Implementation of Problem 13

Author: arnavk23

src/ADNLPProblems/browngen2.jl

@@ -0,0 +1,14 @@
+export browngen2
+
+function browngen2(; n::Int = default_nvar, type::Type{T} = Float64, kwargs...) where {T}
+  n = max(2, n)
+  function f(x; n = length(x))
+    s = zero(T)
+    @inbounds for i = 2:n
+      s += abs(x[i-1])^(x[i]^2 + one(T)) + abs(x[i])^(x[i-1]^2 + one(T))
+    end
+    return s
+  end
+  x0 = [isodd(i) ? -one(T) : one(T) for i in 1:n]
+  return ADNLPModels.ADNLPModel(f, x0, name = "browngen2"; kwargs...)
+end

src/Meta/browngen2.jl

@@ -0,0 +1,27 @@
+browngen2_meta = Dict(
+  :nvar => 100,
+  :variable_nvar => true,
+  :ncon => 0,
+  :variable_ncon => false,
+  :minimize => true,
+  :name => "browngen2",
+  :has_equalities_only => false,
+  :has_inequalities_only => false,
+  :has_bounds => false,
+  :has_fixed_variables => false,
+  :objtype => :other,
+  :contype => :unconstrained,
+  :best_known_lower_bound => -Inf,
+  :best_known_upper_bound => Inf,
+  :is_feasible => missing,
+  :defined_everywhere => missing,
+  :origin => :literature,
+)
+
+get_browngen2_nvar(; n::Integer = default_nvar, kwargs...) = n
+get_browngen2_ncon(; n::Integer = default_nvar, kwargs...) = 0
+get_browngen2_nlin(; n::Integer = default_nvar, kwargs...) = 0
+get_browngen2_nnln(; n::Integer = default_nvar, kwargs...) = 0
+get_browngen2_nequ(; n::Integer = default_nvar, kwargs...) = 0
+get_browngen2_nineq(; n::Integer = default_nvar, kwargs...) = 0
+get_browngen2_nls_nequ(; n::Integer = default_nvar, kwargs...) = 0

src/PureJuMP/browngen1.jl

@@ -1,4 +1,4 @@
-# Generalization of the Brown function
+# Generalization of the Brown function 1
 #
 #   Problem 12 in
 #   L. Luksan, C. Matonoha and J. Vlcek

src/PureJuMP/browngen2.jl

@@ -0,0 +1,24 @@
+# Generalization of the Brown function 2
+#
+#   Problem 13 in
+#   L. Luksan, C. Matonoha and J. Vlcek
+#   Sparse Test Problems for Unconstrained Optimization,
+#   Technical Report 1064,
+#   Institute of Computer Science,
+#   Academy of Science of the Czech Republic
+#
+#   https://www.researchgate.net/publication/325314400_Sparse_Test_Problems_for_Unconstrained_Optimization
+export browngen2
+
+function browngen2(; n::Int = default_nvar)
+  nlp = Model()
+  @variable(nlp, x[1:n])
+  for i in 1:n
+    set_start_value(x[i], isodd(i) ? -1.0 : 1.0)
+  end
+
+  @objective(nlp, Min,
+    sum(abs(x[i-1])^(x[i]^2 + 1) + abs(x[i])^(x[i-1]^2 + 1) for i = 2:n)
+  )
+  return nlp
+end