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Ensure compatibility with Plasmo 0.5.4 and static partition example #5

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Ensure compatibility with Plasmo 0.5.4 and static partition example #5

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3127afa
Add optimal control example with static partition example
tso-martin Jan 10, 2024
fbd99bb
Update value and dual retrieval to Plasmo 0.5.4
tso-martin Jan 10, 2024
20454f0
Add verbosity and example
tso-martin Jan 23, 2024
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60 changes: 60 additions & 0 deletions examples/optimal_control_static_partition.jl
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Original file line number Diff line number Diff line change
@@ -0,0 +1,60 @@
# Example demonstrating the use of overlap to solve a long horizon control problem
# Uses a static partitioning of the graph (useful if KaHyPar is not available)
using Plasmo, Ipopt
using SchwarzOpt

T = 200 # number of time points
d = sin.(1:T) # a disturbance vector
imbalance = 0.1 # partition imbalance
distance = 2 # expand distance
n_parts = 10 # number of partitions

# Create the model (an optigraph)
graph = OptiGraph()

@optinode(graph, state[1:T])
@optinode(graph, control[1:(T-1)])

for (i, node) in enumerate(state)
@variable(node, x)
@constraint(node, x >= 0)
@objective(node, Min, x^2) #- 2*x*d[i])
end
for node in control
@variable(node, u)
@constraint(node, u >= -1000)
@objective(node, Min, u^2)
end
n1 = state[1]
@constraint(n1, n1[:x] == 0)

for i in 1:(T-1)
@linkconstraint(graph, state[i][:x] + control[i][:u] + d[i] == state[i+1][:x])
end

hypergraph, hyper_map = hyper_graph(graph) # create hypergraph object based on graph
# Create an equally sized partition based on the number of time points and number of partitions.
N_node = 2 * T - 1
partition_vector = repeat(1:n_parts, inner=N_node ÷ n_parts)
remaining = N_node % n_parts
if remaining > 0
partition_vector = [partition_vector; repeat(1:remaining)]
end

# apply partition to graph
partition = Partition(hypergraph, partition_vector, hyper_map)
apply_partition!(graph, partition)

# calculate subproblems using expansion distance
subs = subgraphs(graph)
expanded_subgraphs = Plasmo.expand.(graph, subs, distance)
sub_optimizer = optimizer_with_attributes(Ipopt.Optimizer, "print_level" => 0)

# optimize using schwarz overlapping decomposition
optimizer = SchwarzOpt.optimize!(
graph;
subgraphs=expanded_subgraphs,
sub_optimizer=sub_optimizer,
max_iterations=100,
mu=100.0,
)
8 changes: 4 additions & 4 deletions src/optimizer.jl
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@tso-martin: Are the value and dual functions not working as expected when given the graph as an argument in Plasmo v0.5.4? Removing the graph argument should cause issues when running on multiple threads.

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I get errors for each thread, when value and dual are called with the graph argument. Example:

 nested task error: KeyError: key MOI.VariableIndex(37) not found
    Stacktrace:
      [1] getindex
        @ xxx\.julia\packages\MathOptInterface\yczX1\src\Utilities\CleverDicts.jl:164 [inlined]
      [2] getindex
        @ xxx\.julia\packages\MathOptInterface\yczX1\src\Utilities\copy\index_map.jl:64 [inlined]
      [3] get(node_pointer::Plasmo.NodePointer, attr::MathOptInterface.VariablePrimal, idx::MathOptInterface.VariableIndex)
        @ Plasmo xxx\SchwarzTryout\dev\Plasmo\src\moi_backend_node.jl:287
      [4] value(graph::OptiGraph, var::VariableRef)
        @ Plasmo xxx\SchwarzTryout\dev\Plasmo\src\optigraph.jl:514
      [5] (::SchwarzOpt.var"#25#27"{OptiGraph})(::Pair{Int64, VariableRef})
        @ SchwarzOpt .\none:0
      [6] iterate(g::Base.Generator, s::Vararg{Any})
        @ Base .\generator.jl:47 [inlined]
      [7] _all(f::Base.var"#384#386", itr::Base.Generator{Dict{Int64, VariableRef}, SchwarzOpt.var"#25#27"{OptiGraph}}, ::Colon)
        @ Base .\reduce.jl:1287
      [8] all
        @ .\reduce.jl:1283 [inlined]
      [9] Dict(kv::Base.Generator{Dict{Int64, VariableRef}, SchwarzOpt.var"#25#27"{OptiGraph}})
        @ Base .\dict.jl:111
     [10] _do_iteration(subproblem_graph::OptiGraph)
        @ SchwarzOpt xxx\SchwarzTryout\dev\SchwarzOpt\src\optimizer.jl:305
     [11] macro expansion
        @ xxx\SchwarzTryout\dev\SchwarzOpt\src\optimizer.jl:414 [inlined]
     [12] (::SchwarzOpt.var"#45#threadsfor_fun#32"{SchwarzOpt.var"#45#threadsfor_fun#31#33"{…}})(tid::Int64; onethread::Bool)
        @ SchwarzOpt .\threadingconstructs.jl:214
     [13] #45#threadsfor_fun
        @ SchwarzOpt .\threadingconstructs.jl:181 [inlined]
     [14] (::Base.Threads.var"#1#2"{SchwarzOpt.var"#45#threadsfor_fun#32"{SchwarzOpt.var"#45#threadsfor_fun#31#33"{…}}, Int64})()
        @ Base.Threads .\threadingconstructs.jl:153

Removing the graph argument worked fine in multiple threads

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Interesting, that is definitely a bug. Without the graph argument, value grabs the last solution the node was used in. So it's possible it takes the wrong one if there are multiple subgraphs that use it. I will take a look at this and get a fix out. Thanks for checking into this!

Original file line number Diff line number Diff line change
Expand Up @@ -302,8 +302,8 @@ function _do_iteration(subproblem_graph::OptiGraph)
x_sub = subproblem_graph.ext[:x_map] # primal variables to update
l_sub = subproblem_graph.ext[:l_map] # dual variables to update

xk = Dict(key => value(subproblem_graph, val) for (key, val) in x_sub)
lk = Dict(key => dual(subproblem_graph, val) for (key, val) in l_sub)
xk = Dict(key => value(val) for (key, val) in x_sub)
lk = Dict(key => dual(val) for (key, val) in l_sub)

return xk, lk
end
Expand All @@ -327,7 +327,7 @@ function _calculate_primal_feasibility(optimizer)
node = optinode(term)
graph = optimizer.node_subgraph_map[node]
subproblem_graph = optimizer.expanded_subgraph_map[graph]
val += coeff * value(subproblem_graph, term)
val += coeff * value(term)
end
push!(prf, val - linkcon.set.value)
end
Expand Down Expand Up @@ -457,7 +457,7 @@ function optimize!(optimizer::Optimizer)
JuMP.set_start_value.(
Ref(subproblem),
all_variables(subproblem),
value.(Ref(subproblem), all_variables(subproblem)),
value.(all_variables(subproblem)),
)
end
end
Expand Down
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