Convex Optimization in Python using CVXPY and PULP 2023 [Step by Step]

Convex optimization (cvxpy) and linear programming optimization (pulp) in python are demonstrated for solving linear and nonlinear programming objective function, subject to general constraints. EXCEL SOLVER IN PYTHON. Click "Show more" to learn more ?:

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CVXPY is a domain-specific language for convex optimization embedded in Python. It allows the user to express convex optimization problems in a natural syntax that follows the math, rather than in the restrictive standard form required by solvers. CVXPY has been used in hundreds of research projects and by Fortune 500 companies.

Pulp is a Python library for linear optimization. There are many libraries in the Python ecosystem for this kind of optimization problems. PuLP is an open-source linear programming (LP) package that largely uses Python syntax and comes packaged with many industry-standard solvers. It also integrates nicely with a range of open source and commercial LP solvers. (Source: towardsdatascience.com, https://bit.ly/2UDi0TF)

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⌚??????????:
Introduction (0:00)
Get FREE access to my Google Drive (0.50)
What is Convex Optimization (1:38)
pulp, cvxpy, scipy.optimize (8:00)
Pulp (9:17)
cvxpy (16:30)

I used Anaconda jupyterlab for this code. It is an amazing platform for beginners.

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