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
  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 ()
Accepted Answer
  Image Analyst
      
      
 on 14 Jun 2022
        Compute your f matrix, then try this
% Find the overall minimum value of f.
minValue = min(f(:))    % Hopefully 1 but maybe not exactly.
% Find where that min value occurs
[minRow, minCol] = find(f == minValue)
Note if the min occurs in more than one element minRow and minCol will be vectors giving all the places where minValue occurs.
8 Comments
  Walter Roberson
      
      
 on 14 Jun 2022
				sympref(FloatingPointOutput=false);
syms x y
f(x,y) = 2.62./(2.62+(x-y).^4)
dfx = diff(f, x)
critx = solve(dfx, x)
%so every y is a triple critical point for x
dfy = diff(f, y)
crity = solve(dfy, y)
%so every x is a critical point for some y
d2f = simplify(diff(dfx, x))
[N, D] = numden(d2f)
xsaddle = solve(N == 0, x)
vpa(simplify(subs(f, x, xsaddle)))
vpa(simplify(subs(f, x, xsaddle - 1/1000)))
vpa(simplify(subs(f, x, xsaddle + 1/1000)))
So the first two critical point xsaddle are maximums, the second and third critical points are places where greater or lower would lead to imaginary outputs; the last two are again maxima. 
fsurf(f, [-2 2 -2 2])
Looks to me as if there is a "crease".
More Answers (2)
  Walter Roberson
      
      
 on 14 Jun 2022
        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
2 Comments
  tharun
 on 26 Oct 2023
        Find the minimum value f(x,y) = x3 + y 3 subject to the constraints x + y = 20
3 Comments
  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.
  Sam Chak
      
      
 on 26 Oct 2023
				
      Edited: Sam Chak
      
      
 on 26 Oct 2023
  
			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  .
.
 .
.See Also
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