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.
The notebooks are developed with:
- Python 3
- Numpy
- SciPy
- Pandas
- CVXOPT
- CVXPY
These libraries can be easily installed using Anaconda and Pip.
- Activity Level Problem: Solution to a trivial economic activity level problem.
- Illumination Problem: Approximate and exact solutions for a toy example about how to choose the bounded power of lamps to illuminate a indoor space.
- Doubly Stochastic Approximation: How to find the closest doubly stochastic matrix from a given arbitrary matrix.
- Complex Least Norm: The classical least norm problem in the complex domain.
- Minimum Fuel Optimal Control: Minimization of fuel consuption in a simple dynamic linear system.
- Portfolio Optimization: Risk-minimization and risk-return trade-off curves on the classical portfolio optimization problem.