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Implement compress method

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feature/composition
Alinson S. Xavier 1 year ago
parent c1f157b386
commit 65acf4c92f
1 changed files with 191 additions and 37 deletions
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228
model-3.jl
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@ -21,23 +21,23 @@ Random.seed!(42)
# Structs
# =========================================================================
Base.@kwdef struct Component
Base.@kwdef mutable struct Component
name::String
end
Base.@kwdef struct Product
Base.@kwdef mutable struct Product
name::String
comp::Vector{Component}
end
Base.@kwdef struct Center
Base.@kwdef mutable struct Center
name::String
latitude::Float64
longitude::Float64
prod_out::Vector{Product}
end
Base.@kwdef struct Plant
Base.@kwdef mutable struct Plant
name::String
latitude::Float64
longitude::Float64
@ -45,7 +45,7 @@ Base.@kwdef struct Plant
prod_in::Product
end
Base.@kwdef struct Emission
Base.@kwdef mutable struct Emission
name::String
end
@ -310,7 +310,7 @@ end
# Read
# ==============================================================================
function read_json(filename, max_centers = 10, max_plants = 10)
function read_json(filename; max_centers = Inf, max_plants = Inf)::Instance
json = JSON.parsefile(filename)
T = 1:json["parameters"]["time horizon (years)"]
centers = []
@ -484,6 +484,114 @@ function read_json(filename, max_centers = 10, max_plants = 10)
)
end
# Multi-period Heuristic
# ==============================================================================
function compress(original::Instance)::Instance
T = original.T
alpha_plant_emission = Dict(
(p, s, 1) => mean([original.alpha_plant_emission[p, s, t] for t in T]) for
p in original.plants, s in original.emissions
)
alpha_tr_emission = Dict(
(r, s, 1) => mean([original.alpha_tr_emission[r, s, t] for t in T]) for
r in original.products, s in original.emissions
)
c_acq = Dict(
(q, r, 1) => mean([original.c_acq[q, r, t] for t in T]) for
q in original.centers for r in q.prod_out
)
c_center_disp = Dict(
(q, r, 1) => mean([original.c_center_disp[q, r, t] for t in T]) for
q in original.centers for r in q.prod_out
)
c_emission = Dict(
(s, 1) => mean([original.c_emission[s, t] for t in T]) for s in original.emissions
)
c_fix = Dict((p, 1) => sum([original.c_fix[p, t] for t in T]) for p in original.plants)
c_open =
Dict((p, 1) => mean([original.c_open[p, t] for t in T]) for p in original.plants)
c_plant_disp = Dict(
(p, r, 1) => mean([original.c_plant_disp[p, r, t] for t in T]) for
p in original.plants for r in p.prod_out
)
c_store = Dict(
(q, r, 1) => mean([original.c_store[q, r, t] for t in T]) for
q in original.centers for r in q.prod_out
)
c_tr = Dict((r, 1) => mean([original.c_tr[r, t] for t in T]) for r in original.products)
c_var = Dict((p, 1) => mean([original.c_var[p, t] for t in T]) for p in original.plants)
m_cap = Dict(p => original.m_cap[p] * length(T) for p in original.plants)
m_center_disp = Dict(
(r, 1) => sum([original.m_center_disp[r, t] for t in T]) for r in original.products
)
m_emission = Dict(
(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 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 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 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,
alpha_plant_emission,
alpha_tr_emission,
c_acq,
c_center_disp,
c_emission,
c_fix,
c_open,
c_plant_disp,
c_store,
c_tr,
c_var,
m_cap,
m_center_disp,
m_dist=original.m_dist,
m_emission,
m_init,
m_plant_disp,
m_store,
)
end
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)
reset_timer!()
stats_orig = solve(orig; optimizer)
stats_orig["Filename"] = filename
stats_orig["Method"] = "Original"
push!(stats, stats_orig)
# Solve compressed
compressed = compress(orig)
reset_timer!()
stats_comp = solve(compressed; optimizer)
stats_comp["Filename"] = filename
stats_comp["Method"] = "Compressed"
push!(stats, stats_comp)
end
return DataFrame(stats)
end
# Run
# ==============================================================================
@ -496,13 +604,16 @@ function generate_json()
write_json(data, "output-3/case.json")
end
function solve(filename, optimizer)
function solve(filename, optimizer; max_centers = Inf, max_plants = Inf)
reset_timer!()
@timeit "Read JSON" begin
data = read_json(filename)
data = read_json(filename; max_centers, max_plants)
end
return solve(data; optimizer = optimizer, output_dir = dirname(filename))
print_timer()
end
function solve(data::Instance; optimizer, output_dir=nothing)
T = data.T
centers = data.centers
plants = data.plants
@ -510,6 +621,7 @@ function solve(filename, optimizer)
emissions = data.emissions
model = Model(optimizer)
init_time = time()
# Graph
# -------------------------------------------------------------------------
@ -920,13 +1032,30 @@ function solve(filename, optimizer)
end
end
model_build_time = time() - init_time
# Optimize
# -------------------------------------------------------------------------
optimize!(model)
stats = OrderedDict{String,Any}(
"Plants" => length(plants),
"Centers" => length(centers),
"Products" => length(products),
"Time periods" => length(T),
"Model build time (s)" => model_build_time,
"Variables" => num_variables(model),
"Constraints" => num_constraints(model, count_variable_in_set_constraints=false),
"Objective Value" => objective_value(model),
"Solve time (s)" => solve_time(model),
)
if output_dir === nothing
return stats
end
# Report: Transportation
# -------------------------------------------------------------------------
output_dir = dirname(filename)
df = DataFrame()
df."source" = String[]
df."destination" = String[]
@ -949,10 +1078,13 @@ function solve(filename, optimizer)
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] * data.c_tr[r, 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),
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,
),
round(data.c_var[p, t] * value(y[q, p, r][c, t]), digits = 2),
],
)
end
@ -980,13 +1112,19 @@ function solve(filename, optimizer)
r.name,
c.name,
t,
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),
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),
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,
),
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,
),
],
)
end
@ -1006,9 +1144,12 @@ function solve(filename, optimizer)
[
p.name,
t,
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),
round(data.c_fix[p, t] * 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,
),
round(data.c_fix[p, t] * value(x_open[p, t]), digits = 2),
],
)
end
@ -1036,10 +1177,19 @@ function solve(filename, optimizer)
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(sum(value(y[p, q, r][c, t]) for (q, r2) in E_out[p] if r == r2; init = 0.0), digits=2),
round(data.c_plant_disp[p, r, t] * 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,
),
digits = 2,
),
round(
data.c_plant_disp[p, r, t] * value(z_plant_disp[p, r, c, t]),
digits = 2,
),
],
)
end
@ -1060,8 +1210,11 @@ function solve(filename, optimizer)
p.name,
s.name,
t,
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),
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,
),
],
)
end
@ -1091,16 +1244,17 @@ function solve(filename, optimizer)
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.c_emission[s, t] * 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,
),
],
)
end
CSV.write("$output_dir/transp-emissions.csv", df)
print_timer()
return
return stats
end

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