Add gulf (#257)

src/ADNLPProblems/gulf.jl

@@ -0,0 +1,28 @@
+export gulf
+
+function gulf(;use_nls::Bool = false, kwargs...)
+  model = use_nls ? :nls : :nlp
+  return gulf(Val(model); kwargs...)
+end
+
+function gulf(::Val{:nlp}; n::Int = default_nvar, type::Val{T} = Val(Float64), m::Int = 100, kwargs...) where {T}
+  m = min(m, 100)
+  function f(x; m = m)
+    return 1 // 2 * sum((exp(-abs((25 + (-50 * log(i * one(T) / 100))^(2 // 3)) * m * i * x[2])^x[3] / x[1]) - i // 100)^2 for i=1:m)
+  end
+  x0 = T[5, 2.5, 0.15]
+  return ADNLPModels.ADNLPModel(f, x0, name = "gulf"; kwargs...)
+end
+
+function gulf(::Val{:nls}; n::Int = default_nvar, type::Val{T} = Val(Float64), m::Int = 100, kwargs...) where {T}
+  m = min(m, 100)
+
+  function F!(r, x; m = m)
+    for i=1:n
+      r[i] = exp(-abs((25 + (-50 * log(i * one(T) / 100))^(2 // 3)) * m * i * x[2])^x[3] / x[1]) - i // 100
+    end
+    return r
+  end
+  x0 = T[5, 2.5, 0.15]
+  return ADNLPModels.ADNLSModel!(F!, x0, m, name = "gulf-nls"; kwargs...)
+end

src/Meta/gulf.jl

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+gulf_meta = Dict(
+  :nvar => 3,
+  :variable_nvar => true,
+  :ncon => 0,
+  :variable_ncon => false,
+  :minimize => true,
+  :name => "gulf",
+  :has_equalities_only => false,
+  :has_inequalities_only => false,
+  :has_bounds => false,
+  :has_fixed_variables => false,
+  :objtype => :least_squares,
+  :contype => :unconstrained,
+  :best_known_lower_bound => -Inf,
+  :best_known_upper_bound => 0.0,
+  :is_feasible => true,
+  :defined_everywhere => missing,
+  :origin => :unknown,
+)
+get_gulf_nvar(; n::Integer = default_nvar, kwargs...) = 3
+get_gulf_ncon(; n::Integer = default_nvar, kwargs...) = 0
+get_gulf_nlin(; n::Integer = default_nvar, kwargs...) = 0
+get_gulf_nnln(; n::Integer = default_nvar, kwargs...) = 0
+get_gulf_nequ(; n::Integer = default_nvar, kwargs...) = 0
+get_gulf_nineq(; n::Integer = default_nvar, kwargs...) = 0
+get_gulf_nls_nequ(; n::Integer = default_nvar, m = 100, kwargs...) = m

src/PureJuMP/gulf.jl

@@ -0,0 +1,34 @@
+#   The Gulf research and development function for m = 99. 
+#
+#   Source: problem 11 in
+#      J.J. More', B.S. Garbow and K.E. Hillstrom,
+#      "Testing Unconstrained Optimization Software",
+#      ACM Transactions on Mathematical Software, vol. 7(1), pp. 17-41, 1981.
+#   Also problem 27 (p. 57) in
+#      A.R. Buckley,
+#      "Test functions for unconstrained minimization",
+#      TR 1989CS-3, Mathematics, statistics and computing centre,
+#      Dalhousie University, Halifax (CDN), 1989.
+#
+#   SUR2-MN-3-0
+
+export gulf
+
+"Linear function with `n` parameters and `m` observations  - full rank"
+function gulf(args...; n::Int = default_nvar, m::Int = 100, kwargs...)
+  n = 3
+  m = min(m, 100)
+
+  nlp = Model()
+
+  @variable(nlp, x[j = 1:n])
+  set_start_value.(x, [5, 2.5, 0.15])
+
+  @NLobjective(
+    nlp,
+    Min,
+    0.5 * sum((exp(-abs((25 + (-50 * log(i / 100))^(2 / 3)) * m * i * x[2])^x[3] / x[1]) - i / 100)^2 for i=1:m)
+  )
+
+  return nlp
+end