# Non-Linear optimization

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Lala on 26 Jan 2020
Commented: Lala on 5 Feb 2020
Hello,
Please, how do I sove this non linear optimization problem?um.'. The idea is to declare max(1), max(2), and max(3) as constants, like 4, 6, 3.. for simplicity, I renamed the variables to; x1 = a, x2 = b, x3= c, beta1=p, beta2=q, beta3= r
minmodel = optimproblem
a=optimvar('a','Lowerbound',0);
b=optimvar('b', 'Lowerbound',0);
c=optimvar('b','Lowerbound',0);
p=optimvar('p','Lowerbound'0);
q=optimvar('q','Lowerbound'0);
r=optimvar('r','Lowerbound'0);

Walter Roberson on 27 Jan 2020
If I recall correctly, non-linear optimization cannot yet be handled with Problem Based Optimization. Therefore you will need to switch to Solver Based Optimization:
z = @(xB) (exp(-xB(1)) .* max1 + xB(4).*xB(1)) + (exp(-xB(2)) .* max2 + xB(5).*xB(2)) + (exp(-xB(3)) .* max3 + xB(6).*xB(3));
fminsearch(z, rand(1,6))
However, we can see that can be combined with and into a single parameter that is their sum. Or to phrase this another way: unless you combine them into a single parameter, you will not be able to get a unique solution out of the search because the same total can be achieved by increasing one of the parameters slightly and reducing a different parameter slightly.
Perhaps the equations are not as you represented them? Perhaps you have ? But if so then the x1 parts could be combined...
Lala on 5 Feb 2020
Thank you so much!