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@ -76,6 +76,7 @@ Base.@kwdef mutable struct Instance
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m_init::dict{Tuple{Center,Product,Component,Time},Float64}
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m_plant_disp::dict{Tuple{Plant,Product,Time},Float64}
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m_store::dict{Tuple{Center,Product,Time},Float64}
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selected_edges::Union{Nothing,Set} = nothing
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end
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@ -112,39 +113,39 @@ function generate_data()
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cardboard = Component("Cardboard")
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# Products
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waste = Product(name = "Waste", comp = [film, paper, cardboard])
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film_bale = Product(name = "Film bale", comp = [film, paper, cardboard])
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cardboard_bale = Product(name = "Cardboard bale", comp = [paper, cardboard])
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cardboard_sheets = Product(name = "Cardboard sheets", comp = [cardboard])
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waste = Product(name="Waste", comp=[film, paper, cardboard])
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film_bale = Product(name="Film bale", comp=[film, paper, cardboard])
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cardboard_bale = Product(name="Cardboard bale", comp=[paper, cardboard])
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cardboard_sheets = Product(name="Cardboard sheets", comp=[cardboard])
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products = [waste, film_bale, cardboard_bale, cardboard_sheets]
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# Centers
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centers = [
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Center(
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name = "Collection ($city_name)",
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latitude = city_lat,
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longitude = city_lon,
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prod_out = [waste],
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name="Collection ($city_name)",
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latitude=city_lat,
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longitude=city_lon,
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prod_out=[waste],
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) for (city_name, (city_lat, city_lon)) in cities_a
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]
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# Plants
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plants_a = [
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Plant(
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name = "MRF ($city_name)",
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latitude = city_lat,
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longitude = city_lon,
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prod_in = waste,
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prod_out = [film_bale, cardboard_bale],
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name="MRF ($city_name)",
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latitude=city_lat,
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longitude=city_lon,
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prod_in=waste,
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prod_out=[film_bale, cardboard_bale],
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) for (city_name, (city_lat, city_lon)) in cities_b
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]
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plants_b = [
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Plant(
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name = "Paper Mill ($city_name)",
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latitude = city_lat,
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longitude = city_lon,
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prod_in = cardboard_bale,
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prod_out = [cardboard_sheets],
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name="Paper Mill ($city_name)",
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latitude=city_lat,
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longitude=city_lon,
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prod_in=cardboard_bale,
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prod_out=[cardboard_sheets],
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) for (city_name, (city_lat, city_lon)) in cities_b
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]
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plants = [plants_a; plants_b]
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@ -310,7 +311,7 @@ end
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# Read
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# ==============================================================================
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function read_json(filename; max_centers = Inf, max_plants = Inf)::Instance
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function read_json(filename; max_centers=Inf, max_plants=Inf)::Instance
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json = JSON.parsefile(filename)
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T = 1:json["parameters"]["time horizon (years)"]
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centers = []
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@ -529,23 +530,23 @@ function compress(original::Instance)::Instance
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(s, 1) => sum([original.m_emission[s, t] for t in T]) for s in original.emissions
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)
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m_init = Dict(
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(q, r, c, 1) => sum([original.m_init[q, r, c, t] for t in T]) for
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(q, r, c, 1) => length(T) * maximum([original.m_init[q, r, c, t] for t in T]) for
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q in original.centers for r in q.prod_out for c in r.comp
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)
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m_plant_disp = Dict(
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(p, r, 1) => sum([original.m_plant_disp[p, r, t] for t in T]) for
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(p, r, 1) => length(T) * minimum([original.m_plant_disp[p, r, t] for t in T]) for
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p in original.plants for r in p.prod_out
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)
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m_store = Dict(
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(q, r, 1) => sum([original.m_store[q, r, t] for t in T]) for
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(q, r, 1) => length(T) * minimum([original.m_store[q, r, t] for t in T]) for
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q in original.centers for r in q.prod_out
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)
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return Instance(;
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T = 1:1,
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centers = original.centers,
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plants = original.plants,
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products = original.products,
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emissions = original.emissions,
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T=1:1,
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centers=original.centers,
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plants=original.plants,
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products=original.products,
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emissions=original.emissions,
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alpha_mix=original.alpha_mix,
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alpha_plant_emission,
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alpha_tr_emission,
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@ -574,7 +575,7 @@ function benchmark_compress(filename, optimizer; max_centers=[Inf], max_plants=[
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# Solve original
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orig = read_json(filename; max_centers=mc, max_plants=mp)
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reset_timer!()
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stats_orig = solve(orig; optimizer)
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_, stats_orig = solve(orig; optimizer)
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stats_orig["Filename"] = filename
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stats_orig["Method"] = "Original"
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push!(stats, stats_orig)
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@ -582,7 +583,7 @@ function benchmark_compress(filename, optimizer; max_centers=[Inf], max_plants=[
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# Solve compressed
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compressed = compress(orig)
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reset_timer!()
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stats_comp = solve(compressed; optimizer)
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model_comp, stats_comp = solve(compressed; optimizer)
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stats_comp["Filename"] = filename
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stats_comp["Method"] = "Compressed"
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push!(stats, stats_comp)
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@ -604,16 +605,70 @@ function generate_json()
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write_json(data, "output-3/case.json")
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end
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function solve(filename, optimizer; max_centers = Inf, max_plants = Inf)
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function solve(filename, optimizer; max_centers=Inf, max_plants=Inf, heuristic=false)
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reset_timer!()
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@timeit "Read JSON" begin
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data = read_json(filename; max_centers, max_plants)
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end
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return solve(data; optimizer = optimizer, output_dir = dirname(filename))
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return solve(data; optimizer=optimizer, output_dir=dirname(filename), heuristic)
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print_timer()
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end
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function solve(data::Instance; optimizer, output_dir=nothing)
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function solve(data::Instance; optimizer, output_dir=nothing, heuristic=false)
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if heuristic
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@info "Solving compressed instance..."
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comp_data = compress(data)
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comp_model, comp_stats = solve(comp_data; optimizer, heuristic=false)
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# Filter plants
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selected_plants = Plant[]
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for p in comp_data.plants
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if value(comp_model[:x_open][p, 1]) > 0.5
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push!(selected_plants, p)
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end
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end
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@info "Selected $(length(selected_plants)) out of $(length(comp_data.plants)) plants"
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# Filter edges
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selected_edges = Set()
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for (src, dst, r) in comp_model[:E]
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if value(comp_model[:y_total][src, dst, r][1]) > 0.5
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push!(selected_edges, (src, dst, r))
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end
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end
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@info "Selected $(length(selected_edges)) out of $(length(comp_model[:E])) transportation edges"
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data = Instance(;
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data.T,
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data.centers,
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plants=selected_plants,
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data.products,
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data.emissions,
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data.alpha_mix,
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data.alpha_plant_emission,
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data.alpha_tr_emission,
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data.c_acq,
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data.c_center_disp,
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data.c_emission,
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data.c_fix,
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data.c_open,
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data.c_plant_disp,
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data.c_store,
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data.c_tr,
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data.c_var,
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data.m_cap,
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data.m_center_disp,
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data.m_dist,
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data.m_emission,
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data.m_init,
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data.m_plant_disp,
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data.m_store,
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selected_edges,
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)
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end
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T = data.T
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centers = data.centers
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plants = data.plants
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@ -630,7 +685,11 @@ function solve(data::Instance; optimizer, output_dir=nothing)
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E_in = dict(src => [] for src in plants)
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E_out = dict(src => [] for src in plants ∪ centers)
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function push_edge!(src, dst, r)
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push!(E, (src, dst, r))
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e = (src, dst, r)
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if data.selected_edges !== nothing && e ∉ data.selected_edges
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return
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end
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push!(E, e)
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push!(E_out[src], (dst, r))
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push!(E_in[dst], (src, r))
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end
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@ -654,6 +713,9 @@ function solve(data::Instance; optimizer, output_dir=nothing)
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end
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end
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end
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model[:E] = E
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model[:E_in] = E_in
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model[:E_out] = E_out
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@printf("Building optimization problem with:\n")
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@printf(" %8d plants\n", length(plants))
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@ -662,6 +724,25 @@ function solve(data::Instance; optimizer, output_dir=nothing)
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@printf(" %8d time periods\n", length(T))
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@printf(" %8d transportation edges\n", length(E))
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available = Dict((r, t) => 0.0 for r in data.products, t in T)
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for q in centers, t in T
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for r in q.prod_out, s in r.comp
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available[r, t] += data.m_init[q, r, s, t]
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end
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end
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capacity = Dict(r => 0.0 for r in data.products)
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for p in plants
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capacity[p.prod_in] += data.m_cap[p]
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end
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for r in products, t in T
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if available[r, t] > capacity[r]
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@warn "Not enough capacity to process $(r.name) at time $t: $(available[r,t]) > $(capacity[r])"
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end
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end
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# Decision variables
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# -------------------------------------------------------------------------
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@timeit "Model: Add variables" begin
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@ -1045,13 +1126,14 @@ function solve(data::Instance; optimizer, output_dir=nothing)
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"Time periods" => length(T),
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"Model build time (s)" => model_build_time,
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"Variables" => num_variables(model),
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"Constraints" => num_constraints(model, count_variable_in_set_constraints=false),
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"Constraints" =>
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num_constraints(model, count_variable_in_set_constraints=false),
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"Objective Value" => objective_value(model),
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"Solve time (s)" => solve_time(model),
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)
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if output_dir === nothing
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return stats
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return model, stats
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end
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# Report: Transportation
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@ -1078,13 +1160,13 @@ function solve(data::Instance; optimizer, output_dir=nothing)
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r.name,
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c.name,
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t,
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round(data.m_dist[q, p], digits = 2),
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round(value(y[q, p, r][c, t]), digits = 2),
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round(data.m_dist[q, p], digits=2),
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round(value(y[q, p, r][c, t]), digits=2),
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round(
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data.m_dist[q, p] * data.c_tr[r, t] * value(y[q, p, r][c, t]),
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digits = 2,
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digits=2,
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),
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round(data.c_var[p, t] * value(y[q, p, r][c, t]), digits = 2),
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round(data.c_var[p, t] * value(y[q, p, r][c, t]), digits=2),
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],
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)
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end
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@ -1112,18 +1194,18 @@ function solve(data::Instance; optimizer, output_dir=nothing)
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r.name,
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c.name,
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t,
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round(data.m_init[q, r, c, t], digits = 2),
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round(data.m_init[q, r, c, t], digits=2),
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round(
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sum(value(y[q, p, r][c, t]) for (p, r2) in E_out[q] if r == r2),
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digits = 2,
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digits=2,
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),
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round(value(z_store[q, r, c, t]), digits = 2),
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round(value(z_center_disp[q, r, c, t]), digits = 2),
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round(data.m_init[q, r, c, t] * data.c_acq[q, r, t], digits = 2),
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round(data.c_store[q, r, t] * value(z_store[q, r, c, t]), digits = 2),
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round(value(z_store[q, r, c, t]), digits=2),
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round(value(z_center_disp[q, r, c, t]), digits=2),
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round(data.m_init[q, r, c, t] * data.c_acq[q, r, t], digits=2),
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round(data.c_store[q, r, t] * value(z_store[q, r, c, t]), digits=2),
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round(
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data.c_center_disp[q, r, t] * value(z_center_disp[q, r, c, t]),
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|
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digits = 2,
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digits=2,
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),
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|
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],
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)
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@ -1144,12 +1226,12 @@ function solve(data::Instance; optimizer, output_dir=nothing)
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[
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p.name,
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|
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t,
|
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|
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round(value(x_open[p, t]), digits = 2),
|
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|
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|
round(value(x_open[p, t]), digits=2),
|
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|
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|
round(
|
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|
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|
data.c_open[p, t] * (value(x_open[p, t]) - value(x_open[p, t-1])),
|
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|
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|
digits = 2,
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|
|
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|
digits=2,
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|
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|
),
|
|
|
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|
round(data.c_fix[p, t] * value(x_open[p, t]), digits = 2),
|
|
|
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|
round(data.c_fix[p, t] * value(x_open[p, t]), digits=2),
|
|
|
|
|
],
|
|
|
|
|
)
|
|
|
|
|
end
|
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|
|
|
@ -1177,18 +1259,18 @@ function solve(data::Instance; optimizer, output_dir=nothing)
|
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|
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|
r.name,
|
|
|
|
|
c.name,
|
|
|
|
|
t,
|
|
|
|
|
round(value(z_prod[p, r, c, t]), digits = 2),
|
|
|
|
|
round(value(z_plant_disp[p, r, c, t]), digits = 2),
|
|
|
|
|
round(value(z_prod[p, r, c, t]), digits=2),
|
|
|
|
|
round(value(z_plant_disp[p, r, c, t]), digits=2),
|
|
|
|
|
round(
|
|
|
|
|
sum(
|
|
|
|
|
value(y[p, q, r][c, t]) for (q, r2) in E_out[p] if r == r2;
|
|
|
|
|
init = 0.0,
|
|
|
|
|
init=0.0,
|
|
|
|
|
),
|
|
|
|
|
digits = 2,
|
|
|
|
|
digits=2,
|
|
|
|
|
),
|
|
|
|
|
round(
|
|
|
|
|
data.c_plant_disp[p, r, t] * value(z_plant_disp[p, r, c, t]),
|
|
|
|
|
digits = 2,
|
|
|
|
|
digits=2,
|
|
|
|
|
),
|
|
|
|
|
],
|
|
|
|
|
)
|
|
|
|
|
@ -1210,10 +1292,10 @@ function solve(data::Instance; optimizer, output_dir=nothing)
|
|
|
|
|
p.name,
|
|
|
|
|
s.name,
|
|
|
|
|
t,
|
|
|
|
|
round(value(z_plant_emissions[p, s, t]), digits = 2),
|
|
|
|
|
round(value(z_plant_emissions[p, s, t]), digits=2),
|
|
|
|
|
round(
|
|
|
|
|
data.c_emission[s, t] * value(z_plant_emissions[p, s, t]),
|
|
|
|
|
digits = 2,
|
|
|
|
|
digits=2,
|
|
|
|
|
),
|
|
|
|
|
],
|
|
|
|
|
)
|
|
|
|
|
@ -1244,17 +1326,17 @@ function solve(data::Instance; optimizer, output_dir=nothing)
|
|
|
|
|
r.name,
|
|
|
|
|
s.name,
|
|
|
|
|
t,
|
|
|
|
|
round(data.m_dist[q, p], digits = 2),
|
|
|
|
|
round(value(y_total[q, p, r][t]), digits = 2),
|
|
|
|
|
round(value(z_tr_emissions[q, p, r, s, t]), digits = 2),
|
|
|
|
|
round(data.m_dist[q, p], digits=2),
|
|
|
|
|
round(value(y_total[q, p, r][t]), digits=2),
|
|
|
|
|
round(value(z_tr_emissions[q, p, r, s, t]), digits=2),
|
|
|
|
|
round(
|
|
|
|
|
data.c_emission[s, t] * value(z_tr_emissions[q, p, r, s, t]),
|
|
|
|
|
digits = 2,
|
|
|
|
|
digits=2,
|
|
|
|
|
),
|
|
|
|
|
],
|
|
|
|
|
)
|
|
|
|
|
end
|
|
|
|
|
CSV.write("$output_dir/transp-emissions.csv", df)
|
|
|
|
|
|
|
|
|
|
return stats
|
|
|
|
|
return model, stats
|
|
|
|
|
end
|
|
|
|
|
|
Alinson S. Xavier