This project implements the Simplex algorithm in Python to solve linear programming problems. The algorithm is designed to minimize a linear objective function, subject to linear equality constraints, by iterating through the vertices of the feasible region.
In this example, the code is applied to maximize profit for a farmer by determining the optimal allocation of land for growing Wheat and Barley, while taking into account resource constraints such as available labor, land, and other inputs.
- Python 3.x
- NumPy: The algorithm requires numpy for efficient matrix and vector computations.
Install dependencies using:
pip install numpy
The code is flexible and can be extended to solve other types of linear programming problems by modifying the input matrices and objective function.
Feel free to explore the code, modify it for other linear programming problems, and see how the Simplex algorithm finds optimal solutions.