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Fixed KS and TV #107

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Fixed KS and TV #107

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124da84
Fixed ideal points for KS and TV and the selection and update procedu…
kofgokhan Jun 10, 2025
a0c2416
Fixed formatting
kofgokhan Jun 10, 2025
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4 changes: 2 additions & 2 deletions src/algorithms/KirlikSayin.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -111,7 +111,7 @@ function optimize_multiobjective!(algorithm::KirlikSayin, model::Optimizer)
return status, nothing
end
_, Y = _compute_point(model, variables, f_i)
yI[i] = Y + 1
yI[i] = Y
model.ideal_point[i] = Y
MOI.set(
model.inner,
Expand All @@ -125,7 +125,7 @@ function optimize_multiobjective!(algorithm::KirlikSayin, model::Optimizer)
return status, nothing
end
_, Y = _compute_point(model, variables, f_i)
yN[i] = Y
yN[i] = Y + 1
end
# Reset the sense after modifying it.
MOI.set(model.inner, MOI.ObjectiveSense(), sense)
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38 changes: 21 additions & 17 deletions src/algorithms/TambyVanderpooten.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -30,19 +30,20 @@ function _update_search_region(
y::Vector{Float64},
yN::Vector{Float64},
)
bounds_to_remove = Vector{Float64}[]
p = length(y)
bounds_to_remove = Vector{Float64}[]
bounds_to_add = Dict{Vector{Float64},Vector{Vector{Vector{Float64}}}}()
for u in keys(U_N)
if all(y .< u)
push!(bounds_to_remove, u)
for l in 1:p
u_l = _get_child(u, y, l)
N = [
k != l ? [yi for yi in U_N[u][k] if yi[l] < y[l]] : [y]
k == l ? [y] : [yi for yi in U_N[u][k] if yi[l] < y[l]]
for k in 1:p
]
if all(!isempty(N[k]) for k in 1:p if u_l[k] ≠ yN[k])
U_N[u_l] = N
if all(!isempty(N[k]) for k in 1:p if k != l && u_l[k] != yN[k])
bounds_to_add[u_l] = N
end
end
else
Expand All @@ -53,27 +54,31 @@ function _update_search_region(
end
end
end
for bound_to_remove in bounds_to_remove
delete!(U_N, bound_to_remove)
for u in bounds_to_remove
delete!(U_N, u)
end
merge!(U_N, bounds_to_add)
return
end

function _get_child(u::Vector{Float64}, y::Vector{Float64}, k::Int)
@assert length(u) == length(y)
return vcat(u[1:k-1], y[k], u[k+1:length(y)])
return vcat(u[1:(k-1)], y[k], u[(k+1):length(y)])
end

function _select_search_zone(
U_N::Dict{Vector{Float64},Vector{Vector{Vector{Float64}}}},
yI::Vector{Float64},
yN::Vector{Float64},
)
i, j =
argmax([
prod(_project(u, k) - _project(yI, k)) for k in 1:length(yI),
u in keys(U_N)
]).I
return i, collect(keys(U_N))[j]
upper_bounds = collect(keys(U_N))
p = length(yI)
hvs = [
u[k] == yN[k] ? 0.0 : prod(_project(u, k) .- _project(yI, k)) for
k in 1:p, u in upper_bounds
]
k_star, j_star = argmax(hvs).I
return k_star, upper_bounds[j_star]
end

function optimize_multiobjective!(
Expand All @@ -100,7 +105,6 @@ function optimize_multiobjective!(
warm_start_supported = true
end
solutions = Dict{Vector{Float64},Dict{MOI.VariableIndex,Float64}}()
YN = Vector{Float64}[]
variables = MOI.get(model.inner, MOI.ListOfVariableIndices())
n = MOI.output_dimension(model.f)
yI, yN = zeros(n), zeros(n)
Expand All @@ -114,7 +118,7 @@ function optimize_multiobjective!(
return status, nothing
end
_, Y = _compute_point(model, variables, f_i)
yI[i] = Y + 1
yI[i] = Y
model.ideal_point[i] = Y
MOI.set(model.inner, MOI.ObjectiveSense(), MOI.MAX_SENSE)
MOI.optimize!(model.inner)
Expand All @@ -124,7 +128,7 @@ function optimize_multiobjective!(
return status, nothing
end
_, Y = _compute_point(model, variables, f_i)
yN[i] = Y
yN[i] = Y + 1
end
MOI.set(model.inner, MOI.ObjectiveSense(), MOI.MIN_SENSE)
U_N = Dict{Vector{Float64},Vector{Vector{Vector{Float64}}}}()
Expand All @@ -136,7 +140,7 @@ function optimize_multiobjective!(
status = MOI.TIME_LIMIT
break
end
k, u = _select_search_zone(U_N, yI)
k, u = _select_search_zone(U_N, yI, yN)
MOI.set(
model.inner,
MOI.ObjectiveFunction{typeof(scalars[k])}(),
Expand Down
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