aplicatie 2 lab9

using JuMP
using HiGHS

Scaune = ["A", "B", "C", "D", "E", "F", "G", "H", "I", "J"]
C = length(Scaune)
LiniiProductie = [1, 2, 3, 4, 5]
P = length(LiniiProductie)

Profit = [6, 5, 9, 5, 6, 3, 4, 7, 4, 3]
Capacitate = [47, 19, 36, 13, 46]
ResurseFolosite = [
    6 4 2 3 1 10 2 9 3 5;
    5 6 1 1 7 2 9 1 8 6;
    8 10 7 2 9 6 9 6 5 6;
    8 4 8 10 5 4 1 5 3 5;
    1 4 7 2 4 1 2 3 10 1;
]

IC2 = Model(HiGHS.Optimizer)

@variable(IC2, x[c=1:C]>=0)

@objective(IC2, Max, sum(Profit[c]*x[c] for c=1:C))

@constraint(IC2, [p=1:P],
sum(ResurseFolosite[p, c]*x[c] for c=1:C) <= Capacitate[p])

optimize!(IC2)
println("Status final: $(termination_status(IC2))")

if termination_status(IC2) == MOI.OPTIMAL
    println("Valoarea functiei obiectiv: \$(objective_value(IC2))")
    for c = 1:C
        if value(x[c]) > 0.001
            println("Scaun de tip: ", Scaune[c], " a fost produs in cantitatea: ", value(x[c]))
        end
    end
else
    println("Nici o solutie gasita")
end