Constrained optimization of a vector
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Hi!
I am trying to optimize a vector. I want to find 
, where 
(
)=0, and 
.
, where ()=0, and .f_1 and f-2 are two procedural functions, stored in m-files (not straight-forward functions).
How can I do it with a viable (time-effective) algorithm?
Thanks!
采纳的回答
Walter Roberson
2022-5-24
0 个投票
Use fmincon. Make the objective f1^2 and use a nonlinear equality constraint with f2.
4 个评论
mahdi Izadi
2022-5-25
Thanks!
The problem is that f_1 returns a vector;
i.e. 
and matlab returns the error
and matlab returns the error Supplied objective function must return a scalar value. Indeed I am trying to solve n equations simulateneously and the sum of a function of answers should be one.
Could you please kindly let me know how can I fix this?
Thanks so much
Walter Roberson
2022-5-25
norm(f1(a))
mahdi Izadi
2022-5-25
Walter Roberson
2022-5-25
It depends what the calculations do. In particular, are there analytic forms of the jacobian? Possibly a sparse form? fmincon needs to estimate the gradient of every variable against every other variable, and if you have hundreds of variables that can get slow.
更多回答（1 个）
You have two equations so, as long as numel(a)=2 and f1 and f2 are differentiable, you can use fsolve. If numel(a)>2 then you have more unknowns than equations and the problem is ill-posed.
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