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RELOG
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Implement get_solution; improve logging

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v0.1
Alinson S. Xavier 6 years ago
parent 9360edf94c
commit 640451c464
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GPG Key ID: A796166E4E218E02
2 changed files with 124 additions and 76 deletions
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15
src/instance.jl
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@ -53,6 +53,16 @@ Example
"""
function readfile(path::String)::ReverseManufacturingInstance
json = JSON.parsefile(path)
for plant_name in keys(json["plants"])
"outputs" in keys(json["plants"][plant_name]) || continue
for output_name in keys(json["plants"][plant_name]["outputs"])
if json["plants"][plant_name]["outputs"][output_name] < 1e-5
delete!(json["plants"][plant_name]["outputs"], output_name)
end
end
end
products = Dict(key => json["products"][key]
for key in keys(json["products"]))
plants = Dict(key => json["plants"][key]
@ -75,13 +85,14 @@ function readfile(path::String)::ReverseManufacturingInstance
push!(input_product["input plants"], plant)
# Output products
if haskey(plant, "outputs")
if !haskey(plant, "outputs")
plant["outputs"] = Dict()
end
for product_name in keys(plant["outputs"])
product = products[product_name]
push!(product["output plants"], plant)
end
end
end
return ReverseManufacturingInstance(json, products, plants)
end

187
src/model.jl
Unescape View File

@ -47,9 +47,15 @@ function Base.show(io::IO, node::Node)
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
@ -61,6 +67,7 @@ function build_model(instance::ReverseManufacturingInstance,
optimizer,
) :: ReverseManufacturingModel
println("Building optimization model...")
mip = isa(optimizer, JuMP.OptimizerFactory) ? Model(optimizer) : direct_model(optimizer)
decision_nodes, process_nodes, arcs = create_nodes_and_arcs(instance)
vars = DotDict()
@ -68,9 +75,19 @@ function build_model(instance::ReverseManufacturingInstance,
vars.node = Dict(n => @variable(mip, binary=true) for n in values(process_nodes))
create_decision_node_constraints!(mip, decision_nodes, vars)
create_process_node_constraints!(mip, process_nodes, vars)
flow_costs = sum(a.costs[c] * vars.flow[a] for a in arcs for c in keys(a.costs))
node_costs = sum(n.cost * vars.node[n] for n in values(process_nodes))
@objective(mip, Min, flow_costs + node_costs)
println(" Creating objective function...")
obj = @expression(mip, 0 * @variable(mip))
for a in arcs
for c in keys(a.costs)
add_to_expression!(obj, a.costs[c], vars.flow[a])
end
end
for n in values(process_nodes)
add_to_expression!(obj, n.cost, vars.node[n])
end
@objective(mip, Min, obj)
return return ReverseManufacturingModel(mip,
vars,
arcs,
@ -79,6 +96,7 @@ function build_model(instance::ReverseManufacturingInstance,
end
function create_decision_node_constraints!(mip, nodes, vars)
println(" Creating decision-node constraints...")
for (id, n) in nodes
@constraint(mip,
sum(vars.flow[a] for a in n.incoming_arcs) + n.balance ==
@ -87,9 +105,10 @@ function create_decision_node_constraints!(mip, nodes, vars)
end
function create_process_node_constraints!(mip, nodes, vars)
println(" Creating process-node constraints...")
for (id, n) in nodes
# Output amount is implied by input amount
input_sum = sum(vars.flow[a] for a in n.incoming_arcs)
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
@ -99,6 +118,7 @@ function create_process_node_constraints!(mip, nodes, vars)
end
function create_nodes_and_arcs(instance)
println(" Creating nodes and arcs...")
arcs = Arc[]
decision_nodes = Dict()
process_nodes = Dict()
@ -166,7 +186,7 @@ function create_nodes_and_arcs(instance)
for source_location_name in keys(source_plant["locations"])
source_location = source_plant["locations"][source_location_name]
# Process-arcs within a plant
# Process arcs (conversions within a plant)
source = process_nodes[source_plant["input"], source_plant["name"], source_location_name]
dest = decision_nodes[product_name, source_plant["name"], source_location_name]
costs = Dict()
@ -176,7 +196,7 @@ function create_nodes_and_arcs(instance)
push!(source.outgoing_arcs, a)
push!(dest.incoming_arcs, a)
# Transportation-arcs from one plant to another
# 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]
@ -207,7 +227,23 @@ function calculate_distance(source_lat, source_lon, dest_lat, dest_lon)::Float64
return round(distance(x, y) / 1000.0, digits=2)
end
function print_solution(instance, model)
function solve(filename::String;
optimizer=with_optimizer(Cbc.Optimizer,
logLevel=0))
println("Reading $filename")
instance = ReverseManufacturing.readfile(filename)
model = ReverseManufacturing.build_model(instance, optimizer)
println("Optimizing...")
JuMP.optimize!(model.mip)
println("Extracting solution...")
return get_solution(instance, model, vals)
end
function get_solution(instance::ReverseManufacturingInstance,
model::ReverseManufacturingModel)
vals = Dict()
for a in values(model.arcs)
vals[a] = JuMP.value(model.vars.flow[a])
@ -215,77 +251,78 @@ function print_solution(instance, model)
for n in values(model.process_nodes)
vals[n] = JuMP.value(model.vars.node[n])
end
output = Dict(
"plants" => Dict(),
"costs" => Dict(
"fixed" => 0.0,
"variable" => 0.0,
"transportation" => 0.0,
"total" => 0.0,
)
)
for (plant_name, plant) in instance.plants
input_product_name = plant["input"]
for (location_name, location) in plant["locations"]
unused = true
printstyled(@sprintf("%s (at %s):\n", plant_name, location_name),
bold=true,
color=:red)
for arc in model.arcs
arc.dest.plant_name == plant_name || continue
arc.dest.location_name == location_name || continue
arc.source.plant_name != plant_name || continue
vals[arc] > 0.0 || continue
@printf(" ← Receive %.2f kg of %s from %s (at %s)\n",
vals[arc],
arc.source.product_name,
arc.source.plant_name,
arc.source.location_name)
@printf(" Distance %.2f km\n", arc.values["distance"])
@printf(" Transportation cost %.2f USD\n",
vals[arc] * arc.costs["transportation"])
if arc.costs["variable"] > 0
@printf(" Variable operating cost %.2f USD\n",
arc.costs["variable"] * vals[arc])
else
@printf(" Revenue %.2f USD\n",
-arc.costs["variable"] * vals[arc])
end
unused = false
end
for arc in model.arcs
arc.source.plant_name == plant_name || continue
arc.source.location_name == location_name || continue
arc.dest.plant_name == plant_name || continue
arc.dest.location_name == location_name || continue
vals[arc] > 0.0 || continue
@printf(" ↺ Convert %.2f kg of %s into %.2f kg of %s\n",
vals[arc] / arc.values["weight"],
arc.source.product_name,
vals[arc],
arc.dest.product_name)
unused = false
end
for arc in model.arcs
arc.source.plant_name == plant_name || continue
arc.source.location_name == location_name || continue
arc.dest.plant_name != plant_name || continue
vals[arc] > 0.0 || continue
@printf(" → Send %.2f kg of %s to %s (at %s)\n",
vals[arc],
arc.dest.product_name,
arc.dest.plant_name,
arc.dest.location_name)
unused = false
end
if unused
println(" Not used")
end
println()
end
end
printstyled(@sprintf("Total profit: %.2f USD", -objective_value(model.mip)),
bold=true,
color=:red)
end
skip_plant = true
process_node = model.process_nodes[input_product_name, plant_name, location_name]
function solve(filename::String;
optimizer=with_optimizer(Cbc.Optimizer,
logLevel=0))
instance = ReverseManufacturing.readfile(filename)
model = ReverseManufacturing.build_model(instance, optimizer)
JuMP.optimize!(model.mip)
print_solution(instance, model)
dict = Dict{Any, Any}(
"input" => Dict(),
"output" => Dict(),
"total input" => 0.0,
"total output" => Dict(),
"transportation costs" => Dict(),
"variable costs" => Dict(),
)
dict["fixed cost"] = round(vals[process_node] * process_node.cost, digits=5)
output["costs"]["fixed"] += dict["fixed cost"]
# Inputs
for a in process_node.incoming_arcs
if vals[a] > 0
val = round(vals[a], digits=5)
skip_plant = false
source_key = "$(a.source.plant_name) ($(a.source.location_name))"
dict["input"][source_key] = val
dict["total input"] += val
cost_transportation = round(a.costs["transportation"] * val, digits=5)
cost_variable = round(a.costs["variable"] * val, digits=5)
dict["transportation costs"][source_key] = cost_transportation
dict["variable costs"][source_key] = cost_variable
output["costs"]["transportation"] += cost_transportation
output["costs"]["variable"] += cost_variable
end
end
# Outputs
for output_product_name in keys(plant["outputs"])
dict["output"][output_product_name] = output_dict = Dict()
dict["total output"][output_product_name] = 0.0
decision_node = model.decision_nodes[output_product_name, plant_name, location_name]
for a in decision_node.outgoing_arcs
if vals[a] > 0
val = round(vals[a], digits=5)
skip_plant = false
dict["total output"][output_product_name] += val
dest_key = "$(a.dest.plant_name) ($(a.dest.location_name))"
output_dict[dest_key] = val
end
end
end
if !skip_plant
key = "$(plant_name) ($(location_name))"
output["plants"][key] = dict
end
end
end
output["costs"]["total"] = sum(values(output["costs"]))
return output
end
export FlowArc

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