Debug model; improve reports

src/RELOG.jl

@@ -1,5 +1,7 @@
 module RELOG
 
+_round(x::Number) = round(x, digits = 5)
+
 include("instance/structs.jl")
 include("instance/parse.jl")
 include("model/jumpext.jl")

src/model/build.jl

@@ -119,12 +119,16 @@ function build_model(instance::Instance; optimizer, variable_names::Bool = false
 
     # Transportation cost
     for (p1, p2, m) in E, t in T
-        add_to_expression!(obj, distances[p1, p2, m], y[p1.name, p2.name, m.name, t])
+        add_to_expression!(
+            obj,
+            distances[p1, p2, m] * m.tr_cost[t],
+            y[p1.name, p2.name, m.name, t],
+        )
     end
 
     # Center: Revenue
     for c in centers, (p, m) in E_in[c], t in T
-        add_to_expression!(obj, c.revenue[t], y[p.name, c.name, m.name, t])
+        add_to_expression!(obj, -c.revenue[t], y[p.name, c.name, m.name, t])
     end
 
     # Center: Collection cost
@@ -240,7 +244,8 @@ function build_model(instance::Instance; optimizer, variable_names::Bool = false
     eq_building_period = _init(model, :eq_building_period)
     for p in plants, t in T
         if t ∉ instance.building_period
-            eq_building_period[p.name, t] = @constraint(model, x[p.name, t] == 0)
+            eq_building_period[p.name, t] =
+                @constraint(model, x[p.name, t] - x[p.name, t-1] <= 0)
         end
     end
 

src/reports/centers.jl

@@ -11,14 +11,35 @@ function centers_report(model)::DataFrame
     df."year" = Int[]
     df."input product" = String[]
     df."input amount (tonne)" = Float64[]
+    df."revenue (\$)" = Float64[]
+    df."operating cost (\$)" = Float64[]
 
     centers = model.ext[:instance].centers
     T = 1:model.ext[:instance].time_horizon
+    E_in = model.ext[:E_in]
 
     for c in centers, t in T
         input_name = (c.input === nothing) ? "" : c.input.name
-        input = round(value(model[:z_input][c.name, t]), digits = 3)
-        push!(df, [c.name, t, input_name, input])
+        input = value(model[:z_input][c.name, t])
+        if isempty(E_in[c])
+            revenue = 0
+        else
+            revenue = sum(
+                c.revenue[t] * value(model[:y][p.name, c.name, m.name, t]) for
+                (p, m) in E_in[c]
+            )
+        end
+        push!(
+            df,
+            [
+                c.name,
+                t,
+                input_name,
+                _round(input),
+                _round(revenue),
+                _round(c.operating_cost[t]),
+            ],
+        )
     end
     return df
 end
@@ -30,14 +51,37 @@ function center_outputs_report(model)::DataFrame
     df."year" = Int[]
     df."amount collected (tonne)" = Float64[]
     df."amount disposed (tonne)" = Float64[]
+    df."collection cost (\$)" = Float64[]
+    df."disposal cost (\$)" = Float64[]
 
     centers = model.ext[:instance].centers
     T = 1:model.ext[:instance].time_horizon
+    E_out = model.ext[:E_out]
 
     for c in centers, m in c.outputs, t in T
-        collected = round(value(model[:z_collected][c.name, m.name, t]), digits = 3)
-        disposed = round(value(model[:z_disp][c.name, m.name, t]), digits = 3)
-        push!(df, [c.name, m.name, t, collected, disposed])
+        collected = value(model[:z_collected][c.name, m.name, t])
+        disposed = value(model[:z_disp][c.name, m.name, t])
+        disposal_cost = c.disposal_cost[m][t] * disposed
+        if isempty(E_out[c])
+            collection_cost = 0
+        else
+            collection_cost = sum(
+                c.collection_cost[m][t] * value(model[:y][c.name, p.name, m.name, t])
+                for (p, m) in E_out[c]
+            )
+        end
+        push!(
+            df,
+            [
+                c.name,
+                m.name,
+                t,
+                _round(collected),
+                _round(disposed),
+                _round(collection_cost),
+                _round(disposal_cost),
+            ],
+        )
     end
     return df
 end

src/reports/plants.jl

@@ -11,6 +11,9 @@ function plants_report(model)::DataFrame
     df."year" = Int[]
     df."operational?" = Bool[]
     df."input amount (tonne)" = Float64[]
+    df."opening cost (\$)" = Float64[]
+    df."fixed operating cost (\$)" = Float64[]
+    df."variable operating cost (\$)" = Float64[]
 
     plants = model.ext[:instance].plants
     T = 1:model.ext[:instance].time_horizon
@@ -18,8 +21,24 @@ function plants_report(model)::DataFrame
     for p in plants, t in T
         operational = JuMP.value(model[:x][p.name, t]) > 0.5
         input = value(model[:z_input][p.name, t])
-        operational || continue
-        push!(df, [p.name, t, operational, input])
+        opening_cost = 0
+        if value(model[:x][p.name, t]) > 0.5 && value(model[:x][p.name, t-1]) < 0.5
+            opening_cost = p.capacities[1].opening_cost[t]
+        end
+        fix_operating_cost = (operational ? p.capacities[1].fix_operating_cost[t] : 0)
+        var_operating_cost = input * p.capacities[1].var_operating_cost[t]
+        push!(
+            df,
+            [
+                p.name,
+                t,
+                operational,
+                _round(input),
+                _round(opening_cost),
+                _round(fix_operating_cost),
+                _round(var_operating_cost),
+            ],
+        )
     end
     return df
 end
@@ -31,6 +50,7 @@ function plant_outputs_report(model)::DataFrame
     df."year" = Int[]
     df."amount produced (tonne)" = Float64[]
     df."amount disposed (tonne)" = Float64[]
+    df."disposal cost (\$)" = Float64[]
 
     plants = model.ext[:instance].plants
     T = 1:model.ext[:instance].time_horizon
@@ -38,8 +58,11 @@ function plant_outputs_report(model)::DataFrame
     for p in plants, m in keys(p.output), t in T
         produced = JuMP.value(model[:z_prod][p.name, m.name, t])
         disposed = JuMP.value(model[:z_disp][p.name, m.name, t])
-        produced > 1e-3 || continue
-        push!(df, [p.name, m.name, t, produced, disposed])
+        disposal_cost = p.disposal_cost[m][t] * disposed
+        push!(
+            df,
+            [p.name, m.name, t, _round(produced), _round(disposed), _round(disposal_cost)],
+        )
     end
     return df
 end

src/reports/transportation.jl

@@ -13,6 +13,9 @@ function transportation_report(model)::DataFrame
     df."year" = Int[]
     df."amount sent (tonne)" = Float64[]
     df."distance (km)" = Float64[]
+    df."transportation cost (\$)" = Float64[]
+    df."center revenue (\$)" = Float64[]
+    df."center collection cost (\$)" = Float64[]
 
     E = model.ext[:E]
     distances = model.ext[:distances]
@@ -22,7 +25,29 @@ function transportation_report(model)::DataFrame
         amount = value(model[:y][p1.name, p2.name, m.name, t])
         amount > 1e-3 || continue
         distance = distances[p1, p2, m]
-        push!(df, [p1.name, p2.name, m.name, t, amount, distance])
+        tr_cost = distance * amount * m.tr_cost[t]
+        revenue = 0
+        if isa(p2, Center)
+            revenue = p2.revenue[t] * amount
+        end
+        collection_cost = 0
+        if isa(p1, Center)
+            collection_cost = p1.collection_cost[m][t] * amount
+        end
+        push!(
+            df,
+            [
+                p1.name,
+                p2.name,
+                m.name,
+                t,
+                _round(amount),
+                _round(distance),
+                _round(tr_cost),
+                _round(revenue),
+                _round(collection_cost),
+            ],
+        )
     end
     return df
 end

test/fixtures/boat_example.ipynb

@@ -2,59 +2,33 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 67,
+   "execution_count": 115,
    "metadata": {},
    "outputs": [],
    "source": [
     "import json\n",
     "\n",
-    "# cities_a = {\n",
-    "#     \"Chicago\": [41.881832, -87.623177],\n",
-    "#     \"New York City\": [40.712776, -74.005974],\n",
-    "#     \"Los Angeles\": [34.052235, -118.243683],\n",
-    "#     \"Houston\": [29.760427, -95.369804],\n",
-    "#     \"Phoenix\": [33.448376, -112.074036],\n",
-    "#     \"Philadelphia\": [39.952583, -75.165222],\n",
-    "#     \"San Antonio\": [29.424122, -98.493629],\n",
-    "#     \"San Diego\": [32.715736, -117.161087],\n",
-    "#     \"Dallas\": [32.776664, -96.796988],\n",
-    "#     \"San Jose\": [37.338208, -121.886329],\n",
-    "#     \"Austin\": [30.267153, -97.743061],\n",
-    "#     \"Jacksonville\": [30.332184, -81.655651],\n",
-    "#     \"Fort Worth\": [32.755488, -97.330766],\n",
-    "#     \"Columbus\": [39.961176, -82.998794],\n",
-    "#     \"Charlotte\": [35.227087, -80.843127],\n",
-    "#     \"Indianapolis\": [39.768403, -86.158068],\n",
-    "#     \"San Francisco\": [37.774929, -122.419416],\n",
-    "#     \"Seattle\": [47.606209, -122.332071],\n",
-    "#     \"Denver\": [39.739236, -104.990251],\n",
-    "#     \"Washington D.C.\": [38.907192, -77.036871],\n",
-    "#     \"Nashville\": [36.162664, -86.781602],\n",
-    "#     \"Detroit\": [42.331427, -83.045754],\n",
-    "#     \"Oklahoma City\": [35.467560, -97.516428],\n",
-    "#     \"Portland\": [45.505106, -122.675026],\n",
-    "#     \"Las Vegas\": [36.169941, -115.139830],\n",
-    "# }\n",
-    "\n",
-    "# cities_b = {\n",
-    "#     \"Chicago\": [41.881832, -87.623177],\n",
-    "#     \"Phoenix\": [33.448376, -112.074036],\n",
-    "#     \"Dallas\": [32.776664, -96.796988],\n",
-    "#     \"San Jose\": [37.338208, -121.886329],\n",
-    "#     \"Seattle\": [47.606209, -122.332071],\n",
-    "#     \"Las Vegas\": [36.169941, -115.139830],\n",
-    "# }\n",
-    "\n",
     "cities_a = {\n",
     "    \"Chicago\": [41.881832, -87.623177],\n",
+    "    \"New York City\": [40.712776, -74.005974],\n",
+    "    \"Los Angeles\": [34.052235, -118.243683],\n",
+    "    \"Houston\": [29.760427, -95.369804],\n",
+    "    \"Phoenix\": [33.448376, -112.074036],\n",
+    "    \"Philadelphia\": [39.952583, -75.165222],\n",
+    "    \"San Antonio\": [29.424122, -98.493629],\n",
+    "    \"San Diego\": [32.715736, -117.161087],\n",
+    "    \"Dallas\": [32.776664, -96.796988],\n",
+    "    \"San Jose\": [37.338208, -121.886329],\n",
     "}\n",
     "\n",
     "cities_b = {\n",
     "    \"Chicago\": [41.881832, -87.623177],\n",
+    "    \"Phoenix\": [33.448376, -112.074036],\n",
+    "    \"Dallas\": [32.776664, -96.796988],\n",
     "}\n",
     "\n",
     "parameters = {\n",
-    "    \"time horizon (years)\": 1,\n",
+    "    \"time horizon (years)\": 5,\n",
     "    \"building period (years)\": [1],\n",
     "    \"distance metric\": \"Euclidean\",\n",
     "}\n",
@@ -67,7 +41,7 @@
     "    \"revenue ($/tonne)\": None,\n",
     "    \"collection cost ($/tonne)\": {\"Nail\": 1000},\n",
     "    \"operating cost ($)\": 0,\n",
-    "    \"disposal limit (tonne)\": {\"Nail\": 0},\n",
+    "    \"disposal limit (tonne)\": {\"Nail\": None},\n",
     "    \"disposal cost ($/tonne)\": {\"Nail\": 0},\n",
     "}\n",
     "\n",
@@ -79,7 +53,7 @@
     "    \"revenue ($/tonne)\": None,\n",
     "    \"collection cost ($/tonne)\": {\"Wood\": 250},\n",
     "    \"operating cost ($)\": 0,\n",
-    "    \"disposal limit (tonne)\": {\"Wood\": 0},\n",
+    "    \"disposal limit (tonne)\": {\"Wood\": None},\n",
     "    \"disposal cost ($/tonne)\": {\"Wood\": 0},\n",
     "}\n",
     "\n",
@@ -88,10 +62,10 @@
     "    \"outputs\": [\"UsedBoat\"],\n",
     "    \"fixed output (tonne)\": {\"UsedBoat\": 0},\n",
     "    \"variable output (tonne/tonne)\": {\"UsedBoat\": [0.10, 0.25, 0.10]},\n",
-    "    \"revenue ($/tonne)\": 300_000,\n",
+    "    \"revenue ($/tonne)\": 12_000,\n",
     "    \"collection cost ($/tonne)\": {\"UsedBoat\": 100},\n",
     "    \"operating cost ($)\": 125_000,\n",
-    "    \"disposal limit (tonne)\": {\"UsedBoat\": 0},\n",
+    "    \"disposal limit (tonne)\": {\"UsedBoat\": None},\n",
     "    \"disposal cost ($/tonne)\": {\"UsedBoat\": 0},\n",
     "}\n",
     "\n",
@@ -123,15 +97,15 @@
     "    },\n",
     "    \"capacities\": [\n",
     "        {\n",
-    "            \"size (tonne)\": 200,\n",
-    "            \"opening cost ($)\": 10_000,\n",
-    "            \"fixed operating cost ($)\": 1_000,\n",
+    "            \"size (tonne)\": 500,\n",
+    "            \"opening cost ($)\": 1_000_000,\n",
+    "            \"fixed operating cost ($)\": 250_000,\n",
     "            \"variable operating cost ($/tonne)\": 5,\n",
     "        },\n",
     "        {\n",
-    "            \"size (tonne)\": 500,\n",
-    "            \"opening cost ($)\": 20_000,\n",
-    "            \"fixed operating cost ($)\": 2_000,\n",
+    "            \"size (tonne)\": 1000,\n",
+    "            \"opening cost ($)\": 2_000_000,\n",
+    "            \"fixed operating cost ($)\": 500_000,\n",
     "            \"variable operating cost ($/tonne)\": 5,\n",
     "        },\n",
     "    ],\n",
@@ -155,16 +129,15 @@
     "    \"disposal limit (tonne)\": {\"Nail\": 0, \"Wood\": 0},\n",
     "    \"capacities\": [\n",
     "        {\n",
-    "            \"size (tonne)\": 50,\n",
-    "            \"opening cost ($)\": 5_000,\n",
-    "            \"fixed operating cost ($)\": 500,\n",
+    "            \"size (tonne)\": 500,\n",
+    "            \"opening cost ($)\": 500_000,\n",
+    "            \"fixed operating cost ($)\": 125_000,\n",
     "            \"variable operating cost ($/tonne)\": 2.5,\n",
     "        },\n",
     "        {\n",
-    "            \"size (tonne)\": 500,\n",
-    "            \"opening cost ($)\": 10_000,\n",
-    "         \n",
-    "            \"fixed operating cost ($)\": 1_000,\n",
+    "            \"size (tonne)\": 1000,\n",
+    "            \"opening cost ($)\": 1_000_000,\n",
+    "            \"fixed operating cost ($)\": 250_000,\n",
     "            \"variable operating cost ($/tonne)\": 2.5,\n",
     "        },\n",
     "    ],\n",
@@ -174,7 +147,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 68,
+   "execution_count": 116,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -200,7 +173,8 @@
     "            \"longitude (deg)\": city_location[1],\n",
     "        }\n",
     "        for (city_name, city_location) in cities_b.items()\n",
-    "    } | {\n",
+    "    }\n",
+    "    | {\n",
     "        f\"Retail ({city_name})\": {\n",
     "            **retail,\n",
     "            \"latitude (deg)\": city_location[0],\n",
@@ -217,7 +191,8 @@
     "            \"longitude (deg)\": city_location[1],\n",
     "        }\n",
     "        for (city_name, city_location) in cities_a.items()\n",
-    "    } | {\n",
+    "    }\n",
+    "    | {\n",
     "        f\"RecyclingPlant ({city_name})\": {\n",
     "            **recycling_plant,\n",
     "            \"latitude (deg)\": city_location[0],\n",

test/src/model/build_test.jl

@@ -14,11 +14,11 @@ function model_build_test()
     # print(model)
 
     @test obj.terms[y["L1", "C3", "P4", 1]] == (
-        111.118 + # transportation
-        12.0 # revenue
+        111.118 * 0.015 # transportation
+        - 12.0 # revenue
     )
     @test obj.terms[y["C1", "L1", "P2", 4]] == (
-        333.262 +  # transportation
+        333.262 * 0.015 +  # transportation
         0.25 + # center collection cost
         5.0 # plant operating cost
     )
@@ -83,7 +83,7 @@ function model_build_test()
     # Plants: Building period
     @test ("L1", 1) ∉ keys(model[:eq_building_period])
     @test repr(model[:eq_building_period]["L1", 2]) ==
-          "eq_building_period[L1,2] : x[L1,2] = 0"
+          "eq_building_period[L1,2] : -x[L1,1] + x[L1,2] ≤ 0"
 
     # Centers: Definition of total center input
     @test repr(model[:eq_z_input]["C1", 1]) ==