Merge pull request #175 from joaquimg/jg/roa

fix raw opt attribute

Project.toml

@@ -1,7 +1,7 @@
 name = "BilevelJuMP"
 uuid = "485130c0-026e-11ea-0f1a-6992cd14145c"
 authors = ["Joaquim Garcia <[email protected]>, guilhermebodin <[email protected]>"]
-version = "0.5.0"
+version = "0.5.1"
 
 [deps]
 Dualization = "191a621a-6537-11e9-281d-650236a99e60"
@@ -12,5 +12,5 @@ MathOptInterface = "b8f27783-ece8-5eb3-8dc8-9495eed66fee"
 [compat]
 Dualization = "0.5.4"
 JuMP = "1.0"
-MathOptInterface = "1.0"
+MathOptInterface = "1.2"
 julia = "1.6"

README.md

@@ -79,6 +79,8 @@ NLP (Ipopt, KNITRO) solvers or even MIP solvers with the aid of binary
 expansions
 (see [QuadraticToBinary.jl](https://github.com/joaquimg/QuadraticToBinary.jl)).
 Note that binary expansions require variables to have upper and lower bounds.
+Also, note that the `Gurobi` solver supports products, but requires [setting the
+`"NonConvex"` options](https://github.com/jump-dev/Gurobi.jl#using-gurobi-v90-and-you-got-an-error-like-q-not-psd).
 
 Finally, one can use `BilevelJuMP.MixedMode(default = mode)` where `mode` is one
 of the other modes described above. With this method it is possible to set
@@ -89,7 +91,7 @@ reformulation which add the constraint enforcing primal dual equality. The optio
 is `BilevelJuMP.StrongDualityMode(eps)` where `eps` is the tolance on the enforcing
 constraint.
 
-### Note on [QuadraticToBinary.jl](https://github.com/joaquimg/QuadraticToBinary.jl)
+### Note on QuadraticToBinary
 
 [QuadraticToBinary.jl](https://github.com/joaquimg/QuadraticToBinary.jl) is a
 package that converts quadratic terms in constraints and objective. To do so
@@ -99,7 +101,7 @@ directly to the solver itself. For many solvers it is enough to use:
 ```julia
 SOLVER = Xpress.Optimizer()
 Q_SOLVER = QuadraticToBinary.Optimizer{Float64}(SOLVER)
-BilevelModel(Q_SOLVER, mode = BilevelJuMP.ProductMode(1e-5))
+BilevelModel(()->Q_SOLVER, mode = BilevelJuMP.ProductMode(1e-5))
 ```
 
 However, this might lead to some solver not supporting certain functionality like SCIP.
@@ -156,3 +158,14 @@ not work properly with Cbc.
 ```julia
 @variable(Upper(model, variable_type = DualOf(my_lower_constraint))
 ```
+
+* Nonconvex/nonconcave/nonpsd objective/constraint error in a MIP solver.
+See section on
+[`QuadraticToBinary.jl`](#note-on-quadratictobinary)
+or if you are using
+[`Gurobi`](https://github.com/jump-dev/Gurobi.jl#using-gurobi-v90-and-you-got-an-error-like-q-not-psd)
+use:
+```julia
+model = BilevelModel(Gurobi.Optimizer, mode = BilevelJuMP.SOS1Mode()) #or other mode
+set_optimizer_attribute(model, "NonConvex", 2)
+```

src/jump_attributes.jl

@@ -7,7 +7,7 @@ end
 
 function JuMP.set_optimizer_attribute(bm::BilevelModel, name::String, value)
     _check_solver(bm)
-    return JuMP.set_optimizer_attribute(bm, MOI.RawParameter(name), value)
+    return JuMP.set_optimizer_attribute(bm, MOI.RawOptimizerAttribute(name), value)
 end
 function JuMP.set_optimizer_attribute(
     bm::BilevelModel, attr::MOI.AbstractOptimizerAttribute, value
@@ -23,7 +23,7 @@ end
 
 function JuMP.get_optimizer_attribute(bm::BilevelModel, name::String)
     _check_solver(bm)
-    return JuMP.get_optimizer_attribute(bm.solver, MOI.RawParameter(name))
+    return JuMP.get_optimizer_attribute(bm.solver, MOI.RawOptimizerAttribute(name))
 end
 function JuMP.get_optimizer_attribute(
     bm::BilevelModel, attr::MOI.AbstractOptimizerAttribute

src/mibs.jl

@@ -56,37 +56,9 @@ function _build_single_model(
 
     lower_sense = MOI.get(lower, MOI.ObjectiveSense())
 
-    #=
-    temp fix: while mibs does not support mps with obj sense
-    =#
-    if MOI.get(upper, MOI.ObjectiveSense()) == MOI.MAX_SENSE
-        MOI.set(upper, MOI.ObjectiveSense(), MOI.MIN_SENSE)
-        upper_obj_type = MOI.get(upper, MOI.ObjectiveFunctionType())
-        upper_objective = MOI.get(
-            upper,
-            MOI.ObjectiveFunction{upper_obj_type}(),
-        )
-        fixed_upper_obj = MOIU.operate(-, Float64, upper_objective)
-        MOI.set(
-            upper,
-            MOI.ObjectiveFunction{typeof(fixed_upper_obj)}(),
-            fixed_upper_obj,
-        )
-    end
     return model, lower_variables, lower_objective, lower_constraints, lower_sense
 end
 
-function _fix_moi_mps(file)
-    lines = readlines(file)
-    open(file, "w") do io
-        println(io, lines[1])
-        for i in 3:length(lines)
-            println(io, lines[i])
-        end
-    end
-    return
-end
-
 function _index_to_row_link(model::MOI.FileFormats.MPS.Model)
     i = 0
     dict = Dict{MOI.ConstraintIndex, Int}()
@@ -292,8 +264,8 @@ function solve_with_MibS(
         aux_filename = joinpath(path, "model.aux")
         new_model, variables, objective, constraints, sense  =
             _build_single_model(model, true)
+        # This MPS file must be strictly compliant with the format
         MOI.write_to_file(new_model, mps_filename)
-        _fix_moi_mps(mps_filename)
         _write_auxillary_file(
             new_model,
             variables,

test/Project.toml

@@ -5,12 +5,10 @@ JuMP = "4076af6c-e467-56ae-b986-b466b2749572"
 MathOptInterface = "b8f27783-ece8-5eb3-8dc8-9495eed66fee"
 MibS_jll = "118347d2-e127-56b9-9933-6abf9cc1adc1"
 QuadraticToBinary = "014a38d5-7acb-4e20-b6c0-4fe5c2344fd1"
-SCIP = "82193955-e24f-5292-bf16-6f2c5261a85f"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 Pkg = "44cfe95a-1eb2-52ea-b672-e2afdf69b78f"
 
 [compat]
 Ipopt = "=1.0.2"
 MibS_jll = "=1.1.3"
-QuadraticToBinary = "=0.4.0"
-SCIP = "=0.10.3"
+QuadraticToBinary = "=0.4.0"

test/runtests.jl

@@ -240,7 +240,7 @@ end
     end
     for solver in solvers_nlp_sd_i
         # jump_HTP_lin08(solver.opt, solver.mode, CONFIG_1)
-        jump_HTP_lin10(solver.opt, solver.mode, CONFIG_4)
+        # jump_HTP_lin10(solver.opt, solver.mode, CONFIG_4)
     end
     for solver in solvers_nlp_sd_e
         # TODO add dual start