Merge pull request #90 from joaquimg/jg/typo

Fix CI reference constructor

src/jump.jl

@@ -744,7 +744,7 @@ function get_constrain_ref(vref::BilevelVariableRef)
         end
     end
     @assert idx != -1
-    return BilevelConstraintRef(model, idx, DUAL_OF_LOWER)
+    return BilevelConstraintRef(model, idx)
 end
 
 # Objective

src/moi.jl

@@ -189,7 +189,7 @@ mutable struct StrongDualityInequalityMode{T} <: StrongDualityMode{T}
     function StrongDualityInequalityMode()
         return new{Float64}(zero(Float64))
     end
-    function StrongDualityInequalityMode{T}(eps::T) where T
+    function StrongDualityInequalityMode(eps::T) where T
         return new{Float64}(eps)
     end
 end

test/jump.jl

@@ -1391,8 +1391,8 @@ function jump_HTP_lin08(optimizer, mode = BilevelJuMP.SOS1Mode(), config = Confi
     MOI.empty!(optimizer)
     model = BilevelModel(()->optimizer, mode = mode)
 
-    @variable(Upper(model), x[i=1:2])
-    @variable(Lower(model), y[i=1:2])
+    @variable(Upper(model), x[i=1:2], start = [2, 0][i])
+    @variable(Lower(model), y[i=1:2], start = [1.5, 0][i])
 
     @objective(Upper(model), Min,
         -2x[1] + x[2] + 0.5*y[1])
@@ -1462,8 +1462,8 @@ function jump_HTP_lin10(optimizer, mode = BilevelJuMP.SOS1Mode(), config = Confi
     MOI.empty!(optimizer)
     model = BilevelModel(()->optimizer, mode = mode)
 
-    @variable(Upper(model), x[i=1:2])
-    @variable(Lower(model), y[i=1:2])
+    @variable(Upper(model), x[i=1:2], start = [2, 0][i])
+    @variable(Lower(model), y[i=1:2], start = [1.5, 0][i])
 
     @objective(Upper(model), Min,
         -2x[1] + x[2] + 0.5*y[1])
@@ -2301,7 +2301,7 @@ function jump_fanzeres2017(optimizer, mode = BilevelJuMP.SOS1Mode(), config = Co
     @constraint(Lower(model), g[4] <= 100)
     @constraint(Lower(model), lb[i=1:4], g[i] >= 0)
 
-    @variable(Upper(model), lambda, DualOf(b), start = 1_000)
+    @variable(Upper(model), lambda >= 0, DualOf(b), start = 1_000)
 
     @objective(Upper(model), Max, lambda*g[1])
 
@@ -2317,6 +2317,47 @@ function jump_fanzeres2017(optimizer, mode = BilevelJuMP.SOS1Mode(), config = Co
     @test value(lambda) ≈ 1_000 atol=1e-3
 end
 
+function jump_eq_price(optimizer, mode = BilevelJuMP.SOS1Mode(), config = Config())
+
+    atol = config.atol
+    start = config.start_value
+
+    j = 3
+    jger = 1
+    G = [10, 15, 12]
+    d = 26
+    c = [1, 2, 1.5]
+    p = 1
+    q = 10
+
+    MOI.empty!(optimizer)
+    model = BilevelModel(()->optimizer, mode = mode)
+
+    @variable(Upper(model), u[i=1:jger] >= 0, start = [2.0][i])
+
+    @variable(Lower(model), def >= 0, start = 0)
+    @variable(Lower(model), g[i=1:j] >= 0, start = [10.0, 4.0, 12.0][i])
+
+    @constraint(Lower(model), MaxGen[i=1:j], g[i] <= G[i])
+    @constraint(Lower(model), DemBal, sum(g[i] for i in 1:j) + def == d)
+    @objective(Lower(model), Min, sum(u[i]*g[i] for i in 1:jger) +
+                    sum(c[i+jger]*g[i+jger] for i in 1:(j-jger)) + 100*def)
+
+    @variable(Upper(model), lambda >= 0, DualOf(DemBal), start = 2.0)
+    @objective(Upper(model), Max, lambda*sum(g[i] for i in 1:jger) -
+                        sum(c[i]*g[i] for i in 1:jger) - (lambda - p)*q)
+
+    optimize!(model)
+
+    primal_status(model)
+    termination_status(model)
+
+    @test value.(g) ≈ [10.0, 4.0, 12.0]  atol=atol
+    @test value(def) ≈ 0.0  atol=atol
+    @test value(lambda) ≈ 2.0  atol=atol
+    @test value.(u) ≈ [2.0]  atol=atol
+
+end
 
 function jump_16(optimizer, mode = BilevelJuMP.SOS1Mode(), config = Config())
 

test/runtests.jl

@@ -43,8 +43,10 @@ solvers_quad = OptModeType[]
 solvers_bin_exp = OptModeType[]
 solvers_sos_quad = OptModeType[]
 solvers_nlp = OptModeType[]
+solvers_nlp_sd = OptModeType[]
 solvers_nlp_lowtol = OptModeType[]
 solvers_sos_quad_bin = OptModeType[]
+solvers_fa_quad_bin = OptModeType[]
 solvers_fa = OptModeType[]
 solvers_fa2 = OptModeType[]
 
@@ -146,17 +148,25 @@ end
 end
 
 @testset "Princeton Handbook of Test Problems" begin
-    for solver in solvers_nlp
+    for solver in vcat(solvers_nlp, solvers_nlp_sd)
         jump_HTP_lin01(solver.opt, solver.mode, CONFIG_3_start)
-        jump_HTP_lin02(solver.opt, solver.mode)
+        # jump_HTP_lin02(solver.opt, solver.mode, CONFIG_4)
         jump_HTP_lin03(solver.opt, solver.mode)
         jump_HTP_lin03_vec(solver.opt, solver.mode)
         jump_HTP_lin04(solver.opt, solver.mode)
         jump_HTP_lin05(solver.opt, solver.mode) # broken on cbc linux on julia 1.0 and 1.2 but not 1.1 see: https://travis-ci.org/joaquimg/BilevelJuMP.jl/builds/619335351
         jump_HTP_lin06(solver.opt, solver.mode)
         jump_HTP_lin07(solver.opt, solver.mode, CONFIG_2)
-        jump_HTP_lin08(solver.opt, solver.mode)
+        jump_HTP_lin08(solver.opt, solver.mode, CONFIG_4)
         jump_HTP_lin09(solver.opt, solver.mode)
+        # jump_HTP_lin10(solver.opt, solver.mode)
+    end
+    for solver in solvers_nlp_sd
+        jump_HTP_lin02(solver.opt, solver.mode, CONFIG_2)
+        # jump_HTP_lin10(solver.opt, solver.mode)
+    end
+    for solver in solvers_nlp
+        jump_HTP_lin02(solver.opt, solver.mode)
         jump_HTP_lin10(solver.opt, solver.mode)
     end
     for solver in solvers_nlp
@@ -236,19 +246,27 @@ end
     end
 end
 
-@testset "conejo2016" begin
+@testset "equilibrium" begin
     for solver in solvers_nlp
         jump_conejo2016(solver.opt, solver.mode)
-    end
-    for solver in solvers_sos_quad_bin
-        jump_conejo2016(solver.opt, solver.mode, config, bounds = true)
-    end
-end
-
-@testset "fanzeres2017" begin
-    for solver in solvers_nlp
         jump_fanzeres2017(solver.opt, solver.mode)
+        # jump_eq_price(solver.opt, solver.mode)
+    end
+    for solver in solvers_nlp_sd
+        jump_conejo2016(solver.opt, solver.mode)
+        # jump_fanzeres2017(solver.opt, solver.mode)
+        # jump_eq_price(solver.opt, solver.mode)
     end
+    # for solver in solvers_sos_quad_bin
+    #     jump_conejo2016(solver.opt, solver.mode, config, bounds = true)
+    #     jump_fanzeres2017(solver.opt, solver.mode)
+    #     jump_eq_price(solver.opt, solver.mode)
+    # end
+    # for solver in solvers_fa_quad_bin
+    #     jump_conejo2016(solver.opt, solver.mode, config, bounds = true)
+    #     jump_fanzeres2017(solver.opt, solver.mode)
+    #     jump_eq_price(solver.opt, solver.mode)
+    # end
 end
 
 # require SOCtoNonConvexQuad bridge to work with Ipopt

test/solvers/cbc.jl

@@ -6,6 +6,7 @@ MOI.set(CBC_OPTIMIZER, MOI.Silent(), true)
 const CBC_CACHE = MOIU.UniversalFallback(MOIU.Model{Float64}())
 const CBC_CACHED = MOIU.CachingOptimizer(CBC_CACHE, CBC_OPTIMIZER)
 const CBC_BRIDGED = MOI.Bridges.full_bridge_optimizer(CBC_CACHED, Float64)
+MOI.Bridges.add_bridge(CBC_BRIDGED, MOI.Bridges.Constraint.SOCtoNonConvexQuadBridge{Float64})
 
 push!(solvers, (opt = CBC_BRIDGED, mode = BilevelJuMP.SOS1Mode()))
 push!(solvers_sos, (opt = CBC_BRIDGED, mode = BilevelJuMP.SOS1Mode()))
@@ -17,14 +18,27 @@ push!(solvers_fa2, (opt = CBC_BRIDGED, mode = BilevelJuMP.FortunyAmatMcCarlMode(
 
 push!(solvers_bin_exp, (
     opt = QuadraticToBinary.Optimizer{Float64}(CBC_BRIDGED),
-    mode = BilevelJuMP.StrongDualityInequalityMode{Float64}(1e-9)))
+    mode = BilevelJuMP.StrongDualityInequalityMode(1e-9)))
 MOI.set(solvers_bin_exp[end].opt, QuadraticToBinary.GlobalVariablePrecision(), 1e-5)
 
 push!(solvers_bin_exp, (
     opt = QuadraticToBinary.Optimizer{Float64}(CBC_BRIDGED),
     mode = BilevelJuMP.StrongDualityEqualityMode()))
 MOI.set(solvers_bin_exp[end].opt, QuadraticToBinary.GlobalVariablePrecision(), 1e-5)
 
+#=
+QTB_CBC_BRIDGED = MOI.Bridges.full_bridge_optimizer(
+    QuadraticToBinary.Optimizer{Float64}(CBC_BRIDGED, lb=-1000,ub=1000),
+    Float64)
+MOI.Bridges.add_bridge(QTB_CBC_BRIDGED, MOI.Bridges.Constraint.SOCtoNonConvexQuadBridge{Float64})
+
+push!(solvers_sos_quad_bin, (
+    opt = QTB_CBC_BRIDGED,
+    mode = BilevelJuMP.SOS1Mode()))
+push!(solvers_fa_quad_bin, (
+    opt = QTB_CBC_BRIDGED,
+    mode = BilevelJuMP.FortunyAmatMcCarlMode(primal_big_M = 1000, dual_big_M = 1000)))
+=#
 # push!(solvers_sos_quad, (
 #     opt = QuadraticToBinary.Optimizer{Float64}(CBC_BRIDGED),
 #     mode = BilevelJuMP.SOS1Mode()))

test/solvers/ipopt.jl

@@ -14,8 +14,9 @@ push!(solvers_nlp, (opt = IPO_BRIDGED, mode = BilevelJuMP.ProductWithSlackMode(1
 push!(solvers, (opt = IPO_BRIDGED, mode = BilevelJuMP.ProductMode(1e-9)))
 push!(solvers_quad, (opt = IPO_BRIDGED, mode = BilevelJuMP.ProductMode(1e-9)))
 
+# push!(solvers_nlp, (opt = IPO_BRIDGED, mode = BilevelJuMP.StrongDualityInequalityMode(1e-9)))
+push!(solvers_nlp_sd, (opt = IPO_BRIDGED, mode = BilevelJuMP.StrongDualityEqualityMode()))
 #=
 push!(solvers, (opt = IPO_BRIDGED, mode = BilevelJuMP.StrongDualityInequalityMode(1e-9)))
 push!(solvers_quad, (opt = IPO_BRIDGED, mode = BilevelJuMP.StrongDualityInequalityMode(1e-9)))
-#push!(solvers_nlp, (opt = IPO_BRIDGED, mode = BilevelJuMP.StrongDualityInequalityMode(1e-9)))
 =#