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Merge pull request #112 from jump-dev/bl/constrained_variables
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Don't create dual variables of constrained variables
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@guilhermebodin
guilhermebodin authored Oct 20, 2021
2 parents 97668f5 + d551292 commit b958e5a
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4 changes: 2 additions & 2 deletions Project.toml
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Original file line number Diff line number Diff line change
@@ -1,15 +1,15 @@
name = "Dualization"
uuid = "191a621a-6537-11e9-281d-650236a99e60"
authors = ["guilhermebodin <[email protected]>"]
version = "0.3.6"
version = "0.3.5"

[deps]
JuMP = "4076af6c-e467-56ae-b986-b466b2749572"
MathOptInterface = "b8f27783-ece8-5eb3-8dc8-9495eed66fee"

[compat]
JuMP = "0.21"
MathOptInterface = "< 0.9.21"
MathOptInterface = "0.9.20"
julia = "1"

[extras]
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1 change: 1 addition & 0 deletions src/Dualization.jl
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Expand Up @@ -22,6 +22,7 @@ include("supported.jl")
include("dual_names.jl")
include("objective_coefficients.jl")
include("add_dual_cone_constraint.jl")
include("constrained_variables.jl")
include("dual_model_variables.jl")
include("dual_equality_constraints.jl")
include("dualize.jl")
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295 changes: 233 additions & 62 deletions src/MOI_wrapper.jl
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Expand Up @@ -118,43 +118,86 @@ function MOI.supports_constraint(
)
end

function _change_constant(
model,
ci::MOI.ConstraintIndex{<:MOI.ScalarAffineFunction,S},
constant,
idx,
) where {S}
MOI.set(model, MOI.ConstraintSet(), ci, S(constant))
return
end
function _change_constant(
model,
ci::MOI.ConstraintIndex{<:MOI.VectorAffineFunction},
constant,
idx,
)
func = MOI.get(model, MOI.ConstraintFunction(), ci)
constants = copy(func.constant)
constants[idx] = -constant
MOI.modify(model, ci, MOI.VectorConstantChange(constants))
return
end
function MOI.modify(
optimizer::DualOptimizer{T},
::MOI.ObjectiveFunction{MOI.ScalarAffineFunction{T}},
obj_change::MOI.ScalarCoefficientChange{T},
) where {T}
primal_dual_map = optimizer.dual_problem.primal_dual_map
# We must find the constraint corresponding to the variable in the objective
# function and change its coefficient on the constraint.
ci_to_change =
optimizer.dual_problem.primal_dual_map.primal_var_dual_con[obj_change.variable]
sense_change =
MOI.get(optimizer.dual_problem.dual_model, MOI.ObjectiveSense()) ==
MOI.MAX_SENSE ? one(T) : -one(T)
MOI.set(
constant = obj_change.new_coefficient
if MOI.get(optimizer.dual_problem.dual_model, MOI.ObjectiveSense()) ==
MOI.MIN_SENSE
constant = -constant
end
vi = obj_change.variable
if vi in keys(primal_dual_map.constrained_var_idx)
ci_primal, index = primal_dual_map.constrained_var_idx[vi]
ci_dual = primal_dual_map.constrained_var_dual[ci_primal]
if ci_dual === NO_CONSTRAINT
return
end
constant = -constant
else
ci_dual = primal_dual_map.primal_var_dual_con[vi]
index = 1
end
_change_constant(
optimizer.dual_problem.dual_model,
MOI.ConstraintSet(),
ci_to_change,
MOI.EqualTo(sense_change * obj_change.new_coefficient),
ci_dual,
constant,
index,
)
return
end

# TODO add this when constrained variables are implemented
#function MOI.supports_add_constrained_variables(
# optimizer::DualOptimizer{T}, S::Type{MOI.Reals}) where T
# return MOI.supports_constraint(optimizer.dual_problem.dual_model,
# MOI.ScalarAffineFunction{T},
# MOI.EqualTo{T}) # If it was `MOI.Zeros`, we would not need this method as special case of the one below
#end
#function MOI.supports_add_constrained_variables(
# optimizer::DualOptimizer{T}, S::Type{<:MOI.AbstractVectorSet}) where T
# D = _dual_set_type(S)
# if D === nothing
# return false
# end
# return MOI.supports_constraint(optimizer.dual_problem.dual_model,
# MOI.VectorAffineFunction{T}, D)
#end
function MOI.supports_add_constrained_variables(
optimizer::DualOptimizer{T},
S::Type{MOI.Reals},
) where {T}
return MOI.supports_constraint(
optimizer.dual_problem.dual_model,
MOI.ScalarAffineFunction{T},
MOI.EqualTo{T},
)
# If `_dual_set_type(MOI.Reals)` was `MOI.Zeros`, we would not need this method as special case of the one below
end
function MOI.supports_add_constrained_variables(
optimizer::DualOptimizer{T},
S::Type{<:MOI.AbstractVectorSet},
) where {T}
D = _dual_set_type(S)
if D === nothing
return false
end
return MOI.supports_constraint(
optimizer.dual_problem.dual_model,
MOI.VectorAffineFunction{T},
D,
)
end

function MOI.copy_to(dest::DualOptimizer, src::MOI.ModelLike; kwargs...)
# Dualize the original problem
Expand Down Expand Up @@ -221,73 +264,201 @@ function MOI.get(optimizer::DualOptimizer, ::MOI.SolverName)
" attached"
end

function MOI.get(optimizer::DualOptimizer, ::MOI.VariablePrimal, vi::VI)
return -MOI.get(
optimizer.dual_problem.dual_model,
MOI.ConstraintDual(),
get_ci_dual_problem(optimizer, vi),
function _get(
::DualOptimizer{T},
::MOI.AbstractConstraintAttribute,
::MOI.ConstraintIndex{MOI.SingleVariable,MOI.EqualTo{T}},
::MOI.ConstraintIndex{Nothing,Nothing},
) where {T}
return zero(T)
end
function _get(
optimizer::DualOptimizer,
attr::MOI.AbstractConstraintAttribute,
::MOI.ConstraintIndex,
ci::MOI.ConstraintIndex,
)
return MOI.get(optimizer.dual_problem.dual_model, attr, ci)
end
function _get(
optimizer::DualOptimizer{T},
::MOI.AbstractConstraintAttribute,
ci_primal::MOI.ConstraintIndex{MOI.VectorOfVariables,MOI.Zeros},
::MOI.ConstraintIndex{Nothing,Nothing},
) where {T}
n = MOI.output_dimension(
optimizer.dual_problem.primal_dual_map.constrained_var_zero[ci_primal],
)
return zeros(T, n)
end

function _get_at_index(
optimizer::DualOptimizer,
attr::MOI.AbstractConstraintAttribute,
ci_primal::MOI.ConstraintIndex{MOI.SingleVariable},
ci_dual::MOI.ConstraintIndex,
idx,
)
@assert isone(idx)
return _get(optimizer, attr, ci_primal, ci_dual)
end
function _get_at_index(
optimizer::DualOptimizer,
attr::MOI.AbstractConstraintAttribute,
ci_primal::MOI.ConstraintIndex{MOI.VectorOfVariables},
ci_dual::MOI.ConstraintIndex,
idx,
)
return _get(optimizer, attr, ci_primal, ci_dual)[idx]
end

function MOI.get(optimizer::DualOptimizer, ::MOI.VariablePrimal, vi::VI)
primal_dual_map = optimizer.dual_problem.primal_dual_map
if vi in keys(primal_dual_map.constrained_var_idx)
ci_primal, idx = primal_dual_map.constrained_var_idx[vi]
ci_dual = primal_dual_map.constrained_var_dual[ci_primal]
return _get_at_index(
optimizer,
MOI.ConstraintDual(),
ci_primal,
ci_dual,
idx,
)
else
return -MOI.get(
optimizer.dual_problem.dual_model,
MOI.ConstraintDual(),
get_ci_dual_problem(optimizer, vi),
)
end
end

function MOI.get(
optimizer::DualOptimizer,
::MOI.ConstraintDual,
attr::MOI.ConstraintDual,
ci::CI{F,S},
) where {F<:MOI.AbstractScalarFunction,S<:MOI.AbstractScalarSet}
return MOI.get(
optimizer.dual_problem.dual_model,
MOI.VariablePrimal(),
get_vi_dual_problem(optimizer, ci),
)
primal_dual_map = optimizer.dual_problem.primal_dual_map
if ci in keys(primal_dual_map.constrained_var_dual)
ci_dual = primal_dual_map.constrained_var_dual[ci]
if ci_dual === NO_CONSTRAINT
return MOI.Utilities.eval_variables(
primal_dual_map.constrained_var_zero[ci],
) do vi
return MOI.get(
optimizer.dual_problem.dual_model,
MOI.VariablePrimal(),
vi,
)
end
end
set = MOI.get(
optimizer.dual_problem.dual_model,
MOI.ConstraintSet(),
ci_dual,
)
return MOI.get(
optimizer.dual_problem.dual_model,
MOI.ConstraintPrimal(),
ci_dual,
) - MOI.constant(set)
else
return MOI.get(
optimizer.dual_problem.dual_model,
MOI.VariablePrimal(),
get_vi_dual_problem(optimizer, ci),
)
end
end

function MOI.get(
optimizer::DualOptimizer,
::MOI.ConstraintDual,
ci::CI{F,S},
) where {F<:MOI.AbstractVectorFunction,S<:MOI.AbstractVectorSet}
return MOI.get.(
optimizer.dual_problem.dual_model,
MOI.VariablePrimal(),
get_vis_dual_problem(optimizer, ci),
)
primal_dual_map = optimizer.dual_problem.primal_dual_map
if ci in keys(primal_dual_map.constrained_var_dual)
ci_dual = primal_dual_map.constrained_var_dual[ci]
if ci_dual === NO_CONSTRAINT
return MOI.Utilities.eval_variables(
primal_dual_map.constrained_var_zero[ci],
) do vi
return MOI.get(
optimizer.dual_problem.dual_model,
MOI.VariablePrimal(),
vi,
)
end
end
return MOI.get(
optimizer.dual_problem.dual_model,
MOI.ConstraintPrimal(),
primal_dual_map.constrained_var_dual[ci],
)
else
return MOI.get.(
optimizer.dual_problem.dual_model,
MOI.VariablePrimal(),
get_vis_dual_problem(optimizer, ci),
)
end
end

function MOI.get(
optimizer::DualOptimizer,
::MOI.ConstraintPrimal,
ci::CI{F,S},
) where {F<:MOI.AbstractScalarFunction,S<:MOI.AbstractScalarSet}
primal_ci_constant = get_primal_ci_constant(optimizer, ci)
# If it has no key than there is no dual constraint
if !haskey(optimizer.dual_problem.primal_dual_map.primal_con_dual_con, ci)
return -primal_ci_constant
primal_dual_map = optimizer.dual_problem.primal_dual_map
if ci in keys(primal_dual_map.constrained_var_dual)
return _get(
optimizer,
MOI.ConstraintDual(),
ci,
primal_dual_map.constrained_var_dual[ci],
)
else
primal_ci_constant = get_primal_ci_constant(optimizer, ci)
# If it has no key then there is no dual constraint
if !haskey(primal_dual_map.primal_con_dual_con, ci)
return -primal_ci_constant
end
ci_dual_problem = get_ci_dual_problem(optimizer, ci)
return MOI.get(
optimizer.dual_problem.dual_model,
MOI.ConstraintDual(),
ci_dual_problem,
) - primal_ci_constant
end
ci_dual_problem = get_ci_dual_problem(optimizer, ci)
return MOI.get(
optimizer.dual_problem.dual_model,
MOI.ConstraintDual(),
ci_dual_problem,
) - primal_ci_constant
end

function MOI.get(
optimizer::DualOptimizer{T},
::MOI.ConstraintPrimal,
ci::CI{F,S},
) where {T,F<:MOI.AbstractVectorFunction,S<:MOI.AbstractVectorSet}
# If it has no key than there is no dual constraint
if !haskey(optimizer.dual_problem.primal_dual_map.primal_con_dual_con, ci)
# The number of dual variable associated with the primal constraint is the ci dimension
ci_dimension = length(get_vis_dual_problem(optimizer, ci))
return zeros(T, ci_dimension)
primal_dual_map = optimizer.dual_problem.primal_dual_map
if ci in keys(primal_dual_map.constrained_var_dual)
return _get(
optimizer,
MOI.ConstraintDual(),
ci,
primal_dual_map.constrained_var_dual[ci],
)
else
# If it has no key then there is no dual constraint
if !haskey(primal_dual_map.primal_con_dual_con, ci)
# The number of dual variable associated with the primal constraint is the ci dimension
ci_dimension = length(get_vis_dual_problem(optimizer, ci))
return zeros(T, ci_dimension)
end
ci_dual_problem = get_ci_dual_problem(optimizer, ci)
return MOI.get(
optimizer.dual_problem.dual_model,
MOI.ConstraintDual(),
ci_dual_problem,
)
end
ci_dual_problem = get_ci_dual_problem(optimizer, ci)
return MOI.get(
optimizer.dual_problem.dual_model,
MOI.ConstraintDual(),
ci_dual_problem,
)
end

function MOI.get(optimizer::DualOptimizer, ::MOI.TerminationStatus)
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