5 votes
Accepted

Multi period inventory / reordering MILP in PULP

Some comments on your model: you can remove constraints $\#1$ and $\#2$, as you have already defined the variables as non negative the problem is infeasible, because the inventory is not a variable, ...
Kuifje's user avatar
  • 13.2k
3 votes

multi stage stochastic programming algorithm

If your question is “Are nested Benders decomposition or progressive hedging more efficient than solving a very large-scale monolithic formulation (sometimes called ‘deterministic equivalent’) with ...
Tim Varelmann's user avatar
3 votes
Accepted

Can stochastic dual dynamic programming algorithm (or any variant of it) handle multi-stage optimization problems with here-and-now uncertainty nodes?

Here-and-now uncertainty problems, which are also known as Decision-Hazard problems, are problems that decisions need to be made before the revelation of uncertain parameters on each node of a ...
Penghui Guo's user avatar
2 votes
Accepted

In the context of risk-averse multi-stage programming and scheduling of resources consumption, is it always optimum to most risky resource first?

No. It depends on the data and how you quantify risk. Consider two products A and B with costs: t=1 t=2 A ...
Oscar Dowson's user avatar
2 votes
Accepted

How can I write the output stream of SDDP.jl into an excel file?

Use the log_file keyword argument to train: https://odow.github.io/SDDP.jl/stable/apireference/#SDDP.train Or, after training, ...
Oscar Dowson's user avatar
2 votes
Accepted

Is stochastic dual dynamic programming (SDDP) a deterministic solution algorithm or does it have a stochastic component to it?

It depends on the implementation. Irrespective of whether the model has one scenario or many, it's possible to code an implementation of SDDP that is deterministic in the sense that it will return the ...
Oscar Dowson's user avatar
1 vote
Accepted

Connected optimization problems

If I understand the OP correctly, this is an example of a bi-level optimization problem. It can be formulated as follows: \begin{align} \min_{w, d} \quad & g(x)\\ \text{s.t.} \quad & w ...
mtanneau's user avatar
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