Implement basic reports; fix boat example

Project.toml

@@ -4,6 +4,8 @@ authors = ["Alinson S. Xavier <git@axavier.org>"]
 version = "0.1.0"
 
 [deps]
+CSV = "336ed68f-0bac-5ca0-87d4-7b16caf5d00b"
+DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0"
 Geodesy = "0ef565a4-170c-5f04-8de2-149903a85f3d"
 JSON = "682c06a0-de6a-54ab-a142-c8b1cf79cde6"
 JuMP = "4076af6c-e467-56ae-b986-b466b2749572"

src/RELOG.jl

@@ -5,5 +5,8 @@ include("instance/parse.jl")
 include("model/jumpext.jl")
 include("model/dist.jl")
 include("model/build.jl")
+include("reports/plants.jl")
+include("reports/transportation.jl")
+include("reports/centers.jl")
 
 end # module RELOG

src/model/build.jl

@@ -6,14 +6,15 @@ function build_model(instance::Instance; optimizer, variable_names::Bool = false
     products = instance.products
     plants = instance.plants
     T = 1:instance.time_horizon
+    model.ext[:instance] = instance
 
     # Transportation edges
     # -------------------------------------------------------------------------
 
     # Connectivity
-    E = []
+    model.ext[:E] = E = []
-    E_in = Dict(src => [] for src in plants ∪ centers)
+    model.ext[:E_in] = E_in = Dict(src => [] for src in plants ∪ centers)
-    E_out = Dict(src => [] for src in plants ∪ centers)
+    model.ext[:E_out] = E_out = Dict(src => [] for src in plants ∪ centers)
 
     function push_edge!(src, dst, m)
         push!(E, (src, dst, m))
@@ -28,7 +29,7 @@ function build_model(instance::Instance; optimizer, variable_names::Bool = false
             # Plant to plant
             for p2 in plants
                 p1 != p2 || continue
-                m ∉ keys(p2.input_mix) || continue
+                m ∈ keys(p2.input_mix) || continue
                 push_edge!(p1, p2, m)
             end
 
@@ -57,7 +58,7 @@ function build_model(instance::Instance; optimizer, variable_names::Bool = false
     end
 
     # Distances
-    distances = Dict()
+    model.ext[:distances] = distances = Dict()
     for (p1, p2, m) in E
         d = _calculate_distance(p1.latitude, p1.longitude, p2.latitude, p2.longitude)
         distances[p1, p2, m] = d
@@ -86,9 +87,6 @@ function build_model(instance::Instance; optimizer, variable_names::Bool = false
     for p in plants, m in keys(p.output), t in T
         z_prod[p.name, m.name, t] = @variable(model, lower_bound = 0)
     end
-    for c in centers, m in c.outputs, t in T
-        z_prod[c.name, m.name, t] = @variable(model, lower_bound = 0)
-    end
 
     # Amount of product m disposed at plant/center p at time T
     z_disp = _init(model, :z_disp)

src/reports/centers.jl

@@ -0,0 +1,47 @@
+# RELOG: Reverse Logistics Optimization
+# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
+# Released under the modified BSD license. See COPYING.md for more details.
+
+using DataFrames
+using CSV
+
+function centers_report(model)::DataFrame
+    df = DataFrame()
+    df."center" = String[]
+    df."year" = Int[]
+    df."input product" = String[]
+    df."input amount (tonne)" = Float64[]
+
+    centers = model.ext[:instance].centers
+    T = 1:model.ext[:instance].time_horizon
+
+    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])
+    end
+    return df
+end
+
+function center_outputs_report(model)::DataFrame
+    df = DataFrame()
+    df."center" = String[]
+    df."output product" = String[]
+    df."year" = Int[]
+    df."amount collected (tonne)" = Float64[]
+    df."amount disposed (tonne)" = Float64[]
+
+    centers = model.ext[:instance].centers
+    T = 1:model.ext[:instance].time_horizon
+
+    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])
+    end
+    return df
+end
+
+write_centers_report(solution, filename) = CSV.write(filename, centers_report(solution))
+write_center_outputs_report(solution, filename) =
+    CSV.write(filename, center_outputs_report(solution))

src/reports/plants.jl

@@ -0,0 +1,49 @@
+# RELOG: Reverse Logistics Optimization
+# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
+# Released under the modified BSD license. See COPYING.md for more details.
+
+using DataFrames
+using CSV
+
+function plants_report(model)::DataFrame
+    df = DataFrame()
+    df."plant" = String[]
+    df."year" = Int[]
+    df."operational?" = Bool[]
+    df."input amount (tonne)" = Float64[]
+
+    plants = model.ext[:instance].plants
+    T = 1:model.ext[:instance].time_horizon
+
+    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])
+    end
+    return df
+end
+
+function plant_outputs_report(model)::DataFrame
+    df = DataFrame()
+    df."plant" = String[]
+    df."output product" = String[]
+    df."year" = Int[]
+    df."amount produced (tonne)" = Float64[]
+    df."amount disposed (tonne)" = Float64[]
+
+    plants = model.ext[:instance].plants
+    T = 1:model.ext[:instance].time_horizon
+
+    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])
+    end
+    return df
+end
+
+write_plants_report(solution, filename) = CSV.write(filename, plants_report(solution))
+write_plant_outputs_report(solution, filename) =
+    CSV.write(filename, plant_outputs_report(solution))

src/reports/transportation.jl

@@ -0,0 +1,31 @@
+# RELOG: Reverse Logistics Optimization
+# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
+# Released under the modified BSD license. See COPYING.md for more details.
+
+using DataFrames
+using CSV
+
+function transportation_report(model)::DataFrame
+    df = DataFrame()
+    df."source" = String[]
+    df."destination" = String[]
+    df."product" = String[]
+    df."year" = Int[]
+    df."amount sent (tonne)" = Float64[]
+    df."distance (km)" = Float64[]
+
+    E = model.ext[:E]
+    distances = model.ext[:distances]
+    T = 1:model.ext[:instance].time_horizon
+
+    for (p1, p2, m) in E, t in T
+        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])
+    end
+    return df
+end
+
+write_transportation_report(solution, filename) =
+    CSV.write(filename, transportation_report(solution))

test/fixtures/boat_example.ipynb

@@ -2,51 +2,59 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 67,
    "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",
-    "    \"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",
     "parameters = {\n",
-    "    \"time horizon (years)\": 10,\n",
+    "    \"time horizon (years)\": 1,\n",
     "    \"building period (years)\": [1],\n",
     "    \"distance metric\": \"Euclidean\",\n",
     "}\n",
@@ -54,24 +62,24 @@
     "nail_factory = {\n",
     "    \"input\": None,\n",
     "    \"outputs\": [\"Nail\"],\n",
-    "    \"fixed output (tonne)\": {\"Nail\": 1},\n",
+    "    \"fixed output (tonne)\": {\"Nail\": 5},\n",
     "    \"variable output (tonne/tonne)\": {\"Nail\": 0},\n",
     "    \"revenue ($/tonne)\": None,\n",
     "    \"collection cost ($/tonne)\": {\"Nail\": 1000},\n",
     "    \"operating cost ($)\": 0,\n",
-    "    \"disposal limit (tonne)\": {\"Nail\": None},\n",
+    "    \"disposal limit (tonne)\": {\"Nail\": 0},\n",
     "    \"disposal cost ($/tonne)\": {\"Nail\": 0},\n",
     "}\n",
     "\n",
     "forest = {\n",
     "    \"input\": None,\n",
     "    \"outputs\": [\"Wood\"],\n",
-    "    \"fixed output (tonne)\": {\"Wood\": 100},\n",
+    "    \"fixed output (tonne)\": {\"Wood\": 95},\n",
     "    \"variable output (tonne/tonne)\": {\"Wood\": 0},\n",
     "    \"revenue ($/tonne)\": None,\n",
     "    \"collection cost ($/tonne)\": {\"Wood\": 250},\n",
     "    \"operating cost ($)\": 0,\n",
-    "    \"disposal limit (tonne)\": {\"Wood\": None},\n",
+    "    \"disposal limit (tonne)\": {\"Wood\": 0},\n",
     "    \"disposal cost ($/tonne)\": {\"Wood\": 0},\n",
     "}\n",
     "\n",
@@ -80,7 +88,7 @@
     "    \"outputs\": [\"UsedBoat\"],\n",
     "    \"fixed output (tonne)\": {\"UsedBoat\": 0},\n",
     "    \"variable output (tonne/tonne)\": {\"UsedBoat\": [0.10, 0.25, 0.10]},\n",
-    "    \"revenue ($/tonne)\": 3_000,\n",
+    "    \"revenue ($/tonne)\": 300_000,\n",
     "    \"collection cost ($/tonne)\": {\"UsedBoat\": 100},\n",
     "    \"operating cost ($)\": 125_000,\n",
     "    \"disposal limit (tonne)\": {\"UsedBoat\": 0},\n",
@@ -115,7 +123,7 @@
     "    },\n",
     "    \"capacities\": [\n",
     "        {\n",
-    "            \"size (tonne)\": 50,\n",
+    "            \"size (tonne)\": 200,\n",
     "            \"opening cost ($)\": 10_000,\n",
     "            \"fixed operating cost ($)\": 1_000,\n",
     "            \"variable operating cost ($/tonne)\": 5,\n",
@@ -144,7 +152,7 @@
     "        \"Nail\": 0,\n",
     "        \"Wood\": 0,\n",
     "    },\n",
-    "    \"disposal limit (tonne)\": {\"Nail\": None, \"Wood\": None},\n",
+    "    \"disposal limit (tonne)\": {\"Nail\": 0, \"Wood\": 0},\n",
     "    \"capacities\": [\n",
     "        {\n",
     "            \"size (tonne)\": 50,\n",
@@ -166,7 +174,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 68,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -199,8 +207,10 @@
     "            \"longitude (deg)\": city_location[1],\n",
     "        }\n",
     "        for (city_name, city_location) in cities_a.items()\n",
-    "    },\n",
+    "    }\n",
-    "    \"plants\": {\n",
+    "    ,\n",
+    "    \"plants\":\n",
+    "    {\n",
     "        f\"BoatFactory ({city_name})\": {\n",
     "            **boat_factory,\n",
     "            \"latitude (deg)\": city_location[0],\n",
@@ -209,7 +219,7 @@
     "        for (city_name, city_location) in cities_a.items()\n",
     "    } | {\n",
     "        f\"RecyclingPlant ({city_name})\": {\n",
-    "            **boat_factory,\n",
+    "            **recycling_plant,\n",
     "            \"latitude (deg)\": city_location[0],\n",
     "            \"longitude (deg)\": city_location[1],\n",
     "        }\n",

test/src/RELOGT.jl

@@ -7,6 +7,7 @@ using JuliaFormatter
 include("instance/parse_test.jl")
 include("model/build_test.jl")
 include("model/dist_test.jl")
+include("reports_test.jl")
 
 basedir = dirname(@__FILE__)
 
@@ -18,9 +19,9 @@ function runtests()
     @testset "RELOG" begin
         instance_parse_test_1()
         instance_parse_test_2()
-        model_build_test_1()
+        model_build_test()
-        model_build_test_2()
         model_dist_test()
+        report_tests()
     end
 end
 

test/src/model/build_test.jl

@@ -3,7 +3,7 @@ using Test
 using HiGHS
 using JuMP
 
-function model_build_test_1()
+function model_build_test()
     instance = RELOG.parsefile(fixture("simple.json"))
     model = RELOG.build_model(instance, optimizer = HiGHS.Optimizer, variable_names = true)
     y = model[:y]
@@ -110,10 +110,3 @@ function model_build_test_1()
           "eq_disposal_limit[C1,P2,1] : z_disp[C1,P2,1] ≤ 0"
     @test ("C1", "P3", 1) ∉ keys(model[:eq_disposal_limit])
 end
-
-
-function model_build_test_2()
-    instance = RELOG.parsefile(fixture("boat_example.json"))
-    model = RELOG.build_model(instance, optimizer = HiGHS.Optimizer)
-    optimize!(model) 
-end

test/src/reports_test.jl

@@ -0,0 +1,12 @@
+function report_tests()
+    # Load and solve the boat example
+    instance = RELOG.parsefile(fixture("boat_example.json"))
+    model = RELOG.build_model(instance, optimizer = HiGHS.Optimizer, variable_names = true)
+    optimize!(model)
+    write_to_file(model, "tmp/model.lp")
+    RELOG.write_plants_report(model, "tmp/plants.csv")
+    RELOG.write_plant_outputs_report(model, "tmp/plant_outputs.csv")
+    RELOG.write_centers_report(model, "tmp/centers.csv")
+    RELOG.write_center_outputs_report(model, "tmp/center_outputs.csv")
+    RELOG.write_transportation_report(model, "tmp/transportation.csv")
+end