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5 files changed

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‎src/ConstraintModels.jl‎

Lines changed: 5 additions & 3 deletions
Original file line numberDiff line numberDiff line change
@@ -10,20 +10,22 @@ const LS = LocalSearchSolvers
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import LocalSearchSolvers: Options
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export qap
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export mincut
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export chemical_equilibrium
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export golomb
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export qap
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export magic_square
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export mincut
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export n_queens
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export scheduling
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export sudoku
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export chemical_equilibrium
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include("assignment.jl")
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include("chemical_equilibrium.jl")
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include("cut.jl")
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include("golomb.jl")
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include("magic_square.jl")
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include("n_queens.jl")
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include("scheduling.jl")
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include("sudoku.jl")
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end

‎src/scheduling.jl‎

Lines changed: 34 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -0,0 +1,34 @@
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function scheduling(processing_times, due_dates, ::Val{:JuMP})
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model = JuMP.Model(CBLS.Optimizer)
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n = length(processing_times) # number of jobs
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max_time = sum(processing_times)
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minus_eq_param(param) = x -> x[1] - x[2] == param
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less_than_param(param) = x -> x[1] ≤ param
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sequential_tasks(x) = x[1] ≤ x[2] || x[3] ≤ x[4]
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@variable(model, 0 ≤ C[1:n] ≤ max_time, Int) # completion
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@variable(model, 0 ≤ S[1:n] ≤ max_time, Int) # start
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@constraint(model, C in AllDifferent())
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@constraint(model, S in AllDifferent())
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for i in 1:n
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@constraint(model, [C[i], S[i]] in Predicate(minus_eq_param(processing_times[i])))
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# @constraint(model, [C[i]] in Predicate(less_than_param(due_dates[i])))
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end
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# for i in 1:n, j in 1:n
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# i == j && continue
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# @constraint(model, [C[i], S[j], C[j], S[i]] in Predicate(sequential_tasks))
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# end
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return model, C, S
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end
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"""
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scheduling(processing_time, due_date; modeler=:JuMP)
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Create a model for the n-queens problem with `n` queens. The `modeler` argument accepts :JuMP (default), which refer to the JuMP model.
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"""
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scheduling(processing_times, due_dates; modeler=:JuMP) = scheduling(processing_times, due_dates, Val(modeler))

‎test/JuMP.jl‎

Lines changed: 85 additions & 77 deletions
Original file line numberDiff line numberDiff line change
@@ -1,79 +1,87 @@
1-
@testset "JuMP: constraints" begin
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m = Model(CBLS.Optimizer)
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err = _ -> 1.0
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concept = _ -> true
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@variable(m, X[1:10], DiscreteSet(1:4))
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9-
@constraint(m, X in Error(err))
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@constraint(m, X in Predicate(concept))
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@constraint(m, X in AllDifferent())
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@constraint(m, X in AllEqual())
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@constraint(m, X in AllEqualParam(2))
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@constraint(m, X in AlwaysTrue())
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@constraint(m, X[1:4] in DistDifferent())
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@constraint(m, X[1:2] in Eq())
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@constraint(m, X in Ordered())
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end
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@testset "JuMP: sudoku 9x9" begin
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m, X = sudoku(3)
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optimize!(m)
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solution_ = value.(X)
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display(solution_, Val(:sudoku))
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end
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@testset "JuMP: golomb(5)" begin
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m, X = golomb(5)
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optimize!(m)
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@info "JuMP: golomb(5)" value.(X)
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end
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@testset "JuMP: magic_square(3)" begin
35-
m, X = magic_square(3)
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optimize!(m)
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@info "JuMP: magic_square(3)" value.(X)
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end
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@testset "JuMP: n_queens(5)" begin
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m, X = n_queens(5)
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optimize!(m)
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@info "JuMP: n_queens(5)" value.(X)
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end
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@testset "JuMP: qap(12)" begin
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m, X = qap(12, qap_weights, qap_distances)
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optimize!(m)
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@info "JuMP: qap(12)" value.(X)
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end
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@testset "JuMP: basic opt" begin
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model = Model(CBLS.Optimizer)
54-
set_optimizer_attribute(model, "iteration", 100)
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@test get_optimizer_attribute(model, "iteration") == 100
56-
set_time_limit_sec(model, 5.0)
57-
@test time_limit_sec(model) == 5.0
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@variable(model, x in DiscreteSet(0:20))
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@variable(model, y in DiscreteSet(0:20))
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@constraint(model, [x,y] in Predicate(v -> 6v[1] + 8v[2] >= 100 ))
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@constraint(model, [x,y] in Predicate(v -> 7v[1] + 12v[2] >= 120 ))
64-
65-
objFunc = v -> 12v[1] + 20v[2]
66-
@objective(model, Min, ScalarFunction(objFunc))
67-
1+
# @testset "JuMP: constraints" begin
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# m = Model(CBLS.Optimizer)
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4+
# err = _ -> 1.0
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# concept = _ -> true
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7+
# @variable(m, X[1:10], DiscreteSet(1:4))
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9+
# @constraint(m, X in Error(err))
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# @constraint(m, X in Predicate(concept))
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# @constraint(m, X in AllDifferent())
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# @constraint(m, X in AllEqual())
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# @constraint(m, X in AllEqualParam(2))
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# @constraint(m, X in AlwaysTrue())
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# @constraint(m, X[1:4] in DistDifferent())
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# @constraint(m, X[1:2] in Eq())
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# @constraint(m, X in Ordered())
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# end
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# @testset "JuMP: sudoku 9x9" begin
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# m, X = sudoku(3)
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# optimize!(m)
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# solution_ = value.(X)
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# display(solution_, Val(:sudoku))
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# end
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# @testset "JuMP: golomb(5)" begin
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# m, X = golomb(5)
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# optimize!(m)
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# @info "JuMP: golomb(5)" value.(X)
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# end
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# @testset "JuMP: magic_square(3)" begin
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# m, X = magic_square(3)
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# optimize!(m)
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# @info "JuMP: magic_square(3)" value.(X)
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# end
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40+
# @testset "JuMP: n_queens(5)" begin
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# m, X = n_queens(5)
42+
# optimize!(m)
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# @info "JuMP: n_queens(5)" value.(X)
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# end
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46+
# @testset "JuMP: qap(12)" begin
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# m, X = qap(12, qap_weights, qap_distances)
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# optimize!(m)
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# @info "JuMP: qap(12)" value.(X)
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# end
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# @testset "JuMP: basic opt" begin
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# model = Model(CBLS.Optimizer)
54+
# set_optimizer_attribute(model, "iteration", 100)
55+
# @test get_optimizer_attribute(model, "iteration") == 100
56+
# set_time_limit_sec(model, 5.0)
57+
# @test time_limit_sec(model) == 5.0
58+
59+
# @variable(model, x in DiscreteSet(0:20))
60+
# @variable(model, y in DiscreteSet(0:20))
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62+
# @constraint(model, [x,y] in Predicate(v -> 6v[1] + 8v[2] >= 100 ))
63+
# @constraint(model, [x,y] in Predicate(v -> 7v[1] + 12v[2] >= 120 ))
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65+
# objFunc = v -> 12v[1] + 20v[2]
66+
# @objective(model, Min, ScalarFunction(objFunc))
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68+
# optimize!(model)
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# @info "JuMP: basic opt" value(x) value(y) (12*value(x)+20*value(y))
71+
# end
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73+
# @testset "JuMP: Chemical equilibrium" begin
74+
# m, X = chemical_equilibrium(atoms_compounds, elements_weights, standard_free_energy)
75+
# # set_optimizer_attribute(m, "iteration", 10000)
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# # set_time_limit_sec(m, 120.0)
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# optimize!(m)
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# @info "JuMP: $compounds_names ⟺ $mixture_name" value.(X)
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# end
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@testset "JuMP: Scheduling" begin
82+
model, completion_times, start_times = scheduling(processing_times, due_times)
6883
optimize!(model)
69-
70-
@info "JuMP: basic opt" value(x) value(y) (12*value(x)+20*value(y))
71-
end
72-
73-
@testset "JuMP: Chemical equilibrium" begin
74-
m, X = chemical_equilibrium(atoms_compounds, elements_weights, standard_free_energy)
75-
# set_optimizer_attribute(m, "iteration", 10000)
76-
# set_time_limit_sec(m, 120.0)
77-
optimize!(m)
78-
@info "JuMP: $compounds_names ⟺ $mixture_name" value.(X)
84+
@info solution_summary(model)
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@info "JuMP: scheduling" value.(start_times) value.(completion_times) processing_times due_times
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@info (value.(start_times)+processing_times == value.(completion_times))
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end

‎test/instances.jl‎

Lines changed: 5 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -74,3 +74,8 @@ compounds_names = "x₁⋅H + x₂⋅H₂ + x₃⋅H₂O + x₄⋅N + x₅⋅N
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mixture_name = "½⋅N₂H₄ + ½⋅O₂"
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7676
equation = compounds_names * " = " * mixture_name
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# processing_times = [3, 2, 1]
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# due_times = [5, 6, 8]
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processing_times = [3, 2]
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due_times = [5, 6]

‎test/runtests.jl‎

Lines changed: 2 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -8,7 +8,7 @@ using Test
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@testset "ConstraintModels.jl" begin
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include("instances.jl")
11-
include("raw_solver.jl")
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include("MOI_wrapper.jl")
11+
# include("raw_solver.jl")
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# include("MOI_wrapper.jl")
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include("JuMP.jl")
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end

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