diff --git a/src/Cuts/tableau/gmi.jl b/src/Cuts/tableau/gmi.jl
index 600b912..86a17db 100644
--- a/src/Cuts/tableau/gmi.jl
+++ b/src/Cuts/tableau/gmi.jl
@@ -296,7 +296,7 @@ function compute_gmi(data::ProblemData, tableau::Tableau)::ConstraintSet
             end
         end
     end
-    
+
     @timeit "Resize arrays to actual size" begin
         resize!(lhs_I, nnz_count)
         resize!(lhs_J, nnz_count)
diff --git a/src/Cuts/tableau/gmi_dual.jl b/src/Cuts/tableau/gmi_dual.jl
index f897700..ec7a55d 100644
--- a/src/Cuts/tableau/gmi_dual.jl
+++ b/src/Cuts/tableau/gmi_dual.jl
@@ -271,7 +271,7 @@ function collect_gmi_FisSal2011(
     max_pool_size_mb = 1024,
     optimizer,
     silent_solver=true,
-    time_limit = 900,
+    time_limit = 3_600,
     variant = :fast,
 )
     variant in [:subg, :hybr, :fast, :faster] || error("unknown variant: $variant")
@@ -638,7 +638,8 @@ function collect_gmi_FisSal2011(
 
         if round == 1
             @printf(
-                "  %8s %10s %9s %9s %9s %9s %4s %8s %8s %8s\n",
+                "  %8s %8s %10s %9s %9s %9s %9s %4s %8s %8s %8s\n",
+                "time",
                 "round",
                 "obj",
                 "cl_curr",
@@ -659,8 +660,9 @@ function collect_gmi_FisSal2011(
         if log_should_print
             last_print_time = time()
             @printf(
-                "%c %8d %10.3e %9.2e %9.2e %9d %9.2f %4d %8.2e %8.2e %8.2e\n",
+                "%c %8.2f %8d %10.3e %9.2e %9.2e %9d %9.2f %4d %8.2e %8.2e %8.2e\n",
                 log_prefix,
+                time() - initial_time,
                 round,
                 obj_curr,
                 gapcl_curr,
diff --git a/src/Cuts/tableau/tableau.jl b/src/Cuts/tableau/tableau.jl
index b6bbfc0..961dc2c 100644
--- a/src/Cuts/tableau/tableau.jl
+++ b/src/Cuts/tableau/tableau.jl
@@ -73,47 +73,65 @@ function compute_tableau(
         factor = klu(sparse(lhs_b'))
     end
 
-    @timeit "Compute tableau" begin
-        @timeit "Initialize sparse arrays" begin
-            tableau_rhs = zeros(length(rows))
-            tableau_lhs_I = Int[]
-            tableau_lhs_J = Int[]
-            tableau_lhs_V = Float64[]
-
-            # Heuristic: 5% sparsity
-            estimated_nnz = max(div(length(rows) * ncols, 20), length(rows))
-            sizehint!(tableau_lhs_I, estimated_nnz)
-            sizehint!(tableau_lhs_J, estimated_nnz)
-            sizehint!(tableau_lhs_V, estimated_nnz)
+    @timeit "Initialize sparse arrays" begin
+        tableau_rhs::Array{Float64} = zeros(length(rows))
+        tableau_lhs_I::Array{Int} = Int[]
+        tableau_lhs_J::Array{Int} = Int[]
+        tableau_lhs_V::Array{Float64} = Float64[]
+        estimated_nnz::Int = length(rows) * ncols ÷ 20
+        sizehint!(tableau_lhs_I, estimated_nnz)
+        sizehint!(tableau_lhs_J, estimated_nnz)
+        sizehint!(tableau_lhs_V, estimated_nnz)
+        e::Array{Float64} = zeros(nrows)
+        sol::Array{Float64} = zeros(nrows)
+        tableau_row::Array{Float64} = zeros(ncols)
+    end
+
+    A = data.constr_lhs'
+    b = data.constr_ub
+
+    for k in eachindex(rows)
+        @timeit "Solve" begin
+            fill!(e, 0.0)
+            e[rows[k]] = 1.0
+            ldiv!(sol, factor, e)
         end
-        
-        for k in eachindex(rows)
-            @timeit "Prepare inputs" begin
-                i = rows[k]
-                e = zeros(nrows)
-                e[i] = 1.0
-            end
-            @timeit "Solve" begin
-                sol = factor \ e
-            end
-            @timeit "Compute row" begin
-                tableau_row = sol' * data.constr_lhs
-                tableau_rhs[k] = sol' * data.constr_ub
+
+        @timeit "Compute row" begin
+            mul!(tableau_row, A, sol)
+            tableau_rhs[k] = dot(sol, b)
+        end
+
+        needed_space = length(tableau_lhs_I) + ncols
+        if needed_space > estimated_nnz
+            @timeit "Grow arrays" begin
+                estimated_nnz *= 2
+                sizehint!(tableau_lhs_I, estimated_nnz)
+                sizehint!(tableau_lhs_J, estimated_nnz)
+                sizehint!(tableau_lhs_V, estimated_nnz)
             end
-            @timeit "Collect nonzeros" begin
-                for j in 1:ncols
-                    val = tableau_row[j]
-                    if abs(val) > tol
-                        push!(tableau_lhs_I, k)
-                        push!(tableau_lhs_J, j)
-                        push!(tableau_lhs_V, val)
-                    end
+        end
+
+        @timeit "Collect nonzeros" begin
+            for j in 1:ncols
+                val = tableau_row[j]
+                if abs(val) > tol
+                    push!(tableau_lhs_I, k)
+                    push!(tableau_lhs_J, j)
+                    push!(tableau_lhs_V, val)
                 end
             end
         end
-        @timeit "Build sparse matrix" begin
-            tableau_lhs = sparse(tableau_lhs_I, tableau_lhs_J, tableau_lhs_V, length(rows), ncols)
-        end
+    end
+
+    @timeit "Shrink arrays" begin
+        sizehint!(tableau_lhs_I, 0)
+        sizehint!(tableau_lhs_J, 0)
+        sizehint!(tableau_lhs_V, 0)
+    end
+
+    @timeit "Build sparse matrix" begin
+        tableau_lhs = sparse(tableau_lhs_I, tableau_lhs_J, tableau_lhs_V, length(rows), ncols)
     end
 
     @timeit "Compute tableau objective row" begin