & -4x-3y-5z \\\ \textrm{s.t.} \quad & -2x-3y-z \ge -12\\\ & -2x-y-3z \ge -12 \\\ & -z \ge -20 \\\ & x,y,z \ge 0 \\\ & z \text{ integer} \end{aligned} $$

The algorithm's convergence for the given example is shown in the following figure:

Convergence plot

Technologies

The project was created with:

• Python 3.9
• cvxpy 1.2.1
• matplotlib 3.6.2
• numpy 1.23.4
• seaborn 0.11.2

Installation

To use this project, install it locally via:

git clone https://github.com/elena-ecn/benders-decomposition.git

The dependencies can be installed by running:

pip install -r requirements.txt

Note: This project is utilizing the MOSEK solver which requires a license to use. However, you can use any other compatible solver to solve the optimization problems. See here for more information.

To execute the code, run:

python3 main.py

License

The contents of this repository are covered under the MIT License.