add tests

src/decomposition.jl

@@ -472,6 +472,9 @@ function buildformulations!(
 end
 
 function reformulate!(prob::Problem, annotations::Annotations, env::Env)
+    if getcoefmatrix(prob.original_formulation).fillmode
+        closefillmode!(getcoefmatrix(prob.original_formulation))
+    end
     decomposition_tree = annotations.tree
     if decomposition_tree !== nothing
         root = BD.getroot(decomposition_tree)

src/optimize.jl

@@ -50,13 +50,14 @@ function optimize!(prob::MathProg.Problem, annotations::Annotations, params::Par
 
     env = Env(params)
 
-    if getcoefmatrix(prob.original_formulation).fillmode
-        closefillmode!(getcoefmatrix(prob.original_formulation))
-    end
-
     # Apply decomposition
     reformulate!(prob, annotations, env)
 
+    if prob.re_formulation != nothing
+        @show prob.re_formulation.master
+        @show prob.re_formulation.master.optimizer.inner
+    end
+
     # Coluna ready to start
     set_optim_start_time!(env)
     @logmsg LogLevel(-1) "Coluna ready to start."
@@ -67,6 +68,8 @@ function optimize!(prob::MathProg.Problem, annotations::Annotations, params::Par
     end
 
     env.kpis.elapsed_optimization_time = elapsed_optim_time(env)
+    prob.re_formulation = nothing
+    prob.form_counter = Counter(0)
 
     println(_to)
     TO.reset_timer!(_to)

test/issues_tests.jl

@@ -121,12 +121,28 @@ function optimize_twice()
     @objective(model, Max, x)
     @test optimize!(model) == optimize!(model)
 
-    coluna = JuMP.optimizer_with_attributes(
+    model = BlockModel(coluna, direct_model = true)
+    @variable(model, x)
+    @constraint(model, x <= 1)
+    @objective(model, Max, x)
+    @test optimize!(model) == optimize!(model)
+
+    coluna = optimizer_with_attributes(
         Coluna.Optimizer,
-        "params" => CL.Params(solver = ClA.SolveIpForm()),
+        "params" => Coluna.Params(
+            solver = Coluna.Algorithm.TreeSearchAlgorithm()
+        ),
         "default_optimizer" => GLPK.Optimizer
     )
+    @axis(M, 1:20)
+    model = BlockModel(coluna)
+    @variable(model, x[m in M], Bin)
+    @dantzig_wolfe_decomposition(model, decomposition, M)
+    @test optimize!(model) == optimize!(model)
+
     model = BlockModel(coluna, direct_model = true)
+    @variable(model, x[m in M], Bin)
+    @dantzig_wolfe_decomposition(model, decomposition, M)
     @test optimize!(model) == optimize!(model)
 end