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dual bound of tree search is dual bound of open nodes #598

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merged 3 commits into from
Sep 8, 2021
Merged

dual bound of tree search is dual bound of open nodes #598

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35cef0c
dual bound of tree search is dual bound of open nodes
guimarqu Sep 8, 2021
1052a53
Merge branch 'master' into fix_db_of_treesearch
guimarqu Sep 8, 2021
b1a7db9
I screwed up the merge
guimarqu Sep 8, 2021
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30 changes: 7 additions & 23 deletions src/Algorithm/treesearch.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -75,19 +75,15 @@ push!(tree::SearchTree, node::Node) = DS.enqueue!(tree.nodes, node, getnodevalue
popnode!(tree::SearchTree) = DS.dequeue!(tree.nodes)
nb_open_nodes(tree::SearchTree) = length(tree.nodes)

"""
Data used by the tree search algorithm while running. Destroyed after each run.
"""
mutable struct TreeSearchRuntimeData{Sense}
"Data used by the tree search algorithm while running. Destroyed after each run."
mutable struct TreeSearchRuntimeData
primary_tree::SearchTree
max_primary_tree_size::Int64
secondary_tree::SearchTree
tree_order::Int64
optstate::OptimizationState
exploitsprimalsolutions::Bool
Sense::Type{<:Coluna.AbstractSense}
conquer_units_to_restore::UnitsUsage
worst_db_of_pruned_node::DualBound{Sense}
end

function TreeSearchRuntimeData(algo::TreeSearchAlgorithm, reform::Reformulation, input::OptimizationInput)
Expand All @@ -100,12 +96,9 @@ function TreeSearchRuntimeData(algo::TreeSearchAlgorithm, reform::Reformulation,
collect_units_to_restore!(conquer_units_to_restore, algo.conqueralg, reform)
# divide algorithms are always manager algorithms, so we do not need to restore storage units for them

Sense = getobjsense(reform)

tsdata = TreeSearchRuntimeData{Sense}(
tsdata = TreeSearchRuntimeData(
SearchTree(algo.explorestrategy), algo.opennodeslimit, SearchTree(DepthFirstStrategy()),
1, treestate, exploitsprimalsols, Sense, conquer_units_to_restore,
-DualBound{Sense}()
1, treestate, exploitsprimalsols, conquer_units_to_restore
)
master = getmaster(reform)
push!(tsdata, RootNode(master, getoptstate(input), store_records!(reform), algo.skiprootnodeconquer))
Expand Down Expand Up @@ -305,10 +298,9 @@ function run_divide_algorithm!(
return
end

function updatedualbound!(data::TreeSearchRuntimeData)
function updatedualbound!(data::TreeSearchRuntimeData, reform::Reformulation)
treestate = getoptstate(data)
bound_value = getvalue(get_ip_primal_bound(treestate))
worst_bound = DualBound{data.Sense}(bound_value)
worst_bound = DualBound(reform, getvalue(get_ip_primal_bound(treestate)))
for (node, _) in getnodes(data.primary_tree)
db = get_ip_dual_bound(getoptstate(node))
if isbetter(worst_bound, db)
Expand All @@ -323,10 +315,6 @@ function updatedualbound!(data::TreeSearchRuntimeData)
end
end

if isbetter(worst_bound, data.worst_db_of_pruned_node)
worst_bound = data.worst_db_of_pruned_node
end

set_ip_dual_bound!(treestate, worst_bound)
return
end
Expand All @@ -349,15 +337,11 @@ function run!(
if nodestatus == OPTIMAL || nodestatus == INFEASIBLE ||
ip_gap_closed(node.optstate, rtol = algo.opt_rtol, atol = algo.opt_atol)
println("Node is already conquered. No children will be generated.")
db = get_ip_dual_bound(node.optstate)
if isbetter(tsdata.worst_db_of_pruned_node, db)
tsdata.worst_db_of_pruned_node = db
end
elseif nodestatus != TIME_LIMIT
run_divide_algorithm!(algo, env, tsdata, reform, node)
end

updatedualbound!(tsdata)
updatedualbound!(tsdata, reform)

remove_records!(node.recordids)
# we delete solutions from the node optimization state, as they are not needed anymore
Expand Down
25 changes: 25 additions & 0 deletions test/full_instances_tests.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -98,6 +98,31 @@ function generalized_assignment_tests()
@test CLD.GeneralizedAssignment.print_and_check_sol(data, model, x)
end


@testset "gap - node limit" begin
data = CLD.GeneralizedAssignment.data("mediumgapcuts3.txt")

coluna = JuMP.optimizer_with_attributes(
CL.Optimizer,
"params" => CL.Params(
solver = ClA.TreeSearchAlgorithm(
maxnumnodes = 5
)
),
"default_optimizer" => GLPK.Optimizer
)

model, x, dec = CLD.GeneralizedAssignment.model(data, coluna)
BD.objectiveprimalbound!(model, 2000.0)
BD.objectivedualbound!(model, 0.0)

JuMP.optimize!(model)

@test JuMP.objective_bound(model) ≈ 1547.3889
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Are you sure that this test is reproducible? Branching decisions may be different depending on the fractional solution (which depends on the LP solver).

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Yes, I'm not satisfied with this test, I'm leaving it until we think about better tests.

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If it fails for some reason, we can replace @test by @test_broken

@test JuMP.termination_status(model) == MathOptInterface.OTHER_LIMIT
return
end

@testset "gap - ColGen max nb iterations" begin
data = CLD.GeneralizedAssignment.data("smallgap3.txt")

Expand Down