baloncesto contrato v2.txt

import Pkg
tempdir = mktempdir()
Pkg.activate(tempdir)
Pkg.add(["JuMP", "CSV","Clp","GLPK","DataFrames","LinearAlgebra"])

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

m = Model(with_optimizer(Clp.Optimizer))
#Variables: xj= jugadores
@variables(m, begin #Definimos las variables
        x1>=0
        x2>=0
	x3>=0
        x4>=0
	x5>=0            
end)  
# sa
@constraint(m, 50000*x1+25200*x2+36000*x3+47000*x4+12000*x5<=50000)        
@constraint(m, x1<=1)           
@constraint(m, x2<=1)
@constraint(m, x3<=1)
@constraint(m, x4<=1)
@constraint(m, x5<=1)

@objective(m, Max, 15*x1+8*x2+15*x3+17*x4+7*x5)
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)
x5=JuMP.value(x5)

println("Valor func objetivo_max=", obj_value)
println("x1 =", x1)
println("x2 =", x2)
println("x3 =", x3)
println("x4 =", x4)
println("x5 =", x5)

resultado

Max 15 x1 + 8 x2 + 15 x3 + 17 x4 + 7 x5
Subject to
 x1 >= 0.0
 x2 >= 0.0
 x3 >= 0.0
 x4 >= 0.0
 x5 >= 0.0
 50000 x1 + 25200 x2 + 36000 x3 + 47000 x4 + 12000 x5 <= 50000.0
 x1 <= 1.0
 x2 <= 1.0
 x3 <= 1.0
 x4 <= 1.0
 x5 <= 1.0
Valor func objetivo_max=22.723404255319146
x1 =0.0
x2 =0.0
x3 =1.0
x4 =0.04255319148936162
x5 =1.0
Coin0506I Presolve 1 (-5) rows, 5 (0) columns and 5 (-5) elements
Clp0006I 0  Obj -0 Primal inf 0.999999 (1) Dual inf 98.958117 (5)
Clp0006I 1  Obj 22.723404
Clp0000I Optimal - objective value 22.723404
Coin0511I After Postsolve, objective 22.723404, infeasibilities - dual 0 (0), primal 0 (0)
Clp0032I Optimal objective 22.72340426 - 1 iterations time 0.002, Presolve 0.00

Esto es, contrataremos a los jugadores correspondientes a las variables 3 y 5: Chriss Burgess (del Ulsan Phoebus) y K.C. Walekowski (del Farho Vigo). Y haciendo esto obtendremos una aportación (utilidad para el equipo)de los jugadores al equipo de 22.