# [SciPy-User] Inequality constrains definition and violation in slsqp

josef.pktd@gmai... josef.pktd@gmai...
Fri Dec 11 09:11:21 CST 2009

```On Fri, Dec 11, 2009 at 9:39 AM, jagan prabhu <jagan_cbe2003@yahoo.co.in>wrote:

> my objective function is a simple least square function, i have 8
> parameters and  3 inequality constraints, i used fmin_slsqp optimization
> algorithm for my problem, but often my constraints are violated while
> execution. My
> code looks like,
>
> ######### begin ##############################
> #######
> Init = [8.0, 14.0, 16.0, 7.0, 13.0, 50.0, 9.0, 4.0]  #
> [a,b,c,d,e,f,g,h]
> # constraints  (c > d, g > h &  e>=a)
>
> bounds =  [(3.0, 4000.0), (1.0, 6000.0), (2.0, 10000.0), (1.0,
> 4000.0), (4.0, 6000.0), (1.0, 5000.0), (2.0, 10000.0), (1.0, 4000.0)]
> # constraints
> con1 = lambda  x:  x[2]-x[3]
> con2 = lambda  x:  x[6]-x[7]
> con3 = lambda  x:  x[4]-x[0]
> cons = [con1, con2, con3]
> ###
> # gradient function for my problem
>  f = func
>  step = 1.e-3
>  fini = f(*((s,)+args))
>  st = numpy.zeros((len(s),), float)
>  for i in range(len(s)):
>   st[i] = step*s[i]
>   grad[i] = (f(*((s+st,)+args)) - fini)/st[i]
>   st[i] = 0.0
>
> opt = fmin_slsqp(func, Init, ieqcons=cons, bounds= bounds, fprime =
>
> ##############  end of the code #############################
>
> Here the major problem i face is the constraints (c > d, g > h & e>=a) are
> violated frequently during execution, is there any error with my constrain
> definition method or any better way to avoid constrain violations?
>
>

I don't see anything obviously wrong.
With "violated frequently during execution", do you mean during optimization
but not at the final result?

parameters for the functions f(*((s+st,)+args))
are satisfying the constraints, and your stepsizes are pretty big. I don't
know if slsqp itself only evaluates at points that statisfy the constraints.

If that's not the point, then I would need more information to understand
what's going on.

Josef

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