Test primal solution used to compute subgradient in alpha self-adjust…

…ing procedure (#933)
atoptima · Jun 14, 2023 · c083d9d · c083d9d
1 parent f7b88de
commit c083d9d
Showing 1 changed file with 93 additions and 0 deletions.
diff --git a/test/unit/ColGen/colgen_stabilization.jl b/test/unit/ColGen/colgen_stabilization.jl
@@ -15,8 +15,101 @@ function test_misprice_schedule()
 end
 register!(unit_tests, "colgen_stabilization", test_misprice_schedule; f = true)
 
+form_primal_solution() = """
+    master
+        min
+        3x_11 + 2x_12 + 5x_13 + 2x_21 + x_22 +  x_23  + 4y1 + 3y2 + z1 + z2 + 0s1 + 0s2
+        s.t.
+        x_11  + x_12  + x_13  +  x_21 +                 y1 +  y2  + 2z1 + z2 >= 10
+        x_11  + 2x_12 +          x_21 + 2x_22 + 3x_23 + y1 +  2y2 + z1       <= 100
+        x_11  +         3x_13 +          x_22 +  x_23 + y1 +                 == 100
+                                                        y1 +      + z1  + z2 <= 5  
+        s1                                                                   >= 1 {MasterConvexityConstr}
+        s1                                                                   <= 2 {MasterConvexityConstr}
+        s2                                                                   >= 0 {MasterConvexityConstr}
+        s2                                                                   <= 3 {MasterConvexityConstr}
+
+    dw_sp
+        min
+        x_11 + x_12 + x_13 + y1 + 0s1
+        s.t.
+        x_11 + x_12 + x_13 + y1 >= 10
+
+    dw_sp
+        min
+        x_21 + x_22 + x_23 + y2 + 0s2
+        s.t.
+        x_21 + x_22 + x_23 + y2 >= 10
+        
+        integer
+            representatives
+                x_11, x_12, x_13, x_21, x_22, x_23, y1, y2
+
+            pure
+                z1, z2
+
+            pricing_setup
+                s1, s2
+        
+        bounds
+            x_11 >= 0
+            x_12 >= 0
+            x_13 >= 0
+            x_21 >= 0
+            x_22 >= 1
+            x_23 >= 0
+            1 <= y1 <= 2
+            3 <= y2 <= 6
+            z1 >= 0
+            z2 >= 3
+"""
+
+
 function test_primal_solution()
+    _, master, sps, _, _ = reformfromstring(form_primal_solution())
+
+    sp1, sp2 = sps[2], sps[1]
+
+    vids = get_name_to_varids(master)
+    cids = get_name_to_constrids(master)
+
+    pool = Coluna.Algorithm.ColumnsSet()
+
+    sol1 = Coluna.MathProg.PrimalSolution(
+        sp1,
+        [vids["x_11"], vids["x_12"], vids["x_13"], vids["y1"], vids["s1"]],
+        [1.0, 2.0, 3.0, 7.0, 1.0],
+        11.0,
+        Coluna.MathProg.FEASIBLE_SOL
+    )
+    Coluna.Algorithm.add_primal_sol!(pool.subprob_primal_sols, sol1, false) # improving = true
+
+    sol2 = Coluna.MathProg.PrimalSolution(
+        sp2,
+        [vids["x_21"], vids["x_22"], vids["x_23"], vids["y2"], vids["s2"]],
+        [4.0, 4.0, 5.0, 10.0, 1.0],
+        13.0,
+        Coluna.MathProg.FEASIBLE_SOL
+    )
+    Coluna.Algorithm.add_primal_sol!(pool.subprob_primal_sols, sol2, true)
+
+    primal_sol = Coluna.Algorithm._primal_solution(master, pool, true)
 
+    sp1_lb = 1.0
+    sp2_ub = 3.0
+    @test primal_sol[vids["x_11"]] == 1.0 * sp1_lb
+    @test primal_sol[vids["x_12"]] == 2.0 * sp1_lb
+    @test primal_sol[vids["x_13"]] == 3.0 * sp1_lb
+    @test primal_sol[vids["x_21"]] == 4.0 * sp2_ub
+    @test primal_sol[vids["x_22"]] == 4.0 * sp2_ub
+    @test primal_sol[vids["x_23"]] == 5.0 * sp2_ub
+    @test primal_sol[vids["y1"]] == 7.0 * sp1_lb
+    @test primal_sol[vids["y2"]] == 10.0 * sp2_ub
+    @test primal_sol[vids["s1"]] == 1.0 * sp1_lb
+    @test primal_sol[vids["s2"]] == 1.0 * sp2_ub
+    @test primal_sol[vids["z1"]] == 0.0 # TODO: not sure about this test
+    @test primal_sol[vids["z2"]] == 0.0 # TODO: not sure about this test
+    return
 end
 register!(unit_tests, "colgen_stabilization", test_primal_solution; f = true)