The Sequential Simplex Approach to Optimisation

John Ogilvie, CECM

Although Maple has for several years contained procedures for
constrained optimization according to linear programming, another
approach involving simplices is applicable to non-linear regression.
Traditionally the latter approach provides no estimates of uncertainty
of parameters, but E. Romero and I have extended a procedure in Maple
to encompass this capability.  I shall demonstrate with animations the
application of this approach to real and simulated data.