DualSDDP implements the Dual SDDP algorithm for multistage stochastic linear problems with stagewise independent uncertainty, allowing for polyhedral risk measures such as Expectation-AV@R. The theory is developped in https://arxiv.org/abs/2107.10930.
It also implements, for comparison:
- A primal SDDP algorithm
- with outer approximations of the value function, and
- stochastic sampling in the scenario tree.
- a deterministic DDP algorithm
- with inner and outer approximations for the value function, and
- worst-gap selection in the scenario tree.
- Create a module
M
, of typeMSLBO
, containing the problem data; - Determine the number of stages of the problem;
- Choose the E-AV@R parameters and create builder functions (primal or dual)
using
mk_primal_avar
andmk_copersp_avar
(respectively); - Set the LP solver for subproblems;
- Set the initial value;
- Set the number of iterations of the algorithm;
- call
primalsolve
,dualsolve
orproblem_child_solve
.
The examples
directory contains both "one shot" examples (in subdirectories),
as well as Config.jl
batches and configs.
The first time you use the examples directory, you'll have to instantiate it.
The fastest way of doing so is using Pkg
commands (in the examples
directory):
pkg> activate .
pkg> dev ..
This will use the Project.toml
we provide,
then the current checkout for the DualSDDP
package,
and finally resolve all packages.
In so doing, it will also require that the Gurobi
package is installed,
which was used for some of the examples.
If that is not desired, one can remove it from the Packages.toml
file,
or simply issue pkg> rm Gurobi
.