Chetan Mandayam Nayakar
Last Activity: 13 Years ago
Lagrange multipliers, also called Lagrangian multipliers (e.g., Arfken 1985, p. 945), can be used to find the of a multivariate function
subject to the constraint
, where
and
are functions with continuous first partial derivatives on the open set containing the curve
, and
at any point on the curve (where
is the gradient).
For an extremum of
to exist on
, the gradient of
must line up with the gradient of
. In the illustration above,
is shown in red,
in blue, and the intersection of
and
is indicated in light blue. The gradient is a horizontal vector (i.e., it has no
-component) that shows the direction that the function increases; for
it is perpendicular to the curve, which is a straight line in this case. If the two gradients are in the same direction, then one is a multiple (
) of the other, so
 |
(1)
|
The two vectors are equal, so all of their components are as well, giving
 |
(2)
|
for all
, ...,
, where the constant
is called the Lagrange multiplier.
The extremum is then found by solving the
equations in
unknowns, which is done without inverting
, which is why Lagrange multipliers can be so useful.
For multiple constraints
,
, ...,