# The transportation problem

Allocation of passenger cars to trains to minimize cars required or car-miles run. Based on:

Fourer, D.M. Gay and Brian W. Kernighan, A Modeling Language for Mathematical Programming, https://ampl.com/REFS/amplmod.ps.gz Appendix D.

Originally contributed by Louis Luangkesorn, January 30, 2015.

using JuMP
import GLPK
import Test

function example_transp()
ORIG = ["GARY", "CLEV", "PITT"]
DEST = ["FRA", "DET", "LAN", "WIN", "STL", "FRE", "LAF"]
supply = [1_400, 2_600, 2_900]
demand = [900, 1_200, 600, 400, 1_700, 1_100, 1_000]
Test.@test sum(supply) == sum(demand)
cost = [
39   14   11   14   16   82    8;
27    9   12    9   26   95   17;
24   14   17   13   28   99   20
]
model = Model(GLPK.Optimizer)
@variable(model, trans[1:length(ORIG), 1:length(DEST)] >= 0)
@objective(
model,
Min,
sum(
cost[i, j] * trans[i, j]
for i in 1:length(ORIG), j in 1:length(DEST)
)
)
@constraints(model, begin
[i in 1:length(ORIG)], sum(trans[i, :]) == supply[i]
[j in 1:length(DEST)], sum(trans[:, j]) == demand[j]
end)
optimize!(model)
Test.@test termination_status(model) == MOI.OPTIMAL
Test.@test primal_status(model) == MOI.FEASIBLE_POINT
Test.@test objective_value(model) == 196200.0
println("The optimal solution is:")
println(value.(trans))
return
end

example_transp()
The optimal solution is:
[0.0 0.0 0.0 0.0 300.0 1100.0 0.0; 0.0 1200.0 600.0 400.0 0.0 0.0 400.0; 900.0 0.0 0.0 0.0 1400.0 0.0 600.0]