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Heuristic: Use max/min instead of sum for demand, storage, disposal

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Alinson S. Xavier
2024-04-24 12:57:57 -05:00
parent 94c77bd1c5
commit 5888368504
1 changed files with 83 additions and 64 deletions
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147
model-3.jl
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@@ -113,39 +113,39 @@ function generate_data()
cardboard = Component("Cardboard")
# Products
waste = Product(name = "Waste", comp = [film, paper, cardboard])
film_bale = Product(name = "Film bale", comp = [film, paper, cardboard])
cardboard_bale = Product(name = "Cardboard bale", comp = [paper, cardboard])
cardboard_sheets = Product(name = "Cardboard sheets", comp = [cardboard])
waste = Product(name="Waste", comp=[film, paper, cardboard])
film_bale = Product(name="Film bale", comp=[film, paper, cardboard])
cardboard_bale = Product(name="Cardboard bale", comp=[paper, cardboard])
cardboard_sheets = Product(name="Cardboard sheets", comp=[cardboard])
products = [waste, film_bale, cardboard_bale, cardboard_sheets]
# Centers
centers = [
Center(
name = "Collection ($city_name)",
latitude = city_lat,
longitude = city_lon,
prod_out = [waste],
name="Collection ($city_name)",
latitude=city_lat,
longitude=city_lon,
prod_out=[waste],
) for (city_name, (city_lat, city_lon)) in cities_a
]
# Plants
plants_a = [
Plant(
name = "MRF ($city_name)",
latitude = city_lat,
longitude = city_lon,
prod_in = waste,
prod_out = [film_bale, cardboard_bale],
name="MRF ($city_name)",
latitude=city_lat,
longitude=city_lon,
prod_in=waste,
prod_out=[film_bale, cardboard_bale],
) for (city_name, (city_lat, city_lon)) in cities_b
]
plants_b = [
Plant(
name = "Paper Mill ($city_name)",
latitude = city_lat,
longitude = city_lon,
prod_in = cardboard_bale,
prod_out = [cardboard_sheets],
name="Paper Mill ($city_name)",
latitude=city_lat,
longitude=city_lon,
prod_in=cardboard_bale,
prod_out=[cardboard_sheets],
) for (city_name, (city_lat, city_lon)) in cities_b
]
plants = [plants_a; plants_b]
@@ -311,7 +311,7 @@ end
# Read
# ==============================================================================
function read_json(filename; max_centers = Inf, max_plants = Inf)::Instance
function read_json(filename; max_centers=Inf, max_plants=Inf)::Instance
json = JSON.parsefile(filename)
T = 1:json["parameters"]["time horizon (years)"]
centers = []
@@ -530,24 +530,24 @@ function compress(original::Instance)::Instance
(s, 1) => sum([original.m_emission[s, t] for t in T]) for s in original.emissions
)
m_init = Dict(
(q, r, c, 1) => sum([original.m_init[q, r, c, t] for t in T]) for
(q, r, c, 1) => length(T) * maximum([original.m_init[q, r, c, t] for t in T]) for
q in original.centers for r in q.prod_out for c in r.comp
)
m_plant_disp = Dict(
(p, r, 1) => sum([original.m_plant_disp[p, r, t] for t in T]) for
(p, r, 1) => length(T) * minimum([original.m_plant_disp[p, r, t] for t in T]) for
p in original.plants for r in p.prod_out
)
m_store = Dict(
(q, r, 1) => sum([original.m_store[q, r, t] for t in T]) for
(q, r, 1) => length(T) * minimum([original.m_store[q, r, t] for t in T]) for
q in original.centers for r in q.prod_out
)
return Instance(;
T = 1:1,
centers = original.centers,
plants = original.plants,
products = original.products,
emissions = original.emissions,
alpha_mix = original.alpha_mix,
T=1:1,
centers=original.centers,
plants=original.plants,
products=original.products,
emissions=original.emissions,
alpha_mix=original.alpha_mix,
alpha_plant_emission,
alpha_tr_emission,
c_acq,
@@ -561,7 +561,7 @@ function compress(original::Instance)::Instance
c_var,
m_cap,
m_center_disp,
m_dist = original.m_dist,
m_dist=original.m_dist,
m_emission,
m_init,
m_plant_disp,
@@ -569,13 +569,13 @@ function compress(original::Instance)::Instance
)
end
function benchmark_compress(filename, optimizer; max_centers = [Inf], max_plants = [Inf])
function benchmark_compress(filename, optimizer; max_centers=[Inf], max_plants=[Inf])
stats = []
for mc in max_centers, mp in max_plants
# Solve original
orig = read_json(filename; max_centers = mc, max_plants = mp)
orig = read_json(filename; max_centers=mc, max_plants=mp)
reset_timer!()
model_orig, stats_orig = solve(orig; optimizer)
_, stats_orig = solve(orig; optimizer)
stats_orig["Filename"] = filename
stats_orig["Method"] = "Original"
push!(stats, stats_orig)
@@ -605,20 +605,21 @@ function generate_json()
write_json(data, "output-3/case.json")
end
function solve(filename, optimizer; max_centers = Inf, max_plants = Inf, heuristic = false)
function solve(filename, optimizer; max_centers=Inf, max_plants=Inf, heuristic=false)
reset_timer!()
@timeit "Read JSON" begin
data = read_json(filename; max_centers, max_plants)
end
return solve(data; optimizer = optimizer, output_dir = dirname(filename), heuristic)
return solve(data; optimizer=optimizer, output_dir=dirname(filename), heuristic)
print_timer()
end
function solve(data::Instance; optimizer, output_dir = nothing, heuristic = false)
function solve(data::Instance; optimizer, output_dir=nothing, heuristic=false)
if heuristic
@info "Solving compressed instance..."
comp_data = compress(data)
comp_model, comp_stats = solve(comp_data; optimizer, heuristic = false)
comp_model, comp_stats = solve(comp_data; optimizer, heuristic=false)
# Filter plants
selected_plants = Plant[]
@@ -641,7 +642,7 @@ function solve(data::Instance; optimizer, output_dir = nothing, heuristic = fals
data = Instance(;
data.T,
data.centers,
plants = selected_plants,
plants=selected_plants,
data.products,
data.emissions,
data.alpha_mix,
@@ -686,7 +687,6 @@ function solve(data::Instance; optimizer, output_dir = nothing, heuristic = fals
function push_edge!(src, dst, r)
e = (src, dst, r)
if data.selected_edges !== nothing && e ∉ data.selected_edges
@info "Skipping: $(src.name) $(dst.name) $(r.name)"
return
end
push!(E, e)
@@ -724,6 +724,25 @@ function solve(data::Instance; optimizer, output_dir = nothing, heuristic = fals
@printf(" %8d time periods\n", length(T))
@printf(" %8d transportation edges\n", length(E))
available = Dict((r, t) => 0.0 for r in data.products, t in T)
for q in centers, t in T
for r in q.prod_out, s in r.comp
available[r, t] += data.m_init[q, r, s, t]
end
end
capacity = Dict(r => 0.0 for r in data.products)
for p in plants
capacity[p.prod_in] += data.m_cap[p]
end
for r in products, t in T
if available[r, t] > capacity[r]
@warn "Not enough capacity to process $(r.name) at time $t: $(available[r,t]) > $(capacity[r])"
end
end
# Decision variables
# -------------------------------------------------------------------------
@timeit "Model: Add variables" begin
@@ -1108,7 +1127,7 @@ function solve(data::Instance; optimizer, output_dir = nothing, heuristic = fals
"Model build time (s)" => model_build_time,
"Variables" => num_variables(model),
"Constraints" =>
num_constraints(model, count_variable_in_set_constraints = false),
num_constraints(model, count_variable_in_set_constraints=false),
"Objective Value" => objective_value(model),
"Solve time (s)" => solve_time(model),
)
@@ -1141,13 +1160,13 @@ function solve(data::Instance; optimizer, output_dir = nothing, heuristic = fals
r.name,
c.name,
t,
round(data.m_dist[q, p], digits = 2),
round(value(y[q, p, r][c, t]), digits = 2),
round(data.m_dist[q, p], digits=2),
round(value(y[q, p, r][c, t]), digits=2),
round(
data.m_dist[q, p] * data.c_tr[r, t] * value(y[q, p, r][c, t]),
digits = 2,
digits=2,
),
round(data.c_var[p, t] * value(y[q, p, r][c, t]), digits = 2),
round(data.c_var[p, t] * value(y[q, p, r][c, t]), digits=2),
],
)
end
@@ -1175,18 +1194,18 @@ function solve(data::Instance; optimizer, output_dir = nothing, heuristic = fals
r.name,
c.name,
t,
round(data.m_init[q, r, c, t], digits = 2),
round(data.m_init[q, r, c, t], digits=2),
round(
sum(value(y[q, p, r][c, t]) for (p, r2) in E_out[q] if r == r2),
digits = 2,
digits=2,
),
round(value(z_store[q, r, c, t]), digits = 2),
round(value(z_center_disp[q, r, c, t]), digits = 2),
round(data.m_init[q, r, c, t] * data.c_acq[q, r, t], digits = 2),
round(data.c_store[q, r, t] * value(z_store[q, r, c, t]), digits = 2),
round(value(z_store[q, r, c, t]), digits=2),
round(value(z_center_disp[q, r, c, t]), digits=2),
round(data.m_init[q, r, c, t] * data.c_acq[q, r, t], digits=2),
round(data.c_store[q, r, t] * value(z_store[q, r, c, t]), digits=2),
round(
data.c_center_disp[q, r, t] * value(z_center_disp[q, r, c, t]),
digits = 2,
digits=2,
),
],
)
@@ -1207,12 +1226,12 @@ function solve(data::Instance; optimizer, output_dir = nothing, heuristic = fals
[
p.name,
t,
round(value(x_open[p, t]), digits = 2),
round(value(x_open[p, t]), digits=2),
round(
data.c_open[p, t] * (value(x_open[p, t]) - value(x_open[p, t-1])),
digits = 2,
digits=2,
),
round(data.c_fix[p, t] * value(x_open[p, t]), digits = 2),
round(data.c_fix[p, t] * value(x_open[p, t]), digits=2),
],
)
end
@@ -1240,18 +1259,18 @@ function solve(data::Instance; optimizer, output_dir = nothing, heuristic = fals
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,
),
],
)
@@ -1273,10 +1292,10 @@ function solve(data::Instance; optimizer, output_dir = nothing, heuristic = fals
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,
),
],
)
@@ -1307,12 +1326,12 @@ function solve(data::Instance; optimizer, output_dir = nothing, heuristic = fals
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,
),
],
)