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Merged
joaquimg merged 17 commits into from
Nov 8, 2021
Merged

Breaking changes for MOI v0.10 #147

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d459e62
Breaking changes for MOI v0.10
metab0t Sep 19, 2021
000fcbf
Update src/MOI/MOI_wrapper.jl
odow Sep 23, 2021
b1f79aa
Update src/MOI/MOI_wrapper.jl
odow Sep 23, 2021
746bf60
Remove duplicate tests existing MOI
metab0t Sep 23, 2021
d3be95c
Empty model should return empty MOI.ListOfModelAttributesSet.
metab0t Sep 30, 2021
374c843
Fix MOI.Test.test_model_ListOfConstraintAttributesSet
metab0t Sep 30, 2021
e35bc62
Change the way to track state of objective function and sense
metab0t Oct 1, 2021
9c79ec8
Merge branch 'master' into jg/moi0.10
joaquimg Oct 2, 2021
bcf9ea2
fix some tests
joaquimg Oct 2, 2021
d106b9a
fix IIS tests
joaquimg Oct 2, 2021
5fec93a
Merge pull request #153 from jump-dev/jg/moi0.10
joaquimg Oct 2, 2021
ba56b3d
rename moi wrapper tests files
joaquimg Oct 2, 2021
9b827f1
Replace more MOI.SingleVariable
metab0t Oct 3, 2021
7933036
Merge branch 'master' into moi_v0.10
joaquimg Nov 4, 2021
2d3e265
Merge branch 'master' into moi_v0.10
joaquimg Nov 6, 2021
9e0a1b9
fix for version 0.10.4
joaquimg Nov 7, 2021
f39c58e
Update MOI
joaquimg Nov 8, 2021
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4 changes: 2 additions & 2 deletions Project.toml
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Expand Up @@ -2,7 +2,7 @@ name = "Xpress"
uuid = "9e70acf3-d6c9-5be6-b5bd-4e2c73e3e054"
authors = ["Joaquim Dias Garcia <[email protected]>, Dheepak Krishnamurthy <[email protected]>, Jose Daniel Lara <[email protected]>"]
url = "https://github.com/jump-dev/Xpress.jl"
version = "0.13.2"
version = "0.14.0"

[deps]
Libdl = "8f399da3-3557-5675-b5ff-fb832c97cbdb"
Expand All @@ -11,7 +11,7 @@ MathOptInterface = "b8f27783-ece8-5eb3-8dc8-9495eed66fee"
SparseArrays = "2f01184e-e22b-5df5-ae63-d93ebab69eaf"

[compat]
MathOptInterface = "~0.9.20"
MathOptInterface = "0.10.5"
julia = "1"

[extras]
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509 changes: 284 additions & 225 deletions src/MOI/MOI_wrapper.jl
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1 change: 1 addition & 0 deletions test/.gitignore
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@@ -1 +1,2 @@
*.log
*.prt
14 changes: 7 additions & 7 deletions test/Derivative/DerivativeExample.jl
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Expand Up @@ -14,8 +14,8 @@ mutable struct DispachModel
c_demand # Constraint of the generation by the demand
end

#Simple Model of Thermal Generation Dispatch by Constraints with MOI.SingleVariable
function GenerateModel_SingleVariable()
#Simple Model of Thermal Generation Dispatch by Constraints with MOI.VariableIndex
function GenerateModel_VariableIndex()
# Parameters
d = 45.0 # Demand
I = 3 # Number of generators
Expand All @@ -33,10 +33,10 @@ function GenerateModel_SingleVariable()
c_limit_inf = Vector{Any}(undef, I + 1) # Lower limit constraints
c_limit_sup = Vector{Any}(undef, I) # Upper limit constraints
for i in 1:I
c_limit_inf[i] = MOI.add_constraint(optimizer, MOI.SingleVariable(g[i]), MOI.GreaterThan(0.0))
c_limit_sup[i] = MOI.add_constraint(optimizer, MOI.SingleVariable(g[i]), MOI.LessThan(g_sup[i]))
c_limit_inf[i] = MOI.add_constraint(optimizer, g[i], MOI.GreaterThan(0.0))
c_limit_sup[i] = MOI.add_constraint(optimizer, g[i], MOI.LessThan(g_sup[i]))
end
c_limit_inf[I+1] = MOI.add_constraint(optimizer, MOI.SingleVariable(Df), MOI.GreaterThan(0.0))
c_limit_inf[I+1] = MOI.add_constraint(optimizer, Df, MOI.GreaterThan(0.0))

c_demand = MOI.add_constraint(optimizer,
MOI.ScalarAffineFunction(MOI.ScalarAffineTerm.(ones(I+1),[g;Df]), 0.0),
Expand Down Expand Up @@ -158,8 +158,8 @@ end
#Initialization of Parameters
@testset "Results" begin
@testset "Single_Variable" begin
#Generate model by SingleVariable
model1 = GenerateModel_SingleVariable()
#Generate model by VariableIndex
model1 = GenerateModel_VariableIndex()
#Get the results of models with the DiffOpt Forward context
@testset "Forward" begin
resultForward = Forward(model1)
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6 changes: 1 addition & 5 deletions test/MathOptInterface/MOI_callbacks.jl
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Expand Up @@ -4,10 +4,6 @@ using Random
using Test

const MOI = MathOptInterface
const MOIT = MathOptInterface.Test

const MOIT = MOI.Test
const MOIU = MOI.Utilities

function callback_simple_model()
model = Xpress.Optimizer(
Expand Down Expand Up @@ -43,7 +39,7 @@ function callback_knapsack_model()

N = 30
x = MOI.add_variables(model, N)
MOI.add_constraints(model, MOI.SingleVariable.(x), MOI.ZeroOne())
MOI.add_constraints(model, x, MOI.ZeroOne())
MOI.set.(model, MOI.VariablePrimalStart(), x, 0.0)
Random.seed!(1)
item_weights, item_values = rand(N), rand(N)
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