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Linear programming (LP) is a mathematical technique used to optimize a linear objective function, subject to linear equality and inequality constraints. It is widely used in various fields such as economics, engineering, and military applications. Python offers several libraries to solve linear programming problems, including SciPy and PuLP.
Using SciPy for Linear Programming
SciPy is a general-purpose library for scientific computing in Python. It includes the scipy.optimize.linprog function, which can solve linear programming problems. Here's an example of how to use it:
from scipy.optimize import linprog# Define the coefficients of the objective functionc = [-1, -2]# Define the inequality constraints (left-hand side)A_ub = [[2, 1], [-4, 5], [1, -2]]# Define the inequality constraints (right-hand side)b_ub = [20, 10, 2]# Define the equality constraints (left-hand side)A_eq = [[-1, 5]]# Define the equality constraints (right-hand side)b_eq = [15]# Define the bounds for each variablex_bounds = (0, float("inf"))y_bounds = (0, float("inf"))# Solve the linear programming problemresult = linprog(c, A_ub=A_ub, b_ub=b_ub, A_eq=A_eq, b_eq=b_eq, bounds=[x_bounds, y_bounds], method='revised simplex')# Print the resultsprint("Optimal value:", result.fun)print("Optimal solution:", result.x)Copied!âś•Copy Python for Linear Programming: A Beginner's Guide
Jun 11, 2025 · Get started with linear programming in Python with this beginner's guide, covering the basics of LP, Python libraries, and practical examples
Introduction to Linear Programming in Python - Towards Data Science
See more on towardsdatascience.comIn Python, there are different libraries for linear programming such as the multi-purposed SciPy, the beginner-friendly PuLP, the exhaustive Pyomo, and many others. Today, we are going to use Google OR-Tools, which is quite user-friendly, comes with several prepackaged solvers, and has by far the most stars on GitHub. If the installation doesn't …Linear Programming: Solving Real-World Optimization Problems
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