Hi Fortran users!
I am trying to solve an optimization problem where I need to choose 150 variables to maximize an objective function subject to some non-linear constraints. In my program there is one main constraint and all the other ones just require that the choice variables be strictly positive.
Is there a way to take care of the strictly positive constraints without having to add 150 constraints to the code (some kind of a common requirement to keep the choice variables greater or equal to, say 10^-6)?
Also, how is it related to the code provided online at NLopt:
"call nlo_create(opt, NLOPT_LD_MMA, 2)
call nlo_get_lower_bounds(ires, opt, lb)
lb(2) = 0.0
call nlo_set_lower_bounds(ires, opt, lb)
call nlo_set_min_objective(ires, opt, myfunc, 0)"
What is lb(2) here? Where is it coming from?
Thanks for any help with this!
Shahar
I am trying to solve an optimization problem where I need to choose 150 variables to maximize an objective function subject to some non-linear constraints. In my program there is one main constraint and all the other ones just require that the choice variables be strictly positive.
Is there a way to take care of the strictly positive constraints without having to add 150 constraints to the code (some kind of a common requirement to keep the choice variables greater or equal to, say 10^-6)?
Also, how is it related to the code provided online at NLopt:
"call nlo_create(opt, NLOPT_LD_MMA, 2)
call nlo_get_lower_bounds(ires, opt, lb)
lb(2) = 0.0
call nlo_set_lower_bounds(ires, opt, lb)
call nlo_set_min_objective(ires, opt, myfunc, 0)"
What is lb(2) here? Where is it coming from?
Thanks for any help with this!
Shahar