optimization problem with two variable maxima and minima

can any one give me the solution or help me out in solving this equation mathamatically
Y=2x(1)^2 + 23.08x(2)^2 +4(6+x(1))^2 +24+14(x(1)^2 +x(2)^2)^0.5 +3(x(1)^2 + x(2)^2)
the other equation is 1=x(1)*x(2)

7 Comments

Which variable is the unknown? You only have 1 equation, so only one of the variables can be.
here x(1) and x(2) are unkown you can use other equation as
1=x(1)*x(2)
Differentiate Y with respect to x(1) and x(2), set the derivatives to 0 and solve for x(1) and x(2).
help diff
help solve
if i am differentiating the equation with respect to x(1) then the term under square root x(2) is coming
please guide under this matter
I don't understand what you mean.
first step :
by differentiating y with respect to x(1)
then by putting it equal to zero the term x(2) is coming due to square root term
how to solve this
and if we are putting x(2)=1/x(1) then complex term is coming
can you help me out

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Answers (1)

fun=@(x) [2*x(1)^2+23.08*x(2)^2+4*(6+x(1))^2+24+14*(x(1)^2 +x(2)^2)^0.5+3*(x(1)^2+x(2)^2)-Y;...
prod(x)-1];
x=fsolve(fun,initial_guess)

9 Comments

i am unable to run your code
plesae provide the code for x(1)' and x(2)'
You probably need to remove all the spaces in the expression for fun.
fun=@(x) [2*x(1)^2+23.08*x(2)^2+4*(6+x(1))^2+24+14*(x(1)^2 +x(2)^2)^0.5+3*(x(1)^2+x(2)^2)-Y;...
prod(x)-1];
x=fsolve(fun,initial_guess)
it says
Undefined function or variable 'initial_guess'.
You should have used
initial_guess = [-42, pi];
can you please provide combined code in a single script
as the data provided by you is not working
It's still not clear to me what you are trying to do.
Do you want to solve the two equations
Y=2x(1)^2 + 23.08x(2)^2 +4(6+x(1))^2 +24+14(x(1)^2 +x(2)^2)^0.5 +3(x(1)^2 + x(2)^2)
1=x(1)*x(2)
for x(1) and x(2) (for a given value of Y)
or do you want to determine maximum and minimum of
Y(x(1),x(2)) = 2x(1)^2 + 23.08x(2)^2 +4(6+x(1))^2 +24+14(x(1)^2 +x(2)^2)^0.5 +3(x(1)^2 + x(2)^2)
under the constraint
1 = x(1)*x(2)
or ...
i want to minimize
Y(x(1),x(2)) = 2x(1)^2 + 23.08x(2)^2 +4(6+x(1))^2 +24+14(x(1)^2 +x(2)^2)^0.5 +3(x(1)^2 + x(2)^2)
under the constraint
1 = x(1)*x(2)
fun= @(x)2*x.^2+23.08*(1./x).^2+4*(6+x).^2+24+14*(x.^2+(1./x).^2).^0.5+3*(x.^2+(1./x).^2)
x0 = 1.0;
xmin = fminsearch(fun,x0)
Careful on local minimum
>> xmin = fminsearch(fun,1), fun(xmin) % not global minimum
xmin =
0.9418
ans =
270.4623
>> xmin = fminsearch(fun,-2), fun(xmin)
xmin =
-2.2066
ans =
142.7984
>>

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Asked:

on 6 Sep 2019

Edited:

on 11 Sep 2019

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