In the case of an optimization function with three variables and a single constraint function, it is possible to use the method of Lagrange multipliers to solve an optimization problem as well. An example of an optimization function with three variables could be the
Cobb-Douglas function in the previous example:
where
represents the cost of labor,
represents capital input, and
represents the cost of advertising. The method is the same as for the method with a function of two variables; the equations to be solved are
Lagrange multipliers with a three-variable optimization function
Maximize the function
subject to the constraint
The optimization function is
To determine the constraint function, we subtract
from each side of the constraint:
which gives the constraint function as
Next, we calculate
and
This leads to the equations
which can be rewritten in the following form:
Since each of the first three equations has
on the right-hand side, we know that
and all three variables are equal to each other. Substituting
and
into the last equation yields
so
and
and
which corresponds to a critical point on the constraint curve.
Then, we evaluate
f at the point
Therefore, an extremum of the function is
To verify it is a minimum, choose other points that satisfy the constraint and calculate
at that point. For example,
Both of these values are greater than
leading us to believe the extremum is a minimum.
The method of Lagrange multipliers can be applied to problems with more than one constraint. In this case the optimization function,
is a function of three variables:
and it is subject to two constraints:
There are two Lagrange multipliers,
and
and the system of equations becomes
Lagrange multipliers with two constraints
Find the maximum and minimum values of the function
subject to the constraints
and
Let’s follow the problem-solving strategy:
The optimization function is
To determine the constraint functions, we first subtract
from both sides of the first constraint, which gives
so
The second constraint function is
We then calculate the gradients of
The equation
becomes
which can be rewritten as
Next, we set the coefficients of
equal to each other:
The two equations that arise from the constraints are
and
Combining these equations with the previous three equations gives
The first three equations contain the variable
Solving the third equation for
and replacing into the first and second equations reduces the number of equations to four:
Next, we solve the first and second equation for
The first equation gives
the second equation gives
We set the right-hand side of each equation equal to each other and cross-multiply:
Therefore, either
or
If
then the first constraint becomes
The only real solution to this equation is
and
which gives the ordered triple
This point does not satisfy the second constraint, so it is not a solution.
Next, we consider
which reduces the number of equations to three:
We substitute the first equation into the second and third equations:
Then, we solve the second equation for
which gives
We then substitute this into the first equation,
and use the quadratic formula to solve for
Recall
so this solves for
as well. Then,
so
Therefore, there are two ordered triplet solutions:
We substitute
into
which gives
Then, we substitute
into
which gives
is the maximum value and
is the minimum value of
subject to the given constraints.