Closed odow closed 1 year ago
Hello,
So I tried it and I got a different error message this time:
Thanks
I should have tested :)
On Sun, 9 Jul 2023, 7:59 am Bikey Seranilla, @.***> wrote:
Hello,
So I tried it and I got a different error message this time: [image: Screenshot 2023-07-09 at 16 58 01] https://user-images.githubusercontent.com/37835698/252152745-66488019-4048-44ad-b998-4c001264334f.png
Thanks
— Reply to this email directly, view it on GitHub https://github.com/odow/SDDP.jl/pull/639#issuecomment-1627739046, or unsubscribe https://github.com/notifications/unsubscribe-auth/AB6MQJIU6HIMCZFWCZ25NX3XPLBMTANCNFSM6AAAAAA2DRPFYU . You are receiving this because you authored the thread.Message ID: @.***>
Try now
Hi,
I tried it and now a new one:
Actually wait. Let me test this properly
I'm not really sure what the problem is. I need to debug some more, but I won't be online today
No worries, Oscar. Thanks for the help. I will just wait when you're back. :)
try now
julia> using SDDP
julia> model = SDDP.MSPFormat.read_from_file("/Users/Oscar/Downloads/Hydro_Simple/Hydro_Simple")
A policy graph with 12 nodes.
Node indices: 4, ..., 3
julia> import HiGHS
julia> set_optimizer(model, HiGHS.Optimizer)
julia> SDDP.train(model; iteration_limit = 3)
-------------------------------------------------------------------
SDDP.jl (c) Oscar Dowson and contributors, 2017-23
-------------------------------------------------------------------
problem
nodes : 12
state variables : 1
scenarios : 8.10000e+01
existing cuts : false
options
solver : serial mode
risk measure : SDDP.Expectation()
sampling scheme : SDDP.InSampleMonteCarlo
subproblem structure
VariableRef : [6, 6]
AffExpr in MOI.EqualTo{Float64} : [2, 2]
VariableRef in MOI.GreaterThan{Float64} : [5, 5]
VariableRef in MOI.LessThan{Float64} : [1, 2]
numerical stability report
matrix range [1e+00, 1e+00]
objective range [1e+00, 2e+02]
bounds range [2e+02, 1e+06]
rhs range [5e+01, 2e+02]
-------------------------------------------------------------------
iteration simulation bound time (s) solves pid
-------------------------------------------------------------------
1 1.500000e+04 -2.500000e+03 7.572103e+00 16 1
2 1.750000e+04 6.666667e+03 8.615028e+00 356 1
3 7.500000e+03 7.916667e+03 8.632101e+00 372 1
-------------------------------------------------------------------
status : iteration_limit
total time (s) : 8.632101e+00
total solves : 372
best bound : 7.916667e+03
simulation ci : 1.333333e+04 ± 5.889067e+03
numeric issues : 0
-------------------------------------------------------------------
Merging since this seems okay from my end. Hard to tell without other examples.
Hi Oscar,
My apologies for the later reply. I was travelling to Davis for the conference and missed the emails.
I confirm that it worked with the last error I encountered. I will be trying all the rest of the other synthetic problems with it the coming days. Will keep you updated.
Thanks again!
@bonnkleiford: I haven't tested, but here's a fix for you
initial_value
error.