Scientific Computing

This module demonstrates the sequential quadratic programming method for constrained optimization. From a given starting point, a sequence of quadratic programming problems is solved, each of which is derived by applying Newton's method to find a critical point of the Lagrangian function.

The user begins by choosing either a preset example or typing in a
desired objective function *f*(*x*,
*y*)*g*(*x*,
*y*)*x*, *y*)*λ*. The process can be repeated until it converges to the
approximate constrained solution. Values for successive iterates are
recorded in the table below.

**Reference:** Michael T. Heath, *Scientific Computing,
An Introductory Survey*, 2nd edition, McGraw-Hill, New York,
2002. See Sections 6.2.3 and 6.7.1, especially Examples 6.2, 6.6, and
6.7.

**Developers:** Jeffrey Naisbitt and Michael Heath