tema2repaso.txt

using JuMP, CSV, Clp, GLPK, DataFrames, LinearAlgebra

m = Model(with_optimizer(Clp.Optimizer))
#Variables: xij= cantidad de muebles del tipo i=1, 2, 3, 4
@variables(m, begin #Definimos las variables
        x1>=0 
        x2>=0             
        x3>=0            
        x4>=0  
         
end)  
# restricciones de Oferta
@constraint(m, 5*x1+1*x2+9*x3+12*x4<=1500)        
@constraint(m, 2*x1+3*x2+4*x3+1*x4<=1000)           
@constraint(m, 3*x1+2*x2+5*x3+10*x4<=800) 
 
# restricciones de Demanda
@constraint(m, x1>=40)
@constraint(m, x2>=130)
@constraint(m, x3>=30)
@constraint(m, x4>=10)

@objective(m, Max, 12*x1+5*x2+15*x3+10*x4)
print(m)
JuMP.optimize!(m)

obj_value=JuMP.objective_value(m)
x1=JuMP.value(x1)
x2=JuMP.value(x2)
x3=JuMP.value(x3)
x4=JuMP.value(x4)

println("Valor func objetivo_max=", obj_value)
println("x1 =", x1)
println("x2    =", x2)
println("x3    =", x3)
println("x4    =", x4)