mirror of https://github.com/ANL-CEEESA/RELOG.git
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module RELOG
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module RELOG
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include("instance/structs.jl")
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include("instance/structs.jl")
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include("instance/parse.jl")
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include("instance/parse.jl")
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include("model/jumpext.jl")
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include("model/build.jl")
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end # module RELOG
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end # module RELOG
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@ -0,0 +1,95 @@
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using JuMP
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function build_model(instance::Instance; optimizer, variable_names::Bool = false)
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model = JuMP.Model(optimizer)
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centers = instance.centers
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products = instance.products
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plants = instance.plants
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T = 1:instance.time_horizon
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# Transportation edges
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# -------------------------------------------------------------------------
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E = []
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for m in products
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for p1 in plants
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m ∉ keys(p1.output) || continue
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# Plant to plant
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for p2 in plants
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p1 != p2 || continue
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m ∉ keys(p2.input_mix) || continue
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push!(E, (p1, p2, m))
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end
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# Plant to center
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for c in centers
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m == c.input || continue
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push!(E, (p1, c, m))
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end
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end
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for c1 in centers
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m ∈ c1.outputs || continue
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# Center to plant
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for p in plants
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m ∈ keys(p.input_mix) || continue
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push!(E, (c1, p, m))
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end
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# Center to center
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for c2 in centers
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m == c2.input || continue
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push!(E, (c1, c2, m))
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end
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end
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end
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# Decision variables
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# -------------------------------------------------------------------------
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# Plant p is operational at time t
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x = _init(model, :x)
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for p in plants, t in T
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x[p.name, t] = @variable(model, binary = true)
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end
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# Amount of product m sent from center/plant u to center/plant v at time T
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y = _init(model, :y)
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for (p1, p2, m) in E, t in T
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y[p1.name, p2.name, m.name, t] = @variable(model, lower_bound=0)
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end
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# Amount of product m produced by plant/center at time T
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z_prod = _init(model, :z_prod)
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for p in plants, m in keys(p.output), t in T
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z_prod[p.name, m.name, t] = @variable(model, lower_bound=0)
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end
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for c in centers, m in c.outputs, t in T
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z_prod[c.name, m.name, t] = @variable(model, lower_bound=0)
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end
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# Amount of product m disposed at plant/center p at time T
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z_disp = _init(model, :z_disp)
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for p in plants, m in keys(p.output), t in T
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z_disp[p.name, m.name, t] = @variable(model, lower_bound=0)
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end
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for c in centers, m in c.outputs, t in T
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z_disp[c.name, m.name, t] = @variable(model, lower_bound=0)
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end
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# Objective function
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# -------------------------------------------------------------------------
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# Constraints
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# -------------------------------------------------------------------------
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if variable_names
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_set_names!(model)
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end
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return model
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end
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@ -0,0 +1,47 @@
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# This file extends some JuMP functions so that decision variables can be safely
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# replaced by (constant) floating point numbers.
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using Printf
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using JuMP
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import JuMP: value, fix, set_name
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function value(x::Float64)
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return x
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end
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function fix(x::Float64, v::Float64; force)
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return abs(x - v) < 1e-6 || error("Value mismatch: $x != $v")
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end
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function set_name(x::Float64, n::String)
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# nop
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end
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function _init(model::JuMP.Model, key::Symbol)::OrderedDict
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if !(key in keys(object_dictionary(model)))
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model[key] = OrderedDict()
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end
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return model[key]
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end
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function _set_names!(model::JuMP.Model)
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@info "Setting variable and constraint names..."
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time_varnames = @elapsed begin
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_set_names!(object_dictionary(model))
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end
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@info @sprintf("Set names in %.2f seconds", time_varnames)
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end
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function _set_names!(dict::Dict)
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for name in keys(dict)
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dict[name] isa AbstractDict || continue
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for idx in keys(dict[name])
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if dict[name][idx] isa AffExpr
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continue
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end
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idx_str = join(map(string, idx), ",")
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set_name(dict[name][idx], "$name[$idx_str]")
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end
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end
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end
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@ -0,0 +1,10 @@
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using RELOG
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using Test
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using HiGHS
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using JuMP
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function model_build_test()
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instance = RELOG.parsefile(fixture("simple.json"))
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model = RELOG.build_model(instance, optimizer=HiGHS.Optimizer, variable_names=true)
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print(model)
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end
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