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Move graph creation to graph.jl; simplify model.jl

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This commit is contained in:
Alinson S. Xavier
2020-05-03 16:04:57 -05:00
parent aa4f6537fe
commit cbd7bc5247
8 changed files with 458 additions and 484 deletions
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5
src/ReverseManufacturing.jl
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@@ -2,7 +2,8 @@
# Written by Alinson Santos Xavier <axavier@anl.gov>
module ReverseManufacturing
#include("dotdict.jl")
include("dotdict.jl")
include("instance.jl")
#include("model.jl")
include("graph.jl")
include("model.jl")
end

125
src/graph.jl Normal file
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@@ -0,0 +1,125 @@
# Copyright (C) 2019 Argonne National Laboratory
# Written by Alinson Santos Xavier <axavier@anl.gov>
using Geodesy
abstract type Node
end
mutable struct Arc
source::Node
dest::Node
values::Dict{String, Float64}
end
mutable struct ProcessNode <: Node
index::Int
plant::Plant
incoming_arcs::Array{Arc}
outgoing_arcs::Array{Arc}
end
mutable struct ShippingNode <: Node
index::Int
location::Union{Plant, CollectionCenter}
product::Product
incoming_arcs::Array{Arc}
outgoing_arcs::Array{Arc}
end
mutable struct Graph
process_nodes::Array{ProcessNode}
plant_shipping_nodes::Array{ShippingNode}
collection_shipping_nodes::Array{ShippingNode}
arcs::Array{Arc}
end
function build_graph(instance::Instance)::Graph
arcs = []
next_index = 0
process_nodes = ProcessNode[]
plant_shipping_nodes = ShippingNode[]
collection_shipping_nodes = ShippingNode[]
process_nodes_by_input_product = Dict(product => ProcessNode[]
for product in instance.products)
shipping_nodes_by_plant = Dict(plant => []
for plant in instance.plants)
# Build collection center shipping nodes
for center in instance.collection_centers
node = ShippingNode(next_index, center, center.product, [], [])
next_index += 1
push!(collection_shipping_nodes, node)
end
# Build process and shipping nodes for plants
for plant in instance.plants
pn = ProcessNode(next_index, plant, [], [])
next_index += 1
push!(process_nodes, pn)
push!(process_nodes_by_input_product[plant.input], pn)
for product in keys(plant.output)
sn = ShippingNode(next_index, plant, product, [], [])
next_index += 1
push!(plant_shipping_nodes, sn)
push!(shipping_nodes_by_plant[plant], sn)
end
end
# Build arcs from collection centers to plants, and from one plant to another
for source in [collection_shipping_nodes; plant_shipping_nodes]
for dest in process_nodes_by_input_product[source.product]
distance = calculate_distance(source.location.latitude,
source.location.longitude,
dest.plant.latitude,
dest.plant.longitude)
values = Dict("distance" => distance)
arc = Arc(source, dest, values)
push!(source.outgoing_arcs, arc)
push!(dest.incoming_arcs, arc)
push!(arcs, arc)
end
end
# Build arcs from process nodes to shipping nodes within a plant
for source in process_nodes
plant = source.plant
for dest in shipping_nodes_by_plant[plant]
weight = plant.output[dest.product]
values = Dict("weight" => weight)
arc = Arc(source, dest, values)
push!(source.outgoing_arcs, arc)
push!(dest.incoming_arcs, arc)
push!(arcs, arc)
end
end
return Graph(process_nodes,
plant_shipping_nodes,
collection_shipping_nodes,
arcs)
end
function to_csv(graph::Graph)
result = ""
for a in graph.arcs
result *= "$(a.source.index),$(a.dest.index)\n"
end
return result
end
function calculate_distance(source_lat, source_lon, dest_lat, dest_lon)::Float64
x = LLA(source_lat, source_lon, 0.0)
y = LLA(dest_lat, dest_lon, 0.0)
return round(distance(x, y) / 1000.0, digits=2)
end

31
src/instance.jl
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@@ -19,15 +19,9 @@ struct CollectionCenter
end
struct DisposalEntry
product::Product
cost::Float64
limit::Float64
end
struct Plant
name::String
plant_name::String
location_name::String
input::Product
output::Dict{Product, Float64}
latitude::Float64
@@ -38,7 +32,8 @@ struct Plant
base_capacity::Float64
max_capacity::Float64
expansion_cost::Float64
disposal::Array{DisposalEntry}
disposal_limit::Dict{Product, Float64}
disposal_cost::Dict{Product, Float64}
end
@@ -98,19 +93,19 @@ function load(path::String)::Instance
end
for (location_name, location_dict) in plant_dict["locations"]
disposal = DisposalEntry[]
disposal_limit = Dict(p => 0.0 for p in keys(output))
disposal_cost = Dict(p => 0.0 for p in keys(output))
# Plant disposal
if "disposal" in keys(location_dict)
for (product_name, disposal_dict) in location_dict["disposal"]
push!(disposal, DisposalEntry(product_name_to_product[product_name],
disposal_dict["cost"],
disposal_dict["limit"]))
disposal_limit[product_name_to_product[product_name]] = disposal_dict["limit"]
disposal_cost[product_name_to_product[product_name]] = disposal_dict["cost"]
end
end
base_capacity = Inf
max_capacity = Inf
base_capacity = 1e8
max_capacity = 1e8
expansion_cost = 0
if "base capacity" in keys(location_dict)
@@ -125,7 +120,8 @@ function load(path::String)::Instance
expansion_cost = location_dict["expansion cost"]
end
plant = Plant(location_name,
plant = Plant(plant_name,
location_name,
input,
output,
location_dict["latitude"],
@@ -136,7 +132,8 @@ function load(path::String)::Instance
base_capacity,
max_capacity,
expansion_cost,
disposal)
disposal_limit,
disposal_cost)
push!(plants, plant)
end
end

591
src/model.jl
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@@ -3,460 +3,269 @@
using JuMP, LinearAlgebra, Geodesy, Cbc, ProgressBars
mutable struct ReverseManufacturingModel
mutable struct ManufacturingModel
mip::JuMP.Model
vars::DotDict
arcs
shipping_nodes
process_nodes
instance::Instance
graph::Graph
end
abstract type Node
function build_model(instance::Instance, graph::Graph, optimizer)::ManufacturingModel
model = ManufacturingModel(Model(optimizer), DotDict(), instance, graph)
create_vars!(model)
create_objective_function!(model)
create_shipping_node_constraints!(model)
create_process_node_constraints!(model)
return model
end
mutable struct ProcessNode <: Node
product_name::String
plant_name::String
location_name::String
incoming_arcs::Array
outgoing_arcs::Array
fixed_cost::Float64
expansion_cost::Float64
base_capacity::Float64
max_capacity::Float64
end
mutable struct ShippingNode <: Node
product_name::String
plant_name::String
location_name::String
incoming_arcs::Array
outgoing_arcs::Array
balance::Float64
disposal_cost::Float64
disposal_limit::Float64
end
function create_vars!(model::ManufacturingModel)
mip, vars, graph = model.mip, model.vars, model.graph
function Base.show(io::IO, node::ProcessNode)
print(io, "ProcessNode($(node.product_name), $(node.plant_name), $(node.location_name), fixed_cost=$(node.fixed_cost))")
end
vars.flow = Dict(a => @variable(mip, lower_bound=0)
for a in graph.arcs)
function Base.show(io::IO, node::ShippingNode)
print(io, "ShippingNode($(node.product_name), $(node.plant_name), $(node.location_name), balance=$(node.balance), ")
print(io, "disposal_cost=$(node.disposal_cost), disposal_limit=$(node.disposal_limit))")
end
mutable struct Arc
# Origin of the arc
source::Node
# Destination of the arc
dest::Node
# Costs dictionary. Each value in this dictionary is multiplied by the arc flow variable
# and added to the objective function.
costs::Dict
# Values dictionary. This dictionary is used to store extra information about the
# arc. They are not used automatically by the model.
values::Dict
end
function Base.show(io::IO, arc::Arc)
print(io, "Arc($(arc.source), $(arc.dest))")
end
function build_model(instance::ReverseManufacturingInstance,
optimizer,
) :: ReverseManufacturingModel
println("Building optimization model...")
mip = Model(optimizer)
shipping_nodes, process_nodes, arcs = create_nodes_and_arcs(instance)
println(" $(length(shipping_nodes)) shipping nodes")
println(" $(length(process_nodes)) process nodes")
println(" $(length(arcs)) arcs")
vars = DotDict()
vars.flow = Dict(a => @variable(mip, lower_bound=0) for a in arcs)
vars.dispose = Dict(n => @variable(mip,
lower_bound = 0,
upper_bound = n.disposal_limit)
for n in values(shipping_nodes))
vars.open_plant = Dict(n => @variable(mip, binary=true) for n in values(process_nodes))
vars.capacity = Dict(n => @variable(mip, lower_bound = 0, upper_bound = n.max_capacity)
for n in values(process_nodes))
vars.expansion = Dict(n => @variable(mip, lower_bound = 0, upper_bound = (n.max_capacity - n.base_capacity))
for n in values(process_nodes))
create_shipping_node_constraints!(mip, shipping_nodes, vars)
create_process_node_constraints!(mip, process_nodes, vars)
upper_bound = n.location.disposal_limit[n.product])
for n in values(graph.plant_shipping_nodes))
println(" Creating objective function...")
vars.open_plant = Dict(n => @variable(mip, binary=true)
for n in values(graph.process_nodes))
vars.capacity = Dict(n => @variable(mip,
lower_bound = 0,
upper_bound = n.plant.max_capacity)
for n in values(graph.process_nodes))
vars.expansion = Dict(n => @variable(mip,
lower_bound = 0,
upper_bound = (n.plant.max_capacity - n.plant.base_capacity))
for n in values(graph.process_nodes))
end
function create_objective_function!(model::ManufacturingModel)
mip, vars, graph = model.mip, model.vars, model.graph
obj = @expression(mip, 0 * @variable(mip))
# Shipping and variable operating costs
for a in tqdm(arcs)
for c in keys(a.costs)
add_to_expression!(obj, a.costs[c], vars.flow[a])
end
# Process node costs
for n in values(graph.process_nodes)
# Transportation and variable operating costs
for a in n.incoming_arcs
c = n.plant.input.transportation_cost * a.values["distance"]
c += n.plant.variable_operating_cost
add_to_expression!(obj, c, vars.flow[a])
end
# Opening and fixed operating costs
for n in tqdm(values(process_nodes))
add_to_expression!(obj, n.fixed_cost, vars.open_plant[n])
end
# Fixed and opening costss
add_to_expression!(obj,
n.plant.fixed_operating_cost + n.plant.opening_cost,
vars.open_plant[n])
# Expansion cost
for n in tqdm(values(process_nodes))
add_to_expression!(obj, n.expansion_cost, vars.expansion[n])
# Expansion costs
add_to_expression!(obj, n.plant.expansion_cost,
vars.expansion[n])
end
# Disposal costs
for n in tqdm(values(shipping_nodes))
add_to_expression!(obj, n.disposal_cost, vars.dispose[n])
for n in values(graph.plant_shipping_nodes)
add_to_expression!(obj,
n.location.disposal_cost[n.product],
vars.dispose[n])
end
@objective(mip, Min, obj)
return ReverseManufacturingModel(mip,
vars,
arcs,
shipping_nodes,
process_nodes)
end
function create_shipping_node_constraints!(mip, nodes, vars)
println(" Creating shipping-node constraints...")
for (id, n) in tqdm(nodes)
function create_shipping_node_constraints!(model::ManufacturingModel)
mip, vars, graph = model.mip, model.vars, model.graph
# Collection centers
for n in graph.collection_shipping_nodes
@constraint(mip, sum(vars.flow[a] for a in n.outgoing_arcs) == n.location.amount)
end
# Plants
for n in graph.plant_shipping_nodes
@constraint(mip,
sum(vars.flow[a] for a in n.incoming_arcs) + n.balance ==
sum(vars.flow[a] for a in n.incoming_arcs) ==
sum(vars.flow[a] for a in n.outgoing_arcs) + vars.dispose[n])
end
end
function create_process_node_constraints!(mip, nodes, vars)
println(" Creating process-node constraints...")
for (id, n) in tqdm(nodes)
function create_process_node_constraints!(model)
mip, vars, graph = model.mip, model.vars, model.graph
for n in graph.process_nodes
# Output amount is implied by input amount
input_sum = isempty(n.incoming_arcs) ? 0 : sum(vars.flow[a] for a in n.incoming_arcs)
for a in n.outgoing_arcs
@constraint(mip, vars.flow[a] == a.values["weight"] * input_sum)
end
# If plant is closed, capacity is zero.
@constraint(mip, vars.capacity[n] <= n.max_capacity * vars.open_plant[n])
# If plant is closed, capacity is zero
@constraint(mip, vars.capacity[n] <= n.plant.max_capacity * vars.open_plant[n])
# Capacity is linked to expansion
@constraint(mip, vars.capacity[n] <= n.base_capacity + vars.expansion[n])
@constraint(mip, vars.capacity[n] <= n.plant.base_capacity + vars.expansion[n])
# Input sum must be smaller than capacity
@constraint(mip, input_sum <= vars.capacity[n])
end
end
function create_nodes_and_arcs(instance)
println(" Creating nodes and arcs...")
arcs = Arc[]
shipping_nodes = Dict()
process_nodes = Dict()
function solve(filename::String; optimizer=Cbc.Optimizer)
println("Reading $filename...")
instance = ReverseManufacturing.load(filename)
# Create all nodes
for (product_name, product) in instance.products
println("Building graph...")
graph = ReverseManufacturing.build_graph(instance)
# Shipping nodes for initial amounts
if haskey(product, "initial amounts")
for location_name in keys(product["initial amounts"])
balance = product["initial amounts"][location_name]["amount"]
n = ShippingNode(product_name,
"Origin", # plant_name
location_name,
[], # incoming_arcs
[], # outgoing_arcs
balance,
0.0, # disposal_cost
0.0, # disposal_limit
)
shipping_nodes[n.product_name, n.plant_name, n.location_name] = n
end
end
# Process nodes for each plant
for plant in product["input plants"]
for (location_name, location) in plant["locations"]
base_capacity = 1e8
max_capacity = 1e8
expansion_cost = 0.0
fixed_cost = location["opening cost"] + location["fixed operating cost"]
if "base capacity" in keys(location)
base_capacity = location["base capacity"]
end
if "max capacity" in keys(location)
max_capacity = location["max capacity"]
end
if "expansion cost" in keys(location)
expansion_cost = location["expansion cost"]
end
n = ProcessNode(product_name,
plant["name"],
location_name,
[], # incoming_arcs
[], # outgoing_arcs
fixed_cost,
expansion_cost,
base_capacity,
max_capacity)
process_nodes[n.product_name, n.plant_name, n.location_name] = n
end
end
# Shipping nodes for each plant
for plant in product["output plants"]
for (location_name, location) in plant["locations"]
disposal_cost = 0.0
disposal_limit = 0.0
if "disposal" in keys(location) && product_name in keys(location["disposal"])
dict = location["disposal"][product_name]
disposal_cost = dict["cost"]
if "limit" in keys(dict)
disposal_limit = dict["limit"]
else
disposal_limit = 1e10
end
end
n = ShippingNode(product_name,
plant["name"],
location_name,
[], # incoming_arcs
[], # outgoing_arcs
0.0, # balance
disposal_cost,
disposal_limit,
)
shipping_nodes[n.product_name, n.plant_name, n.location_name] = n
end
end
end
# Create arcs
for (product_name, product) in instance.products
# Transportation arcs from initial location to plants
if haskey(product, "initial amounts")
for source_location_name in keys(product["initial amounts"])
source_location = product["initial amounts"][source_location_name]
for dest_plant in product["input plants"]
for dest_location_name in keys(dest_plant["locations"])
dest_location = dest_plant["locations"][dest_location_name]
source = shipping_nodes[product_name, "Origin", source_location_name]
dest = process_nodes[product_name, dest_plant["name"], dest_location_name]
distance = calculate_distance(source_location["latitude"],
source_location["longitude"],
dest_location["latitude"],
dest_location["longitude"])
costs = Dict("transportation" => product["transportation cost"] * distance,
"variable" => dest_location["variable operating cost"])
values = Dict("distance" => distance)
a = Arc(source, dest, costs, values)
push!(arcs, a)
push!(source.outgoing_arcs, a)
push!(dest.incoming_arcs, a)
end
end
end
end
for source_plant in product["output plants"]
for source_location_name in keys(source_plant["locations"])
source_location = source_plant["locations"][source_location_name]
# Process arcs (conversions within a plant)
source = process_nodes[source_plant["input"], source_plant["name"], source_location_name]
dest = shipping_nodes[product_name, source_plant["name"], source_location_name]
costs = Dict()
values = Dict("weight" => source_plant["outputs"][product_name])
a = Arc(source, dest, costs, values)
push!(arcs, a)
push!(source.outgoing_arcs, a)
push!(dest.incoming_arcs, a)
# Transportation arcs (from one plant to another)
for dest_plant in product["input plants"]
for dest_location_name in keys(dest_plant["locations"])
dest_location = dest_plant["locations"][dest_location_name]
source = shipping_nodes[product_name,
source_plant["name"],
source_location_name]
dest = process_nodes[product_name, dest_plant["name"], dest_location_name]
distance = calculate_distance(source_location["latitude"],
source_location["longitude"],
dest_location["latitude"],
dest_location["longitude"])
costs = Dict("transportation" => product["transportation cost"] * distance,
"variable" => dest_location["variable operating cost"])
values = Dict("distance" => distance)
a = Arc(source, dest, costs, values)
push!(arcs, a)
push!(source.outgoing_arcs, a)
push!(dest.incoming_arcs, a)
end
end
end
end
end
return shipping_nodes, process_nodes, arcs
end
function calculate_distance(source_lat, source_lon, dest_lat, dest_lon)::Float64
x = LLA(source_lat, source_lon, 0.0)
y = LLA(dest_lat, dest_lon, 0.0)
return round(distance(x, y) / 1000.0, digits=2)
end
function solve(filename::String;
optimizer=Cbc.Optimizer)
println("Reading $filename")
instance = ReverseManufacturing.readfile(filename)
model = ReverseManufacturing.build_model(instance, optimizer)
println("Building optimization model...")
model = ReverseManufacturing.build_model(instance, graph, optimizer)
println("Optimizing...")
JuMP.optimize!(model.mip)
println("Extracting solution...")
return get_solution(instance, model)
# println("Extracting solution...")
# return get_solution(instance, model)
end
function get_solution(instance::ReverseManufacturingInstance,
model::ReverseManufacturingModel)
vals = Dict()
for a in values(model.arcs)
vals[a] = JuMP.value(model.vars.flow[a])
end
for n in values(model.process_nodes)
vals[n] = JuMP.value(model.vars.open_plant[n])
end
# function get_solution(instance::ReverseManufacturingInstance,
# model::ReverseManufacturingModel)
# vals = Dict()
# for a in values(model.arcs)
# vals[a] = JuMP.value(model.vars.flow[a])
# end
# for n in values(model.process_nodes)
# vals[n] = JuMP.value(model.vars.open_plant[n])
# end
output = Dict(
"plants" => Dict(),
"costs" => Dict(
"fixed" => 0.0,
"variable" => 0.0,
"transportation" => 0.0,
"disposal" => 0.0,
"total" => 0.0,
"expansion" => 0.0,
)
)
# output = Dict(
# "plants" => Dict(),
# "costs" => Dict(
# "fixed" => 0.0,
# "variable" => 0.0,
# "transportation" => 0.0,
# "disposal" => 0.0,
# "total" => 0.0,
# "expansion" => 0.0,
# )
# )
for (plant_name, plant) in instance.plants
skip_plant = true
plant_dict = Dict{Any, Any}()
input_product_name = plant["input"]
# for (plant_name, plant) in instance.plants
# skip_plant = true
# plant_dict = Dict{Any, Any}()
# input_product_name = plant["input"]
for (location_name, location) in plant["locations"]
skip_location = true
process_node = model.process_nodes[input_product_name, plant_name, location_name]
# for (location_name, location) in plant["locations"]
# skip_location = true
# process_node = model.process_nodes[input_product_name, plant_name, location_name]
plant_loc_dict = Dict{Any, Any}(
"input" => Dict(),
"output" => Dict(
"send" => Dict(),
"dispose" => Dict(),
),
"total input" => 0.0,
"total output" => Dict(),
"latitude" => location["latitude"],
"longitude" => location["longitude"],
"capacity" => round(JuMP.value(model.vars.capacity[process_node]), digits=2)
)
# plant_loc_dict = Dict{Any, Any}(
# "input" => Dict(),
# "output" => Dict(
# "send" => Dict(),
# "dispose" => Dict(),
# ),
# "total input" => 0.0,
# "total output" => Dict(),
# "latitude" => location["latitude"],
# "longitude" => location["longitude"],
# "capacity" => round(JuMP.value(model.vars.capacity[process_node]), digits=2)
# )
plant_loc_dict["fixed cost"] = round(vals[process_node] * process_node.fixed_cost, digits=5)
plant_loc_dict["expansion cost"] = round(JuMP.value(model.vars.expansion[process_node]) * process_node.expansion_cost, digits=5)
output["costs"]["fixed"] += plant_loc_dict["fixed cost"]
output["costs"]["expansion"] += plant_loc_dict["expansion cost"]
# plant_loc_dict["fixed cost"] = round(vals[process_node] * process_node.fixed_cost, digits=5)
# plant_loc_dict["expansion cost"] = round(JuMP.value(model.vars.expansion[process_node]) * process_node.expansion_cost, digits=5)
# output["costs"]["fixed"] += plant_loc_dict["fixed cost"]
# output["costs"]["expansion"] += plant_loc_dict["expansion cost"]
# Inputs
for a in process_node.incoming_arcs
if vals[a] <= 1e-3
continue
end
skip_plant = skip_location = false
val = round(vals[a], digits=5)
if !(a.source.plant_name in keys(plant_loc_dict["input"]))
plant_loc_dict["input"][a.source.plant_name] = Dict()
end
if a.source.plant_name == "Origin"
product = instance.products[a.source.product_name]
source_location = product["initial amounts"][a.source.location_name]
else
source_plant = instance.plants[a.source.plant_name]
source_location = source_plant["locations"][a.source.location_name]
end
# # Inputs
# for a in process_node.incoming_arcs
# if vals[a] <= 1e-3
# continue
# end
# skip_plant = skip_location = false
# val = round(vals[a], digits=5)
# if !(a.source.plant_name in keys(plant_loc_dict["input"]))
# plant_loc_dict["input"][a.source.plant_name] = Dict()
# end
# if a.source.plant_name == "Origin"
# product = instance.products[a.source.product_name]
# source_location = product["initial amounts"][a.source.location_name]
# else
# source_plant = instance.plants[a.source.plant_name]
# source_location = source_plant["locations"][a.source.location_name]
# end
# Input
cost_transportation = round(a.costs["transportation"] * val, digits=5)
plant_loc_dict["input"][a.source.plant_name][a.source.location_name] = dict = Dict()
cost_variable = round(a.costs["variable"] * val, digits=5)
dict["amount"] = val
dict["distance"] = a.values["distance"]
dict["transportation cost"] = cost_transportation
dict["variable operating cost"] = cost_variable
dict["latitude"] = source_location["latitude"]
dict["longitude"] = source_location["longitude"]
plant_loc_dict["total input"] += val
# # Input
# cost_transportation = round(a.costs["transportation"] * val, digits=5)
# plant_loc_dict["input"][a.source.plant_name][a.source.location_name] = dict = Dict()
# cost_variable = round(a.costs["variable"] * val, digits=5)
# dict["amount"] = val
# dict["distance"] = a.values["distance"]
# dict["transportation cost"] = cost_transportation
# dict["variable operating cost"] = cost_variable
# dict["latitude"] = source_location["latitude"]
# dict["longitude"] = source_location["longitude"]
# plant_loc_dict["total input"] += val
output["costs"]["transportation"] += cost_transportation
output["costs"]["variable"] += cost_variable
end
# output["costs"]["transportation"] += cost_transportation
# output["costs"]["variable"] += cost_variable
# end
# Outputs
for output_product_name in keys(plant["outputs"])
plant_loc_dict["total output"][output_product_name] = 0.0
plant_loc_dict["output"]["send"][output_product_name] = product_dict = Dict()
shipping_node = model.shipping_nodes[output_product_name, plant_name, location_name]
# # Outputs
# for output_product_name in keys(plant["outputs"])
# plant_loc_dict["total output"][output_product_name] = 0.0
# plant_loc_dict["output"]["send"][output_product_name] = product_dict = Dict()
# shipping_node = model.shipping_nodes[output_product_name, plant_name, location_name]
disposal_amount = JuMP.value(model.vars.dispose[shipping_node])
if disposal_amount > 1e-5
plant_loc_dict["output"]["dispose"][output_product_name] = disposal_dict = Dict()
disposal_dict["amount"] = JuMP.value(model.vars.dispose[shipping_node])
disposal_dict["cost"] = disposal_dict["amount"] * shipping_node.disposal_cost
plant_loc_dict["total output"][output_product_name] += disposal_amount
output["costs"]["disposal"] += disposal_dict["cost"]
end
# disposal_amount = JuMP.value(model.vars.dispose[shipping_node])
# if disposal_amount > 1e-5
# plant_loc_dict["output"]["dispose"][output_product_name] = disposal_dict = Dict()
# disposal_dict["amount"] = JuMP.value(model.vars.dispose[shipping_node])
# disposal_dict["cost"] = disposal_dict["amount"] * shipping_node.disposal_cost
# plant_loc_dict["total output"][output_product_name] += disposal_amount
# output["costs"]["disposal"] += disposal_dict["cost"]
# end
for a in shipping_node.outgoing_arcs
if vals[a] <= 1e-3
continue
end
skip_plant = skip_location = false
if !(a.dest.plant_name in keys(product_dict))
product_dict[a.dest.plant_name] = Dict{Any,Any}()
end
dest_location = instance.plants[a.dest.plant_name]["locations"][a.dest.location_name]
val = round(vals[a], digits=5)
plant_loc_dict["total output"][output_product_name] += val
product_dict[a.dest.plant_name][a.dest.location_name] = dict = Dict()
dict["amount"] = val
dict["distance"] = a.values["distance"]
dict["latitude"] = dest_location["latitude"]
dict["longitude"] = dest_location["longitude"]
end
end
# for a in shipping_node.outgoing_arcs
# if vals[a] <= 1e-3
# continue
# end
# skip_plant = skip_location = false
# if !(a.dest.plant_name in keys(product_dict))
# product_dict[a.dest.plant_name] = Dict{Any,Any}()
# end
# dest_location = instance.plants[a.dest.plant_name]["locations"][a.dest.location_name]
# val = round(vals[a], digits=5)
# plant_loc_dict["total output"][output_product_name] += val
# product_dict[a.dest.plant_name][a.dest.location_name] = dict = Dict()
# dict["amount"] = val
# dict["distance"] = a.values["distance"]
# dict["latitude"] = dest_location["latitude"]
# dict["longitude"] = dest_location["longitude"]
# end
# end
if !skip_location
plant_dict[location_name] = plant_loc_dict
end
end
if !skip_plant
output["plants"][plant_name] = plant_dict
end
end
# if !skip_location
# plant_dict[location_name] = plant_loc_dict
# end
# end
# if !skip_plant
# output["plants"][plant_name] = plant_dict
# end
# end
output["costs"]["total"] = sum(values(output["costs"]))
return output
end
# output["costs"]["total"] = sum(values(output["costs"]))
# return output
# end
export FlowArc

42
test/graph_test.jl Normal file
View File

@@ -0,0 +1,42 @@
# Copyright (C) 2020 Argonne National Laboratory
# Written by Alinson Santos Xavier <axavier@anl.gov>
using ReverseManufacturing
@testset "Graph" begin
@testset "build_graph" begin
basedir = dirname(@__FILE__)
instance = ReverseManufacturing.load("$basedir/../instances/samples/s1.json")
graph = ReverseManufacturing.build_graph(instance)
process_node_by_location_name = Dict(n.plant.location_name => n
for n in graph.process_nodes)
@test length(graph.plant_shipping_nodes) == 8
@test length(graph.collection_shipping_nodes) == 10
@test length(graph.process_nodes) == 6
node = graph.collection_shipping_nodes[1]
@test node.location.name == "C1"
@test length(node.incoming_arcs) == 0
@test length(node.outgoing_arcs) == 2
@test node.outgoing_arcs[1].source.location.name == "C1"
@test node.outgoing_arcs[1].dest.plant.plant_name == "F1"
@test node.outgoing_arcs[1].dest.plant.location_name == "L1"
@test node.outgoing_arcs[1].values["distance"] == 1095.62
node = process_node_by_location_name["L1"]
@test node.plant.plant_name == "F1"
@test node.plant.location_name == "L1"
@test length(node.incoming_arcs) == 10
@test length(node.outgoing_arcs) == 2
node = process_node_by_location_name["L3"]
@test node.plant.plant_name == "F2"
@test node.plant.location_name == "L3"
@test length(node.incoming_arcs) == 2
@test length(node.outgoing_arcs) == 2
@test length(graph.arcs) == 38
end
end

34
test/instance_test.jl
View File

@@ -12,11 +12,9 @@ using ReverseManufacturing
plants = instance.plants
products = instance.products
plant_name_to_plant = Dict(p.name => p for p in plants)
location_name_to_plant = Dict(p.location_name => p for p in plants)
product_name_to_product = Dict(p.name => p for p in products)
p2 = product_name_to_product["P2"]
p3 = product_name_to_product["P3"]
@test length(centers) == 10
@test centers[1].name == "C1"
@@ -28,8 +26,9 @@ using ReverseManufacturing
@test length(plants) == 6
plant = plant_name_to_plant["L1"]
@test plant.name == "L1"
plant = location_name_to_plant["L1"]
@test plant.plant_name == "F1"
@test plant.location_name == "L1"
@test plant.input.name == "P1"
@test plant.latitude == 0
@test plant.longitude == 0
@@ -40,26 +39,33 @@ using ReverseManufacturing
@test plant.max_capacity == 1000
@test plant.expansion_cost == 1
p2 = product_name_to_product["P2"]
p3 = product_name_to_product["P3"]
@test length(plant.output) == 2
@test plant.output[p2] == 0.2
@test plant.output[p3] == 0.5
@test plant.disposal_limit[p2] == 1
@test plant.disposal_limit[p3] == 1
@test plant.disposal_cost[p2] == -10
@test plant.disposal_cost[p3] == -10
@test length(plant.disposal) == 2
@test plant.disposal[1].product.name == "P2"
@test plant.disposal[1].cost == -10
@test plant.disposal[1].limit == 1
plant = plant_name_to_plant["L3"]
@test plant.name == "L3"
plant = location_name_to_plant["L3"]
@test plant.location_name == "L3"
@test plant.input.name == "P2"
@test plant.latitude == 25
@test plant.longitude == 65
@test plant.opening_cost == 3000
@test plant.fixed_operating_cost == 50
@test plant.variable_operating_cost == 50
@test plant.base_capacity == Inf
@test plant.max_capacity == Inf
@test plant.base_capacity == 1e8
@test plant.max_capacity == 1e8
@test plant.expansion_cost == 0
p4 = product_name_to_product["P4"]
@test plant.output[p3] == 0.05
@test plant.output[p4] == 0.8
@test plant.disposal_limit[p3] == 0.0
@test plant.disposal_limit[p4] == 0.0
end
end

87
test/model_test.jl
View File

@@ -4,61 +4,54 @@
using ReverseManufacturing, Cbc, JuMP, Printf, JSON
@testset "Model" begin
instance = ReverseManufacturing.load("samples/s1")
model = ReverseManufacturing.build_model(instance, Cbc.Optimizer)
@testset "build" begin
basedir = dirname(@__FILE__)
instance = ReverseManufacturing.load("$basedir/../instances/samples/s1.json")
graph = ReverseManufacturing.build_graph(instance)
model = ReverseManufacturing.build_model(instance, graph, Cbc.Optimizer)
# Verify nodes
@test ("P1", "Origin", "C1") in keys(model.shipping_nodes)
@test ("P1", "Origin", "C3") in keys(model.shipping_nodes)
@test ("P1", "Origin", "C8") in keys(model.shipping_nodes)
@test ("P2", "F1", "L1") in keys(model.shipping_nodes)
@test ("P2", "F1", "L2") in keys(model.shipping_nodes)
@test ("P3", "F1", "L1") in keys(model.shipping_nodes)
@test ("P3", "F1", "L2") in keys(model.shipping_nodes)
@test ("P3", "F2", "L3") in keys(model.shipping_nodes)
@test ("P3", "F2", "L4") in keys(model.shipping_nodes)
@test ("P4", "F2", "L3") in keys(model.shipping_nodes)
@test ("P4", "F2", "L4") in keys(model.shipping_nodes)
@test ("P1", "F1", "L1") in keys(model.process_nodes)
@test ("P1", "F1", "L2") in keys(model.process_nodes)
@test ("P2", "F2", "L3") in keys(model.process_nodes)
@test ("P2", "F2", "L4") in keys(model.process_nodes)
@test ("P3", "F4", "L6") in keys(model.process_nodes)
@test ("P4", "F3", "L5") in keys(model.process_nodes)
process_node_by_location_name = Dict(n.plant.location_name => n
for n in graph.process_nodes)
# Verify some arcs
p1_orig_c1 = model.shipping_nodes["P1", "Origin", "C1"]
p1_f1_l1 = model.process_nodes["P1", "F1", "L1"]
@test length(p1_orig_c1.outgoing_arcs) == 2
@test length(p1_f1_l1.incoming_arcs) == 10
shipping_node_by_location_and_product_names = Dict((n.location.location_name, n.product.name) => n
for n in graph.plant_shipping_nodes)
arc = p1_orig_c1.outgoing_arcs[1]
@test arc.dest.location_name == "L1"
@test arc.values["distance"] == 1095.62
@test round(arc.costs["transportation"], digits=2) == 16.43
@test arc.costs["variable"] == 30.0
p2_f1_l1 = model.shipping_nodes["P2", "F1", "L1"]
p2_f2_l3 = model.process_nodes["P2", "F2", "L3"]
@test length(p2_f1_l1.incoming_arcs) == 1
@test length(p2_f1_l1.outgoing_arcs) == 2
@test length(model.vars.flow) == 38
@test length(model.vars.dispose) == 8
@test length(model.vars.open_plant) == 6
@test length(model.vars.capacity) == 6
@test length(model.vars.expansion) == 6
l1 = process_node_by_location_name["L1"]
v = model.vars.capacity[l1]
@test lower_bound(v) == 0.0
@test upper_bound(v) == 1000.0
v = model.vars.expansion[l1]
@test lower_bound(v) == 0.0
@test upper_bound(v) == 750.0
v = model.vars.dispose[shipping_node_by_location_and_product_names["L1", "P2"]]
@test lower_bound(v) == 0.0
@test upper_bound(v) == 1.0
arc = p2_f1_l1.incoming_arcs[1]
@test arc.values["weight"] == 0.2
@test isempty(arc.costs)
end
@testset "Solve" begin
@testset "build" begin
solution = ReverseManufacturing.solve("$(pwd())/../instances/samples/s1.json")
println(JSON.print(solution, 2))
# println(JSON.print(solution, 2))
@test "plants" in keys(solution)
@test "F1" in keys(solution["plants"])
@test "F2" in keys(solution["plants"])
@test "F3" in keys(solution["plants"])
@test "F4" in keys(solution["plants"])
@test "L2" in keys(solution["plants"]["F1"])
@test "total output" in keys(solution["plants"]["F1"]["L2"])
# @test "plants" in keys(solution)
# @test "F1" in keys(solution["plants"])
# @test "F2" in keys(solution["plants"])
# @test "F3" in keys(solution["plants"])
# @test "F4" in keys(solution["plants"])
# @test "L2" in keys(solution["plants"]["F1"])
# @test "total output" in keys(solution["plants"]["F1"]["L2"])
@test "capacity" in keys(solution["plants"]["F1"]["L1"])
# @test "capacity" in keys(solution["plants"]["F1"]["L1"])
end
end

3
test/runtests.jl
View File

@@ -5,5 +5,6 @@ using Test
@testset "ReverseManufacturing" begin
include("instance_test.jl")
#include("model_test.jl")
include("graph_test.jl")
include("model_test.jl")
end