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Add support for starting values #111

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Sep 30, 2018
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Add support for starting values #111

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Add support for starting values
blegat Sep 27, 2018
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blegat Sep 28, 2018
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46 changes: 43 additions & 3 deletions src/MOIWrapper.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -8,7 +8,7 @@ const MOIU = MOI.Utilities
const SF = Union{MOI.SingleVariable, MOI.ScalarAffineFunction{Float64}, MOI.VectorOfVariables, MOI.VectorAffineFunction{Float64}}
const SS = Union{MOI.EqualTo{Float64}, MOI.GreaterThan{Float64}, MOI.LessThan{Float64}, MOI.Zeros, MOI.Nonnegatives, MOI.Nonpositives, MOI.SecondOrderCone, MOI.ExponentialCone, MOI.PositiveSemidefiniteConeTriangle}

struct MOISolution
mutable struct MOISolution
ret_val::Int
primal::Vector{Float64}
dual::Vector{Float64}
Expand Down Expand Up @@ -77,7 +77,8 @@ MOIU.needs_allocate_load(instance::Optimizer) = true

function MOI.supports(::Optimizer,
::Union{MOI.ObjectiveSense,
MOI.ObjectiveFunction{MOI.ScalarAffineFunction{Float64}}})
MOI.ObjectiveFunction{MOI.ScalarAffineFunction{Float64}},
MOI.VariablePrimalStart})
return true
end

Expand Down Expand Up @@ -259,13 +260,49 @@ function MOIU.load_variables(optimizer::Optimizer, nvars::Integer)
b = zeros(m)
c = zeros(nvars)
optimizer.data = ModelData(m, nvars, I, J, V, b, 0., c)
# `optimizer.sol` contains the result of the previous optimization.
# It is used as a warm start if its length is the same, e.g.
# probably because no variable and/or constraint has been added.
if length(optimizer.sol.primal) != nvars
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What could the length be if not nvars? Would isempty also work as a test? Same below.

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sol contains the solution of the previous optimization. If the user has added new variables, then it is not nvars

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Does this interface allow adding variables and/or constraints?

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You can copy a model with a different number of variables/constraints. Normally, they will arrive in the same order.

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Could this if be replaced with resize! then?

optimizer.sol.primal = zeros(nvars)
end
@assert length(optimizer.sol.dual) == length(optimizer.sol.slack)
if length(optimizer.sol.dual) != m
optimizer.sol.dual = zeros(m)
optimizer.sol.slack = zeros(m)
end
end

function MOIU.allocate(::Optimizer, ::MOI.VariablePrimalStart,
::MOI.VariableIndex, ::Float64)
end
function MOIU.allocate(::Optimizer, ::MOI.ConstraintPrimalStart,
::MOI.ConstraintIndex, ::Float64)
end
function MOIU.allocate(::Optimizer, ::MOI.ConstraintDualStart,
::MOI.ConstraintIndex, ::Float64)
end
function MOIU.allocate(optimizer::Optimizer, ::MOI.ObjectiveSense, sense::MOI.OptimizationSense)
optimizer.maxsense = sense == MOI.MaxSense
end
function MOIU.allocate(::Optimizer, ::MOI.ObjectiveFunction, ::MOI.ScalarAffineFunction) end

function MOIU.load(optimizer::Optimizer, ::MOI.VariablePrimalStart,
vi::MOI.VariableIndex, value::Float64)
optimizer.sol.primal[vi.value] = value
end
function MOIU.load(optimizer::Optimizer, ::MOI.ConstraintPrimalStart,
ci::MOI.ConstraintIndex, value)
offset = constroffset(optimizer, ci)
rows = constrrows(optimizer, ci)
optimizer.sol.primal[offset .+ rows] .= value
end
function MOIU.load(optimizer::Optimizer, ::MOI.ConstraintDualStart,
ci::MOI.ConstraintIndex, value)
offset = constroffset(optimizer, ci)
rows = constrrows(optimizer, ci)
optimizer.sol.primal[offset .+ rows] .= value
end
function MOIU.load(::Optimizer, ::MOI.ObjectiveSense, ::MOI.OptimizationSense) end
function MOIU.load(optimizer::Optimizer, ::MOI.ObjectiveFunction, f::MOI.ScalarAffineFunction)
c0 = Vector(sparsevec(variable_index_value.(f.terms), coefficient.(f.terms), optimizer.data.n))
Expand All @@ -282,7 +319,10 @@ function MOI.optimize!(optimizer::Optimizer)
objconstant = optimizer.data.objconstant
c = optimizer.data.c
optimizer.data = nothing # Allows GC to free optimizer.data before A is loaded to SCS
sol = SCS_solve(SCS.Indirect, m, n, A, b, c, cone.f, cone.l, cone.qa, cone.sa, cone.ep, cone.ed, cone.p)
sol = SCS_solve(SCS.Indirect, m, n, A, b, c,
cone.f, cone.l, cone.qa, cone.sa, cone.ep, cone.ed, cone.p,
optimizer.sol.primal, optimizer.sol.dual,
optimizer.sol.slack)
ret_val = sol.ret_val
primal = sol.x
dual = sol.y
Expand Down