|
 The
Optimisation package provides many techniques for finding the minimum
or maximum of an objective function subject to constraints. It solves
linear programs, quadratic programs, nonlinear programs, and both linear
and nonlinear least-squares problems, whether constrained or
unconstrained. Variables may be continuous, integer or binary.
A new sparse interior-point method has been implemented
for linear programs. The new algorithm is much more efficient than the
existing, simplex-based active-set method for large, sparse problems and
takes advantage of the sparse matrix package UMFPACK. Maple
automatically determines the most efficient method to use based on the
linear programming problem, or you can specify the method you want to
use.
Here are some examples of the new interior-point method in action:
The following plot shows a comparison between the two methods on a set of standard Netlib benchmark problems:
|
Datasheet
