Software Tools

The research leverages some tools to formulate and solve convex optimization problems. They provide a range of algorithms and solvers for various types of convex optimization problems, and allow users to work with the problem in a natural syntax that is easy to understand and manipulate. CVXPY is a Python-based modeling language for convex optimization problems. It allows users to create and operate problem variables and functions, then solve them using the state-of-the-art solvers. CVXOPT is a Python library for convex optimization. It provides a range of algorithms for solving convex optimization problems, including linear programming, quadratic programming, and semidefinite programming. PICOS is a Python-based API for convex optimization problems. It is similar to CVXPY, but it is designed to work with a wider range of solvers, including both open-source and commercial solvers. CVX is a Matlab-based modeling language for convex optimization problems. It is similar to CVXPY but can be integerated with native Matlab codebase.

Python

Packages

• CVXPY https://www.cvxpy.org/
• CVXOPT https://cvxopt.org/
• PICOS https://picos-api.gitlab.io/picos/

MATLAB

Packages

• CVX http://cvxr.com/cvx/download/