# The multi-commodity flow problem

JuMP implementation of the multicommodity transportation model AMPL: A Modeling Language for Mathematical Programming, 2nd ed by Robert Fourer, David Gay, and Brian W. Kernighan 4-1.

Originally contributed by Louis Luangkesorn, February 26, 2015.

using JuMP
import GLPK
import Test

function example_multi(; verbose = true)
orig = ["GARY", "CLEV", "PITT"]
dest = ["FRA", "DET", "LAN", "WIN", "STL", "FRE", "LAF"]
prod = ["bands", "coils", "plate"]
numorig = length(orig)
numdest = length(dest)
numprod = length(prod)
# supply(prod, orig) amounts available at origins
supply = [
400    700    800;
800   1600   1800;
200    300    300
]
# demand(prod, dest) amounts required at destinations
demand = [
300   300   100    75   650   225   250;
500   750   400   250   950   850   500;
100   100     0    50   200   100   250
]
# limit(orig, dest) of total units from any origin to destination
limit = [625.0 for j in 1:numorig, i in 1:numdest]
# cost(dest, orig, prod) Shipment cost per unit
cost = reshape([
[
[  30,   10,    8,   10,   11,   71,    6];
[  22,    7,   10,    7,   21,   82,   13];
[  19,   11,   12,   10,   25,   83,   15]
];
[
[  39,   14,   11,   14,   16,   82,    8];
[  27,    9,   12,    9,   26,   95,   17];
[  24,   14,   17,   13,   28,   99,   20]
];
[
[  41,   15,   12,   16,   17,   86,    8];
[  29,    9,   13,    9,   28,   99,   18];
[  26,   14,   17,   13,   31,  104,   20]
]
], 7, 3, 3)
# DECLARE MODEL
multi = Model(GLPK.Optimizer)
# VARIABLES
@variable(multi, trans[1:numorig, 1:numdest, 1:numprod] >= 0)
# OBJECTIVE
@objective(
multi,
Max,
sum(
cost[j, i, p] * trans[i, j, p]
for i in 1:numorig, j in 1:numdest, p in 1:numprod
)
)
# CONSTRAINTS
# Supply constraint
@constraint(
multi,
supply_con[i in 1:numorig, p in 1:numprod],
sum(trans[i, j, p] for j in 1:numdest) == supply[p, i]
)
# Demand constraint
@constraint(
multi,
demand_con[j in 1:numdest, p in 1:numprod],
sum(trans[i, j, p] for i in 1:numorig) == demand[p, j]
)
# Total shipment constraint
@constraint(
multi,
total_con[i in 1:numorig, j in 1:numdest],
sum(trans[i, j, p] for p in 1:numprod) - limit[i, j] <= 0
)
optimize!(multi)
Test.@test termination_status(multi) == MOI.OPTIMAL
Test.@test primal_status(multi) == MOI.FEASIBLE_POINT
Test.@test objective_value(multi) == 225_700.0
if verbose
println("RESULTS:")
for i in 1:length(orig)
for j in 1:length(dest)
for p in 1:length(prod)
print(" $(prod[p])$(orig[i]) $(dest[j]) =$(value(trans[i, j, p]))\t")
end
println()
end
end
end
return
end

example_multi()
RESULTS:
bands GARY FRA = 25.0	 coils GARY FRA = 500.0	 plate GARY FRA = 100.0
bands GARY DET = 125.0	 coils GARY DET = 0.0	 plate GARY DET = 50.0
bands GARY LAN = 0.0	 coils GARY LAN = 0.0	 plate GARY LAN = 0.0
bands GARY WIN = 0.0	 coils GARY WIN = 0.0	 plate GARY WIN = 50.0
bands GARY STL = 250.0	 coils GARY STL = 300.0	 plate GARY STL = 0.0
bands GARY FRE = 0.0	 coils GARY FRE = 0.0	 plate GARY FRE = 0.0
bands GARY LAF = 0.0	 coils GARY LAF = 0.0	 plate GARY LAF = 0.0
bands CLEV FRA = 275.0	 coils CLEV FRA = 0.0	 plate CLEV FRA = 0.0
bands CLEV DET = 100.0	 coils CLEV DET = 200.0	 plate CLEV DET = 50.0
bands CLEV LAN = 100.0	 coils CLEV LAN = 0.0	 plate CLEV LAN = 0.0
bands CLEV WIN = 0.0	 coils CLEV WIN = 75.0	 plate CLEV WIN = 0.0
bands CLEV STL = 0.0	 coils CLEV STL = 625.0	 plate CLEV STL = 0.0
bands CLEV FRE = 225.0	 coils CLEV FRE = 325.0	 plate CLEV FRE = 0.0
bands CLEV LAF = 0.0	 coils CLEV LAF = 375.0	 plate CLEV LAF = 250.0
bands PITT FRA = 0.0	 coils PITT FRA = 0.0	 plate PITT FRA = 0.0
bands PITT DET = 75.0	 coils PITT DET = 550.0	 plate PITT DET = 0.0
bands PITT LAN = 0.0	 coils PITT LAN = 400.0	 plate PITT LAN = 0.0
bands PITT WIN = 75.0	 coils PITT WIN = 175.0	 plate PITT WIN = 0.0
bands PITT STL = 400.0	 coils PITT STL = 25.0	 plate PITT STL = 200.0
bands PITT FRE = 0.0	 coils PITT FRE = 525.0	 plate PITT FRE = 100.0
bands PITT LAF = 250.0	 coils PITT LAF = 125.0	 plate PITT LAF = 0.0