Refactor to use _compute_point in all algorithms (#35)

Author: odow

src/MultiObjectiveAlgorithms.jl

@@ -488,6 +488,18 @@ end
 
 MOI.get(::Optimizer, ::MOI.DualStatus) = MOI.NO_SOLUTION
 
+function _compute_point(
+    model::Optimizer,
+    variables::Vector{MOI.VariableIndex},
+    f,
+)
+    X = Dict{MOI.VariableIndex,Float64}(
+        x => MOI.get(model.inner, MOI.VariablePrimal(), x) for x in variables
+    )
+    Y = MOI.Utilities.eval_variables(x -> X[x], f)
+    return X, Y
+end
+
 for file in readdir(joinpath(@__DIR__, "algorithms"))
     include(joinpath(@__DIR__, "algorithms", file))
 end

src/algorithms/EpsilonConstraint.jl

@@ -110,11 +110,7 @@ function optimize_multiobjective!(
         if MOI.get(model.inner, MOI.TerminationStatus()) != MOI.OPTIMAL
             break
         end
-        X = Dict{MOI.VariableIndex,Float64}(
-            x => MOI.get(model.inner, MOI.VariablePrimal(), x) for
-            x in variables
-        )
-        Y = MOI.Utilities.eval_variables(x -> X[x], model.f)
+        X, Y = _compute_point(model, variables, model.f)
         if isempty(solutions) || !(Y ≈ solutions[end].y)
             push!(solutions, SolutionPoint(X, Y))
         end

src/algorithms/Hierarchical.jl

@@ -107,11 +107,7 @@ function optimize_multiobjective!(algorithm::Hierarchical, model::Optimizer)
             break
         end
         # Add tolerance constraints
-        X = Dict{MOI.VariableIndex,Float64}(
-            x => MOI.get(model.inner, MOI.VariablePrimal(), x) for
-            x in variables
-        )
-        Y = MOI.Utilities.eval_variables(x -> X[x], new_vector_f)
+        X, Y = _compute_point(model, variables, new_vector_f)
         sense = MOI.get(model.inner, MOI.ObjectiveSense())
         for (i, fi) in enumerate(MOI.Utilities.eachscalar(new_vector_f))
             rtol = MOI.get(algorithm, ObjectiveRelativeTolerance(i))
@@ -123,10 +119,7 @@ function optimize_multiobjective!(algorithm::Hierarchical, model::Optimizer)
             push!(constraints, MOI.add_constraint(model, fi, set))
         end
     end
-    X = Dict{MOI.VariableIndex,Float64}(
-        x => MOI.get(model.inner, MOI.VariablePrimal(), x) for x in variables
-    )
-    Y = MOI.Utilities.eval_variables(x -> X[x], model.f)
+    X, Y = _compute_point(model, variables, model.f)
     # Remove tolerance constraints
     for c in constraints
         MOI.delete(model, c)

src/algorithms/KirlikSayin.jl

@@ -67,14 +67,6 @@ function _update_list(L::Vector{_Rectangle}, f::Vector{Float64})
     return L_new
 end
 
-function _compute_objective(model, variables, f)
-    X = Dict{MOI.VariableIndex,Float64}(
-        x => MOI.get(model.inner, MOI.VariablePrimal(), x) for x in variables
-    )
-    Y = MOI.Utilities.eval_variables(x -> X[x], f)
-    return X, Y
-end
-
 function _project(x::Vector{Float64}, axis::Int)
     return [x[i] for i in 1:length(x) if i != axis]
 end
@@ -114,7 +106,7 @@ function optimize_multiobjective!(algorithm::KirlikSayin, model::Optimizer)
         if MOI.get(model.inner, MOI.TerminationStatus()) != MOI.OPTIMAL
             return MOI.OTHER_ERROR, nothing
         end
-        _, Y = _compute_objective(model, variables, f_i)
+        _, Y = _compute_point(model, variables, f_i)
         yI[i] = Y
         MOI.set(
             model.inner,
@@ -125,7 +117,7 @@ function optimize_multiobjective!(algorithm::KirlikSayin, model::Optimizer)
         if MOI.get(model.inner, MOI.TerminationStatus()) != MOI.OPTIMAL
             return MOI.OTHER_ERROR, nothing
         end
-        _, Y = _compute_objective(model, variables, f_i)
+        _, Y = _compute_point(model, variables, f_i)
         yN[i] = Y
     end
     # Reset the sense after modifying it.
@@ -175,7 +167,7 @@ function optimize_multiobjective!(algorithm::KirlikSayin, model::Optimizer)
             _remove_rectangle(L, _Rectangle(_project(yI, k), uᵢ))
             continue
         end
-        X, Y = _compute_objective(model, variables, model.f)
+        X, Y = _compute_point(model, variables, model.f)
         Y_proj = _project(Y, k)
         if !(Y in YN)
             push!(solutions, SolutionPoint(X, Y))

src/algorithms/Lexicographic.jl

@@ -72,26 +72,16 @@ function _solve_in_sequence(
         if MOI.get(model.inner, MOI.TerminationStatus()) != MOI.OPTIMAL
             return MOI.OTHER_ERROR, nothing
         end
-        # Add tolerance constraints
-        X = Dict{MOI.VariableIndex,Float64}(
-            x => MOI.get(model.inner, MOI.VariablePrimal(), x) for
-            x in variables
-        )
-        Y = MOI.Utilities.eval_variables(x -> X[x], f)
-        sense = MOI.get(model.inner, MOI.ObjectiveSense())
+        X, Y = _compute_point(model, variables, f)
         rtol = MOI.get(algorithm, ObjectiveRelativeTolerance(i))
-        set = if sense == MOI.MIN_SENSE
+        set = if MOI.get(model.inner, MOI.ObjectiveSense()) == MOI.MIN_SENSE
             MOI.LessThan(Y + rtol * abs(Y))
         else
             MOI.GreaterThan(Y - rtol * abs(Y))
         end
         push!(constraints, MOI.add_constraint(model, f, set))
     end
-    X = Dict{MOI.VariableIndex,Float64}(
-        x => MOI.get(model.inner, MOI.VariablePrimal(), x) for x in variables
-    )
-    Y = MOI.Utilities.eval_variables(x -> X[x], model.f)
-    # Remove tolerance constraints
+    X, Y = _compute_point(model, variables, model.f)
     for c in constraints
         MOI.delete(model, c)
     end

src/algorithms/NISE.jl

@@ -45,11 +45,8 @@ function _solve_weighted_sum(model::Optimizer, ::NISE, weights::Vector{Float64})
     if status != MOI.OPTIMAL
         return status, nothing
     end
-    X = Dict{MOI.VariableIndex,Float64}(
-        x => MOI.get(model.inner, MOI.VariablePrimal(), x) for
-        x in MOI.get(model.inner, MOI.ListOfVariableIndices())
-    )
-    Y = MOI.Utilities.eval_variables(x -> X[x], model.f)
+    variables = MOI.get(model.inner, MOI.ListOfVariableIndices())
+    X, Y = _compute_point(model, variables, model.f)
     return status, SolutionPoint(X, Y)
 end