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