[SciPy-user] Using optimize.fmin_cobyla

[Arthur Valadares]

Hi, I have the following problem I'm trying to solve:

I have a calculation where, given some parameters, I calculate a vector 'A'
of values and based on this vector, I calculate a final vector 'B' which is
the return of my calculation.
What I want to do is maximize one specific value on 'A' while keeping a
constraint (let C be a constant, the constraint is: C - A[x] = B[x]).

I'm trying to use fmin_cobyla, but I'm a little lost on how to use it to
solve this problem.. Does anyone have any example on using cobyla  or
especifically what I should do? I have tried using it for quite a while, but
I'm just not understanding it right.

On Excel you can just put on Solver to set target A[x], by changing A[x]
with constraint C - A[x] = B[x].

Any tips?

This is my first post, so I wanted to thank the scipy community for all the
great work.

-- 
Arthur Valadares
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