justinjiajia / cvx-nb

IPython Notebooks of Convex Optimization Problems

cvx-nb: Convex Optimization Notebooks

This repository contains a set of IPython Notebooks with solution for interesting optimization problems. Some of the problems and data are from the book, Convex Optimization by Stephen Boyd and Lieven Vandenberghe.

Requirements:

The notebooks are developed with:

• Python 3
• Numpy
• SciPy
• Pandas
• CVXOPT
• CVXPY

These libraries can be easily installed using Anaconda and Pip.

Notebooks

1. Activity Level Problem: Solution to a trivial economic activity level problem.
2. Illumination Problem: Approximate and exact solutions for a toy example about how to choose the bounded power of lamps to illuminate a indoor space.
3. Doubly Stochastic Approximation: How to find the closest doubly stochastic matrix from a given arbitrary matrix.
4. Complex Least Norm: The classical least norm problem in the complex domain.
5. Minimum Fuel Optimal Control: Minimization of fuel consuption in a simple dynamic linear system.
6. Portfolio Optimization: Risk-minimization and risk-return trade-off curves on the classical portfolio optimization problem.