add test for a simple quadratic function

src/solver.jl

@@ -368,7 +368,7 @@ function armijo_line_search(f, x, d, fx, xmin, xmax; α0 = 1.0, β = 0.5, c = 1e
 end
 
 """
-    _coordinate_descent!(s, x)
+    _coordinate_descent_move!(s, x)
 
 Runs an iteration of coordinate descent over axis "x".
 The derivative is (temporarily?) computed via finite difference.
@@ -412,6 +412,7 @@ function _step!(s)
     x = _select_worse(s)
     _verbose(s, "Selected x = $x")
 
+    # TODO: this if statement is currently not working, every variable is treated as integer 
     if get_domain(s, x) isa ContinuousDomain
         # We perform coordinate descent over the variable axis
         best_values, best_swap, tabu = _coordinate_descent_move!(s, x)

test/raw_solver.jl

@@ -1,5 +1,3 @@
-using Intervals
-
 function mincut(graph; source, sink, interdiction = 0)
     m = model(; kind = :cut)
     n = size(graph, 1)
@@ -117,6 +115,20 @@ function chemical_equilibrium(A, B, C)
     return m
 end
 
+function sum_squares(n)
+    m = model(; kind = :sum_squares)
+
+    d = domain(-10.0 .. 10.0)
+
+    foreach(_ -> variable!(m, d), 1:n)
+
+    ss = x -> sum(j -> j * x[j] * x[j], 1:n)
+
+    objective!(m, ss)
+
+    return m
+end
+
 @testset "Raw solver: internals" begin
     models = [
         sudoku(2)
@@ -248,3 +260,13 @@ end
     display(solution(s))
     display(s.time_stamps)
 end
+
+@testset "Raw solver: sum squares" begin
+    # Sanity check: simple quadratic function with a trivial minimum at 0
+    n = 10
+    m = sum_squares(n)
+    s = solver(m; options = Options(print_level = :minimal))
+    solve!(s)
+    display(solution(s))
+    display(s.time_stamps)
+end

test/runtests.jl

@@ -4,6 +4,7 @@ import ConstraintDomains
 import CompositionalNetworks
 @everywhere using Constraints
 using Dictionaries
+using Intervals
 @everywhere using LocalSearchSolvers
 using Test
 using TestItemRunner