Hello everyone.
I am trying to use the CPLEXCP.jl. However, I am having some issues when using this library. Follows the code I am executing. This is the link of the github project.
using CPLEXCP
using MathOptInterface
using ConstraintProgrammingExtensions
const MOI = MathOptInterface
const CP = ConstraintProgrammingExtensions
# create model
model = CPLEXCP.Optimizer()
# create variables
a = first(MOI.add_constrained_variable(model, MOI.Integer()))
b = first(MOI.add_constrained_variable(model, MOI.Integer()))
c = first(MOI.add_constrained_variable(model, MOI.Integer()))
# create objective function
coeff = [5, 4, 7]
var = [a, b, c]
objFunc = MOI.ScalarAffineFunction(MOI.ScalarAffineTerm.(map(c -> c, coeff), map(v -> v, var)), 0)
model.objective_function = objFunc
model.objective_sense = MOI.MAX_SENSE
# run model
MOI.optimize!(model)
# get values
@show MOI.get(model, MOI.VariablePrimal(), a)
@show MOI.get(model, MOI.VariablePrimal(), b)
@show MOI.get(model, MOI.VariablePrimal(), c)
After running the above algorithm, I obtain the following output. First follow the steps at the README.md file, to setup the project properly.
┌ Warning: JavaCall needs the environment variable `JULIA_COPY_STACKS` to be `1` or `yes`.
│ Calling the JVM may result in undefined behavior.
└ @ JavaCall ~/.julia/packages/JavaCall/MlduK/src/JavaCall.jl:53
! --------------------------------------------------- CP Optimizer 20.1.0.0 --
! Satisfiability problem - 0 variables, 0 constraints
! Initial process time : 0,00s (0,00s extraction + 0,00s propagation)
! . Log search space : 0,0 (before), 0,0 (after)
! . Memory usage : 266,6 kB (before), 266,6 kB (after)
! Using parallel search with 20 workers.
! ----------------------------------------------------------------------------
! Branches Non-fixed W Branch decision
* 0 0,00s -
! ----------------------------------------------------------------------------
! Search completed, 1 solution found.
! ----------------------------------------------------------------------------
! Number of branches : 0
! Number of fails : 0
! Total memory usage : 533,0 kB (493,2 kB CP Optimizer + 39,7 kB Concert)
! Time spent in solve : 0,00s (0,00s engine + 0,00s extraction)
! Search speed (br. / s) : 0
! ----------------------------------------------------------------------------
MOI.get(model, MOI.VariablePrimal(), a) = 0.0
MOI.get(model, MOI.VariablePrimal(), b) = 0.0
MOI.get(model, MOI.VariablePrimal(), c) = 0.0
What bothers me, are the 0s as values for the variables a, b, and c. Since a maximization function was defined:
coeff = [5, 4, 7]
var = [a, b, c]
objFunc = MOI.ScalarAffineFunction(MOI.ScalarAffineTerm.(map(c -> c, coeff), map(v -> v, var)), 0)
model.objective_function = objFunc
model.objective_sense = MOI.MAX_SENSE
A was expecting a, b, and c to have value Inf, once the coefficients are all positive. But it seems that the objective function has no effect at all. I would like to know if someone faced similar issue before.
Thank you, case there is any misunderstanding, let me know. Regards.