New answers tagged mathematical-optimization
1
vote
Is a four-variable function less than one?
The command
FindInstance[{f >= 1, x >= 0, w >= 1, y > 0, z > 0}, {w, x, y, z}]
returns {} which, if one trusts ...
0
votes
Chi-square minimization error
The problem is caused by "NDSolve". It should localize the dummy variable "t", but fails to do so. Consider:
...
2
votes
Chi-square minimization error
Three comments:
solve for all variables simultaneously instead of solving for $(x,y,z)$ first and $w$ second,
use NonlinearModelFit instead of writing your own ...
4
votes
Accepted
Optimizing an ODE fitting algorithm with interpolated data
Another way to do the fitting.
1 - We will using a custom-made second order interpolation as giving in f[t]. A dummy extra data point was introduced to facilitate ...
3
votes
Optimizing an ODE fitting algorithm with interpolated data
This problem has 4 parameters, and only 6 x 3 = 18 data points. I suspect that this problem is only weakly determined, if you consider the "Rule of 10" which states that you should have 10 ...
2
votes
Accepted
'The objective function is not a scalar' in NMinimize
You define beta in NMinimize as a scalar. Replacing beta by: 1 and evaluating:
...
1
vote
Why hasn't the minimum value of a+b been determined?
As the first condition is actually an equation, we may solve for b:
sol=Solve[9 == 9^(1/a) 3^(4/b), b][[1]]
As we want real numbers, we can delete the imaginary ...
6
votes
Accepted
Why hasn't the minimum value of a+b been determined?
The following works in 13.3.1 on Windows 10.
Minimize[{a + b, Reduce[9 == 9^(1/a) 3^(4/b) && a*b > 0, Reals]}, {a, b}]
$\left\{2 \sqrt{2}+3,\left\{a\to ...
3
votes
Accepted
Modifying `FindMinimum` to work for noisy functions?
I compiled your code and used Bayesian Optimization.
I think,when dealing with noisy function, we should convert it into the deterministic equivalent or treat it as ...
1
vote
How to speed up optimization?
Have you considered using Orthogonalize for this? This finds an orthogonal basis for the powers of x over [0,5] and then projects ...
2
votes
How to speed up optimization?
This is a bit out there, but you can actually do this using the neural network facilities which opens up the possibility to use a GPU:
...
0
votes
Could a minimization problem be easily converted into a NonlinearModelFit?
The standard approach (going back to at least 1935) for your linear model ($a+bx$) with a known covariance matrix is Generalized Least Squares (https://en.wikipedia.org/wiki/...
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