Finding the minimum value
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Hi.I have a function f(x,y)=2.62./2.62+(x-y).^4, based on the attached figure, the minimum value for this function is 1. I want to know among all of the value for x and y that makes f(x,y)=1, what is the minimum of x-y? I mean how can I find the minimum value of x-y from all of the values that make f(x,y)=1.
Thanks in advance for any help
openfig('xy.fig');
4 Comments
Torsten
on 14 Jun 2022
x-y is constantly 0 for all values that make f(x,y) = 1.
Maybe you forgot to set brackets in your function definition ?
f(x,y)=2.62./(2.62+(x-y).^4)
instead of
f(x,y)=2.62./2.62+(x-y).^4
?
M
on 14 Jun 2022
Walter Roberson
on 14 Jun 2022
Edited: Walter Roberson
on 14 Jun 2022
For real x and y, (x-y)^4 is always non-negative. 2.62 plus a non-negative value will always be minimum 2.62 or larger. 2.62 divided by a value that is 2.62 or larger, has a maximum value of 1 and cannot be greater than 1. Imagine for example x=1000 y=0 giving 2.62+1e12 as the denominator, the division is going to give near 1e-11
The plot cannot be for the formula you give. The plot could, however, be for the version of the formula missing the ()
M
on 14 Jun 2022
Accepted Answer
More Answers (2)
Walter Roberson
on 14 Jun 2022
0 votes
For the revised formula over real numbers the minimum value is when x and y differ as much as possible, in particular if the difference between them is infinite, which would give you an output of 0.
The maximum value occurs when (x-y)^4 is minimal which occurs when x == y exactly, which gives you 2.62/2.62 == 1
tharun
on 26 Oct 2023
0 votes
Find the minimum value f(x,y) = x3 + y 3 subject to the constraints x + y = 20
3 Comments
tharun
on 26 Oct 2023
answer needed
Walter Roberson
on 26 Oct 2023
When you have an equality constraint relating x and y, solve the constraint for one of the variables, getting a formula for it in terms of the other variable. Then substitute that formula into the main function. You now have a function of a single variable to be optimized. Proceed by way of calculus.
Minimize a bivariate function 

subject to constrained
,
can be transformed into an unconstrained optimization problem by taking the substitution method:
This yields
,
,and the minimum of the quadratic function can be found at
From the equality constraint, we can find
.
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