Fix floating point comparison in TambyVanderpooten

Author: odow

src/algorithms/TambyVanderpooten.jl

@@ -187,12 +187,12 @@ function minimize_multiobjective!(
         bounds_to_remove = Vector{Float64}[]
         for u_i in keys(U_N)
             for k in 1:n
-                if u_i[k] == yI[k]
+                if isapprox(u_i[k], yI[k]; atol = 1e-6)
                     push!(bounds_to_remove, u_i)
                 else
                     for (u_j, y_j) in V[k]
                         if all(_project(u_i, k) .<= _project(u_j, k)) &&
-                           (y_j[k] == u_i[k])
+                           isapprox(y_j[k], u_i[k]; atol = 1e-6)
                             push!(bounds_to_remove, u_i)
                         end
                     end
@@ -205,6 +205,6 @@ function minimize_multiobjective!(
             end
         end
     end
-    solutions = [SolutionPoint(X, Y) for (Y, X) in solutions]
-    return status, solutions
+    solutions_vec = [SolutionPoint(X, Y) for (Y, X) in solutions]
+    return status, filter_nondominated(MOI.MIN_SENSE, solutions_vec)
 end

test/problems.jl

@@ -472,4 +472,31 @@ function test_issue_122(model)
     return
 end
 
+function test_issue_133()
+    #!format: off
+    p = Float64[
+        33 90 96 75 1 69 100 50 63 61 59 95 58 10 77 30 86 89 82 51 38 33 73 54 91 89 95 82 48 67
+        55 36 80 58 20 96 75 57 24 68 37 58 8 85 27 25 71 53 47 72 57 64 1 8 12 68 3 80 20 90
+        22 40 50 73 44 65 12 26 13 77 14 68 71 35 54 98 45 95 98 19 18 38 14 51 37 48 35 97 95 36
+    ]
+    w = Float64[
+        22, 13, 10, 25, 4, 15, 17, 15, 15, 28, 14, 13, 2, 23, 6, 22, 18, 6, 23,
+        21, 7, 7, 14, 4, 3, 27, 10, 5, 9, 10
+    ]
+    #!format: on
+    model = MOA.Optimizer(HiGHS.Optimizer)
+    MOI.set(model, MOA.Algorithm(), MOA.TambyVanderpooten())
+    MOI.set(model, MOI.Silent(), true)
+    x = MOI.add_variables(model, length(w))
+    MOI.add_constraint.(model, x, MOI.ZeroOne())
+    MOI.set(model, MOI.ObjectiveSense(), MOI.MAX_SENSE)
+    f = MOI.Utilities.vectorize(p * x)
+    MOI.set(model, MOI.ObjectiveFunction{typeof(f)}(), f)
+    MOI.add_constraint(model, w' * x, MOI.LessThan(204.0))
+    MOI.optimize!(model)
+    @test MOI.get(model, MOI.TerminationStatus()) == MOI.OPTIMAL
+    @test MOI.get(model, MOI.ResultCount()) == 95
+    return
+end
+
 end  # module Problems