Implement full recourse; remove feasibility cuts

src/model/build.jl

@@ -24,6 +24,7 @@ function build_model(
     probs::Vector{Float64};
     optimizer,
     method=:ef,
+    tol=0.1,
 )
     T = instance.time
 
@@ -118,6 +119,13 @@ function build_model(
                 upper_bound = graph.collection_shipping_nodes[n].location.amount[t],
             )
 
+            # Var: collection_shortfall
+            @recourse(
+                model,
+                collection_shortfall[n in 1:CSN, t in 1:T],
+                lower_bound = 0,
+            )
+
             # Var: store
             @recourse(
                 model,
@@ -209,6 +217,11 @@ function build_model(
                     csn[n].location.product.disposal_cost[t] * collection_dispose[n, t]
                     for n in 1:CSN
                     for t in 1:T
+                ) + sum(
+                    # Collection shortfall
+                    1e4 * collection_shortfall[n, t]
+                    for n in 1:CSN
+                    for t in 1:T
                 )
             )
 
@@ -280,7 +293,7 @@ function build_model(
                 sum(
                     flow[arc.index, t]
                     for arc in csn[n].outgoing_arcs
-                ) == csn[n].location.amount[t] - collection_dispose[n, t]
+                ) == csn[n].location.amount[t] - collection_dispose[n, t] - collection_shortfall[n, t]
             )
 
             # Material flow at plant shipping nodes
@@ -323,7 +336,7 @@ function build_model(
         sp = instantiate(model, ξ; optimizer=LShaped.Optimizer)
         set_optimizer_attribute(sp, MasterOptimizer(), optimizer)
         set_optimizer_attribute(sp, SubProblemOptimizer(), optimizer)
-        set_optimizer_attribute(sp, FeasibilityStrategy(), FeasibilityCuts())
+        set_optimizer_attribute(sp, RelativeTolerance(), tol)
     else
         error("unknown method: $method")
     end

src/model/solve.jl

@@ -29,6 +29,8 @@ function solve_stochastic(;
     scenarios::Vector{String},
     probs::Vector{Float64},
     optimizer,
+    method=:ef,
+    tol=0.1,
 )
     @info "Reading instance files..."
     instances = [parsefile(sc) for sc in scenarios]
@@ -37,7 +39,7 @@ function solve_stochastic(;
     graphs = [build_graph(inst) for inst in instances]
 
     @info "Building stochastic model..."
-    sp = RELOG.build_model(instances[1], graphs, probs; optimizer)
+    sp = RELOG.build_model(instances[1], graphs, probs; optimizer, method, tol)
 
     @info "Optimizing stochastic model..."
     optimize!(sp)

test/model/solve_test.jl

@@ -40,13 +40,13 @@ function model_solve_test()
         solution = RELOG.solve(fixture("instances/s1.json"), heuristic = true)
     end
 
-    @testset "solve (infeasible)" begin
-        json = JSON.parsefile(fixture("instances/s1.json"))
-        for (location_name, location_dict) in json["products"]["P1"]["initial amounts"]
-            location_dict["amount (tonne)"] *= 1000
-        end
-        @test_throws ErrorException("No solution available") RELOG.solve(RELOG.parse(json))
-    end
+    # @testset "solve (infeasible)" begin
+    #     json = JSON.parsefile(fixture("instances/s1.json"))
+    #     for (location_name, location_dict) in json["products"]["P1"]["initial amounts"]
+    #         location_dict["amount (tonne)"] *= 1000
+    #     end
+    #     @test_throws ErrorException("No solution available") RELOG.solve(RELOG.parse(json))
+    # end
 
     @testset "solve (with storage)" begin
         basedir = dirname(@__FILE__)
@@ -75,7 +75,11 @@ function model_solve_test()
                 fixture("instances/case3_p010_s1.25.json"),
             ],
             probs=[0.5, 0.5],
-            optimizer=HiGHS.Optimizer,
+            optimizer=optimizer_with_attributes(
+                HiGHS.Optimizer,
+                "log_to_console" => false,
+            ),
+            method=:lshaped,
         )
     end
 end