Merge pull request #817 from SciML/nomadcons

Add constraints support for NOMAD

Author: Vaibhavdixit02

lib/OptimizationNOMAD/src/OptimizationNOMAD.jl

@@ -7,8 +7,11 @@ using NOMAD, Optimization.SciMLBase
 export NOMADOpt
 struct NOMADOpt end
 
+@enum ConstraintBarrierType ExtremeBarrierMethod ProgressiveBarrierMethod
+
 SciMLBase.allowsbounds(::NOMADOpt) = true
 SciMLBase.allowscallback(::NOMADOpt) = false
+SciMLBase.allowsconstraints(::NOMADOpt) = true
 
 function __map_optimizer_args!(prob::OptimizationProblem, opt::NOMAD.NomadProblem;
         callback = nothing,
@@ -40,12 +43,14 @@ function __map_optimizer_args!(prob::OptimizationProblem, opt::NOMAD.NomadProble
     return nothing
 end
 
+@inline strcnsmethod(m::ConstraintBarrierType) = m === ExtremeBarrierMethod ? "EB" : "PB"
+
 function SciMLBase.__solve(prob::OptimizationProblem, opt::NOMADOpt;
         maxiters::Union{Number, Nothing} = nothing,
         maxtime::Union{Number, Nothing} = nothing,
         abstol::Union{Number, Nothing} = nothing,
         reltol::Union{Number, Nothing} = nothing,
-        progress = false,
+        cons_method = ExtremeBarrierMethod,
         kwargs...)
     local x
 
@@ -57,15 +62,27 @@ function SciMLBase.__solve(prob::OptimizationProblem, opt::NOMADOpt;
         return first(x)
     end
 
-    function bb(x)
-        l = _loss(x)
-        success = !isnan(l) && !isinf(l)
-        count_eval = true
-        return (success, count_eval, [l])
-    end
-
-    if !isnothing(prob.lcons) | !isnothing(prob.ucons)
-        @warn "Linear and nonlinear constraints defined in OptimizationProblem are currently not used by $(opt)"
+    if prob.f.cons === nothing
+        function bb(x)
+            l = _loss(x)
+            success = !isnan(l) && !isinf(l)
+            count_eval = true
+            return (success, count_eval, [l])
+        end
+    else
+        eqinds = findall(i -> prob.lcons[i] == prob.ucons[i], 1:length(prob.ucons))
+        function bbcons(x)
+            l = _loss(x)
+            c = zeros(eltype(x), length(prob.ucons))
+            prob.f.cons(c, x, prob.p)
+            c -= prob.ucons
+            if !isempty(eqinds)
+                c[eqinds] = abs.(c[eqinds])
+            end
+            success = !isnan(l) && !isinf(l)
+            count_eval = true
+            return (success, count_eval, vcat(l, c))
+        end
     end
 
     bounds = (;)
@@ -77,7 +94,13 @@ function SciMLBase.__solve(prob::OptimizationProblem, opt::NOMADOpt;
         bounds = (; bounds..., upper_bound = prob.ub)
     end
 
-    opt_setup = NOMAD.NomadProblem(length(prob.u0), 1, ["OBJ"], bb; bounds...)
+    if prob.f.cons === nothing
+        opt_setup = NOMAD.NomadProblem(length(prob.u0), 1, ["OBJ"], bb; bounds...)
+    else
+        opt_setup = NOMAD.NomadProblem(length(prob.u0), 1 + length(prob.ucons),
+            vcat("OBJ", fill(strcnsmethod(cons_method), length(prob.ucons))),
+            bbcons; bounds...)
+    end
 
     __map_optimizer_args!(prob, opt_setup, maxiters = maxiters, maxtime = maxtime,
         abstol = abstol, reltol = reltol; kwargs...)

lib/OptimizationNOMAD/test/runtests.jl

@@ -16,4 +16,19 @@ using Test
     prob = OptimizationProblem(f, x0, _p; lb = [-1.0, -1.0], ub = [1.5, 1.5])
     sol = Optimization.solve(prob, NOMADOpt())
     @test 10 * sol.objective < l1
+
+    cons = (res, x, p) -> (res[1] = x[1]^2 + x[2]^2; nothing)
+    f = OptimizationFunction(rosenbrock, cons = cons)
+    prob = OptimizationProblem(f, x0, _p; lcons = [-Inf], ucons = [1.0])
+    sol = Optimization.solve(prob, NOMADOpt(), maxiters = 5000)
+    @test 10 * sol.objective < l1
+
+    function con2_c(res, x, p)
+        res .= [x[1]^2 + x[2]^2, x[2] * sin(x[1]) - x[1]]
+    end
+
+    f = OptimizationFunction(rosenbrock, cons = con2_c)
+    prob = OptimizationProblem(f, x0, _p; lcons = [-Inf, -Inf], ucons = [0.5, 0.0])
+    sol = Optimization.solve(prob, NOMADOpt(), maxiters = 5000)
+    @test sol.objective < l1
 end