Numerical Optimisers Class Structure and Usage

When optimising, it is necessary to set up an appropriate cost function which provides the interface between the optimiser and the problem domain. It also specifies the ranges for the various parameters and can be used to achieve some degree of constrained optimisation by hiding some process parameters from the optimiser in addition to restricting the parameter ranges (not always applicable).

Once this information has been provided, it is simply a matter of calling a member function MinimalX or MaximalX to find the input parameter which either minimises or maximises the cost function.

Here is an example of how they can be used:

• Finding the closest point on some curve or surface (described by a NumFuncC or NumModelC) to some reference point.