Lagrange Multipliers
The method of Lagrange multipliers solves the constrained optimization problem by transforming it into a non-constrained optimization problem of the form:
Then finding the gradient and Hessian as was done above will determine any optimum values of .
Suppose we now want to find optimum values for subject to from [2].
Then the Lagrangian method will result in a non-constrained function.
The gradient for this new function is
Finding the stationary points of the above equations can be obtained from their matrix from.
This results in .
Next we can use the Hessian as before to determine the type of this stationary point.
Since then the solution minimizes subject to with .
Resources
- Lagrange Multipliers, WikiBooks: Calculus Optimization Methods
Videos
- LaGrange Multipliers - Finding Maximum or Minimum Values Video by patrickJMT
- Lagrange Multipliers Practice Problems Video by ames Hamblin 2017
- Lagrange multipliers | MIT 18.02SC Multivariable Calculus, Fall 2010 Video by MIT OpenCourseWare
- Lagrange Multipliers - Two Constraints -patrickJMT 2009 Video by patrickJMT 2009
- Lagrange multipliers (3 variables) | MIT 18.02SC Multivariable Calculus, Fall 2010 Video by MIT OpenCourseWare