# [SciPy-user] Generating tuples and lists connected with optimize.fmin_l_bfgs_b(func, guess, bounds=bounds, iprint=-1)

Christian Kristukat ckkart at hoc.net
Fri Jul 1 06:32:42 CDT 2005

Nils Wagner wrote:
> Is it possible to solve constrained optimization problems of the form
>
> min f(x)
>
> s.t.
>
> 0 < x_1 < =1
> 0 < x_2 < =1
>
> n(x) = 0
> with scipy. n(x) denotes a nonlinear function  of the design variables
> x^T=[x_1,\dots,x_n]
> So we have both equality and inequality constraints.

Might be stupid, but as we are limited to machine precision, one could take the
machine precision as lower limit:
eps <= x_1 <= 1
That should be equal to 0 < x_1. Correct me if I'm wrong.

Regards, Christian