WARNING: This package is currently in development, and is not operationnal yet.
This is a Julia implementation of the Stochastic Dual Dynamic Programming (SDDP) algorithm. It is built upon JuMP
SDDP is an algorithm to solve multistage stochastic optimization problems. It return bounds on the value of the optimization problem and approximation of Bellman function that are used to derive an optimal solution.
These problems are modelled with:
-
stage-wise independent discrete noise
-
Linear dynamic
-
Linear or piecewise linear cost
This algorithm could be applied to the following examples:
-
Dams valley management
-
Newsvendor testcase
The documentation will be soon updated to explain how this algorithm work.
Pkg.clone("https://github.com/leclere/StochDynamicProgramming.jl.git")
IJulia Notebooks will be provided to explain how this package work.
The documentation is built with Sphinx, so ensure that this package is installed:
sudo apt-get install python-sphinx
To build the documentation:
cd doc
make html