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Refactor reformulation parser #754

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Dec 8, 2022
Merged

Refactor reformulation parser #754

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e132211
Refactor reformulation parser
eduardovegas Dec 7, 2022
7edb12c
Update parser tests
eduardovegas Dec 7, 2022
22dcf09
Use parser to build reformulations in the tests
eduardovegas Dec 7, 2022
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67 changes: 24 additions & 43 deletions test/integration/initial_columns_callback.jl
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Original file line number Diff line number Diff line change
@@ -1,60 +1,41 @@
@testset "Integration - initial columns callback" begin
# DW subproblem formulation having a given nb of variables.
# Its parent is the master with representatives of sp vars & a constraint sum_i i*x_i <= 0.
# Cost of variable x[i] is i.
function build_reformulation(nb_variables)
env = CL.Env{ClMP.VarId}(CL.Params())

# Create the reformulation
reform = ClMP.Reformulation(env)

# Create subproblem and variables
spform = ClMP.create_formulation!(env, ClMP.DwSp(nothing, nothing, nothing, ClMP.Continuous))
spvars = Dict{String, ClMP.Variable}();
for i in 1:nb_variables
x = ClMP.setvar!(spform, "x$i", ClMP.DwSpPricingVar)
ClMP.setperencost!(spform, x, i * 1.0)
spvars["x$i"] = x
end
ClMP.add_dw_pricing_sp!(reform, spform)

# Create master and representatives
master = ClMP.create_formulation!(env, ClMP.DwMaster(); parent_formulation = reform)
spform.parent_formulation = master
mastervars = Dict{String, ClMP.Variable}();
for i in 1:nb_variables
x = ClMP.setvar!(
master, "x$i", ClMP.MasterRepPricingVar, id = ClMP.getid(spvars["x$i"])
)
ClMP.setperencost!(master, x, i * 1.0)
mastervars["x$i"] = x
end

constr = ClMP.setconstr!(
master, "constr", ClMP.MasterMixedConstr;
members = Dict(ClMP.getid(mastervars["x$i"]) => 1.0 * i for i in 1:nb_variables)
)
ClMP.setmaster!(reform, master)

closefillmode!(ClMP.getcoefmatrix(master))
closefillmode!(ClMP.getcoefmatrix(spform))
function build_reformulation()
nb_variables = 4
form_string = """
master
min
1.0*x1 + 2.0*x2 + 3.0*x3 + 4.0*x4
s.t.
1.0*x1 + 2.0*x2 + 3.0*x3 + 4.0*x4 >= 0.0

dw_sp
min
1.0*x1 + 2.0*x2 + 3.0*x3 + 4.0*x4

continuous
representatives
x1, x2, x3, x4
"""
env, master, subproblems, constraints = reformfromstring(form_string)
spform = subproblems[1]
spvarids = Dict(CL.getname(spform, var) => varid for (varid, var) in CL.getvars(spform))

# Fake JuMP model to simulate the user interacting with it in the callback.
fake_model = JuMP.Model()
@variable(fake_model, x[i in 1:nb_variables])

for name in ["x$i" for i in 1:nb_variables]
CleverDicts.add_item(env.varids, ClMP.getid(spvars[name]))
CleverDicts.add_item(env.varids, spvarids[name])
end
return env, master, spform, spvars, x, constr
return env, master, spform, x, constraints[1]
end

# Create a formulation with 4 variables [x1 x2 x3 x4] and provide an initial column
# [1 0 2 0].
# Cost of the column in the master should be 7.
# Coefficient of the column in the constraint should be 7.
@testset "normal case" begin
env, master, spform, vars, x, constr = build_reformulation(4)
env, master, spform, x, constr = build_reformulation()

function callback(cbdata)
variables = [x[1].index, x[3].index]
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