Add KNITRO@15 to CI

.github/workflows/ci.yml

@@ -11,17 +11,42 @@ permissions:
 jobs:
   test:
     name: 'KNITRO'
-    runs-on: 'ubuntu-latest'
+    runs-on: ${{ matrix.os }}
     strategy:
       fail-fast: false
       matrix:
-        version: ['1.10', '1']
+        include:
+         # Julia v1.10, Linux, KNITRO@15
+         - version: '1.10'
+           os: 'ubuntu-latest'
+           arch: 'x64'
+           KNITRO_JL_WHL: 'true'
+         # Julia v1, Linux, KNITRO@15
+         - version: '1'
+           os: 'ubuntu-latest'
+           arch: 'x64'
+           KNITRO_JL_WHL: 'true'
+         # Julia v1, macOS-aarch64, KNITRO@15
+         - version: '1'
+           os: macos-14
+           arch: aarch64
+           KNITRO_JL_WHL: 'true'
+         # Julia v1, Windows, KNITRO@15
+         - version: '1'
+           os: 'windows-latest'
+           arch: 'x64'
+           KNITRO_JL_WHL: 'true'
+         # Julia v1, Linux, KNITRO@14
+         - version: '1'
+           os: 'ubuntu-latest'
+           arch: 'x64'
+           KNITRO_JL_WHL: 'false'
     steps:
       - uses: actions/checkout@v4
       - uses: julia-actions/setup-julia@v2
         with:
           version: ${{ matrix.version }}
-          arch: 'x64'
+          arch: ${{ matrix.arch }}
       - uses: julia-actions/cache@v1
       - shell: bash
         env:
@@ -30,6 +55,7 @@ jobs:
           echo "$SECRET_KNITRO_LICENSE" > ~/artelys_lic.txt
       - uses: julia-actions/julia-buildpkg@v1
         env:
+          KNITRO_JL_WHL: ${{ matrix.KNITRO_JL_WHL }}
           SECRET_KNITRO_URL: ${{ secrets.KNITRO_URL }}
           SECRET_KNITRO_LIBIOMP5: ${{ secrets.KNITRO_LIBIOMP5 }}
       - uses: julia-actions/julia-runtest@v1

.gitignore

@@ -4,3 +4,4 @@ deps/lib*
 deps/artelys*
 deps/build.log
 test/*.mps
+deps/knitro*

deps/build.jl

@@ -1,4 +1,9 @@
-using Libdl, Base.Sys
+# Copyright (c) 2016: Ng Yee Sian, Miles Lubin, other contributors
+#
+# Use of this source code is governed by an MIT-style license that can be found
+# in the LICENSE.md file or at https://opensource.org/licenses/MIT.
+
+import Libdl
 
 const DEPS_FILE = joinpath(dirname(@__FILE__), "deps.jl")
 
@@ -41,16 +46,41 @@ function try_local_installation()
     return
 end
 
-function try_ci_installation()
+const WHEELS = Dict(
+    "linux" => "https://files.pythonhosted.org/packages/76/6e/ffe880b013ad244f0fd91940454e4f2bf16fa01e74c469e1b0fb75eda12a/knitro-15.0.0-py3-none-manylinux1_x86_64.whl",
+    "macos" => "https://files.pythonhosted.org/packages/76/66/936edcd2255055cf6c8a060d1beeb8ce543ef078dceb631caad22a20002a/knitro-15.0.0-py3-none-macosx_13_0_arm64.whl",
+    "windows" => "https://files.pythonhosted.org/packages/13/3f/54953373ee3b631640b33b5d4bdb0217bdb1f8514b9374b08348e098ea2a/knitro-15.0.0-py3-none-win_amd64.whl",
+)
+
+function try_wheel_installation()
+    libname, url = if Sys.islinux()
+        "libknitro.so", WHEELS["linux"]
+    elseif Sys.iswindows()
+        "knitro.dll", WHEELS["windows"]
+    elseif Sys.isapple()
+        "libknitro.dylib", WHEELS["macos"]
+    end
+    if !isdir(joinpath(@__DIR__, "knitro"))
+        run(`curl --output knitro.whl $url`)
+        run(`unzip knitro.whl`)
+    end
+    filename = joinpath(@__DIR__, "knitro", "lib", libname)
+    write_depsfile("", filename)
+    return
+end
+
+function try_secret_installation()
     local_filename = joinpath(@__DIR__, "libknitro.so")
     download(ENV["SECRET_KNITRO_URL"], local_filename)
     download(ENV["SECRET_KNITRO_LIBIOMP5"], joinpath(@__DIR__, "libiomp5.so"))
     write_depsfile("", local_filename)
     return
 end
 
-if get(ENV, "SECRET_KNITRO_URL", "") != ""
-    try_ci_installation()
+if get(ENV, "KNITRO_JL_WHL", "false") == "true"
+    try_wheel_installation()
+elseif get(ENV, "SECRET_KNITRO_URL", "") != ""
+    try_secret_installation()
 else
     try_local_installation()
 end

ext/KNITROMathOptInterfaceExt.jl

@@ -131,6 +131,7 @@
     constraint_mapping::Dict{MOI.ConstraintIndex,Union{Cint,Vector{Cint}}}
     license_manager::Union{KNITRO.LMcontext,Nothing}
     options::Dict{String,Any}
+    binary_variables::Vector{MOI.VariableIndex}
     # Cache for the solution
     x::Vector{Float64}
     lambda::Vector{Float64}
@@ -160,6 +161,7 @@
         Dict{MOI.ConstraintIndex,Union{Cint,Vector{Cint}}}(),
         license_manager,
         Dict{String,Any}(),
+        MOI.VariableIndex[],
         Float64[],
         Float64[],
         nothing,
@@ -201,6 +203,7 @@
     end
     empty!(model.x)
     empty!(model.lambda)
+    empty!(model.binary_variables)
     MOI.set(model, MOI.TimeLimitSec(), model.time_limit_sec)
     return
 end
@@ -276,20 +279,28 @@
     model.time_limit_sec = value
     # By default, maxtime is set to 1e8 in Knitro.
     limit = something(value, 1e8)
-    # KNITRO does not have a single option to control the global time limit, so
-    # we set various options.
-    # MAXTIME_REAL is the base option, which applies if the problem is a NLP.
-    KNITRO.@_checked KNITRO.KN_set_double_param(
-        model.inner,
-        KNITRO.KN_PARAM_MAXTIMEREAL,
-        limit,
-    )
-    # MIP_MAXTIME_REAL applies if the problem is a MINLP
-    KNITRO.@_checked KNITRO.KN_set_double_param(
-        model.inner,
-        KNITRO.KN_PARAM_MIP_MAXTIMEREAL,
-        limit,
-    )
+    if KNITRO.knitro_version() >= v"15.0"
+        KNITRO.@_checked KNITRO.KN_set_double_param(
+            model.inner,
+            KNITRO.KN_PARAM_MAXTIME,
+            limit,
+        )
+    else
+        # KNITRO does not have a single option to control the global time limit, so
+        # we set various options.
+        # MAXTIME_REAL is the base option, which applies if the problem is a NLP.
+        KNITRO.@_checked KNITRO.KN_set_double_param(
+            model.inner,
+            KNITRO.KN_PARAM_MAXTIMEREAL,
+            limit,
+        )
+        # MIP_MAXTIME_REAL applies if the problem is a MINLP
+        KNITRO.@_checked KNITRO.KN_set_double_param(
+            model.inner,
+            KNITRO.KN_PARAM_MIP_MAXTIMEREAL,
+            limit,
+        )
+    end
     return
 end
 
@@ -675,29 +686,12 @@
 
 function MOI.add_constraint(model::Optimizer, x::MOI.VariableIndex, ::MOI.ZeroOne)
     MOI.throw_if_not_valid(model, x)
-    lb, ub = nothing, nothing
-    p = Ref{Cdouble}(NaN)
-    if model.variable_info[x.value].has_lower_bound
-        KNITRO.@_checked KNITRO.KN_get_var_lobnd(model.inner, _c_column(x), p)
-        lb = max(0.0, p[])
-    end
-    if model.variable_info[x.value].has_upper_bound
-        KNITRO.@_checked KNITRO.KN_get_var_upbnd(model.inner, _c_column(x), p)
-        ub = min(1.0, p[])
-    end
     KNITRO.@_checked KNITRO.KN_set_var_type(
         model.inner,
         _c_column(x),
-        KNITRO.KN_VARTYPE_BINARY,
+        KNITRO.KN_VARTYPE_INTEGER,
     )
-    # Calling `set_var_type` resets variable bounds in KNITRO. To fix, we need
-    # to restore them after calling `set_var_type`.
-    if lb !== nothing
-        KNITRO.@_checked KNITRO.KN_set_var_lobnd(model.inner, _c_column(x), lb)
-    end
-    if ub !== nothing
-        KNITRO.@_checked KNITRO.KN_set_var_upbnd(model.inner, _c_column(x), ub)
-    end
+    push!(model.binary_variables, x)
     ci = MOI.ConstraintIndex{MOI.VariableIndex,MOI.ZeroOne}(x.value)
     model.constraint_mapping[ci] = convert(Cint, x.value)
     return ci
@@ -1398,7 +1392,19 @@
            !isa(model.objective, MOI.ScalarNonlinearFunction)
         _add_objective(model, model.objective)
     end
+    # Update binary variable bounds
+    binary_cols = _c_column.(model.binary_variables)
+    nV = length(binary_cols)
+    lb, ub, tmp = zeros(Cdouble, nV), zeros(Cdouble, nV), zeros(Cdouble, nV)
+    KNITRO.@_checked KNITRO.KN_get_var_lobnds(model.inner, nV, binary_cols, lb)
+    KNITRO.@_checked KNITRO.KN_get_var_upbnds(model.inner, nV, binary_cols, ub)
+    tmp .= max.(lb, 0.0)
+    KNITRO.@_checked KNITRO.KN_set_var_lobnds(model.inner, nV, binary_cols, tmp)
+    tmp .= min.(ub, 1.0)
+    KNITRO.@_checked KNITRO.KN_set_var_upbnds(model.inner, nV, binary_cols, tmp)
     KNITRO.KN_solve(model.inner)
+    KNITRO.@_checked KNITRO.KN_set_var_lobnds(model.inner, nV, binary_cols, lb)
+    KNITRO.@_checked KNITRO.KN_set_var_upbnds(model.inner, nV, binary_cols, ub)
     model.number_solved += 1
     return
 end

test/C_wrapper.jl

@@ -159,14 +159,15 @@ end
     _to_string(x) = GC.@preserve(x, unsafe_string(pointer(x)))
     @test _to_string(tmp) == "xtol"
     KN_get_param_doc(kc, KN_PARAM_XTOL, tmp, 1024)
+    header = KNITRO.knitro_version() >= v"15" ? "" : "# "
     @test _to_string(tmp) ==
-          "# Step size tolerance used for terminating the optimization.\n"
+          "$(header)Step size tolerance used for terminating the optimization.\n"
     KN_get_param_type(kc, KN_PARAM_XTOL, pCint)
     @test pCint[] == KN_PARAMTYPE_FLOAT
     KN_get_num_param_values(kc, KN_PARAM_XTOL, pCint)
     @test pCint[] == 0
     KN_get_param_value_doc(kc, KN_PARAM_GRADOPT, 1, tmp, 1024)
-    @test _to_string(tmp) == "exact"
+    @test occursin("exact", _to_string(tmp))
     KN_get_param_id(kc, "xtol", pCint)
     @test pCint[] == KN_PARAM_XTOL
 
@@ -276,20 +277,20 @@ end
     @test pCint[] >= 0
     pCdouble = Ref{Cdouble}()
     KN_get_abs_feas_error(kc, pCdouble)
-    @test pCdouble[] < 1e-10
+    @test pCdouble[] < 1e-6
     KN_get_rel_feas_error(kc, pCdouble)
-    @test pCdouble[] < 1e-10
+    @test pCdouble[] < 1e-6
     KN_get_abs_opt_error(kc, pCdouble)
-    @test pCdouble[] < 1e-7
+    @test pCdouble[] < 1e-4
     KN_get_rel_opt_error(kc, pCdouble)
-    @test pCdouble[] < 1e-8
+    @test pCdouble[] < 1e-6
     KN_get_con_value(kc, 0, pCdouble)
-    @test pCdouble[] ≈ 3.96
+    @test ≈(pCdouble[], 3.96; atol=1e-4)
     nStatus, objSol, x, lambda_ = KN_get_solution(kc)
     @test nStatus == 0
-    @test x ≈ [0.0, 2.0, 1.98]
+    @test ≈(x, [0.0, 2.0, 1.98]; atol=1e-4)
 
-    @test objSol ≈ 31.363199 atol = 1e-5
+    @test objSol ≈ 31.363 atol = 1e-3
 
     # Test getters for primal and dual variables
     if KNITRO.knitro_version() >= v"12.0"
@@ -499,7 +500,7 @@ end
     KN_set_obj_name(kc, "myobj")
     # Set feasibility tolerances
     KN_set_var_feastols_all(kc, [0.1, 0.001, 0.1])
-    KN_set_con_feastols_all(kc, [0.1])
+    KN_set_con_feastols_all(kc, [1e-4])
     KN_set_compcon_feastols_all(kc, [0.1])
     # Set finite differences step size
     KN_set_cb_relstepsizes_all(kc, cb, [0.1, 0.001, 0.1])
@@ -880,7 +881,7 @@ end
     for x in xIndices
         KN_set_var_primal_init_value(kc, x, 0.8)
     end
-
+    KN_set_var_lobnd(kc, 2, 0.0)
     # Add the constraints and set the rhs and coefficients
     KN_add_cons(kc, 3, zeros(Cint, 3))
     KN_set_con_eqbnds_all(kc, [1.0, 0.0, 0.0])