Examination of various techniques for the acceleration of multivariable optimization problems

Magnetic field optimization problems with three or more variables are often characterized by multiple local minima. Among the favored techniques for dealing with this challenge are to represent the objective function in terms of a small subset of data scattered throughout the search region. Radial basis functions, multivariable splines, and a new class of representative functions are compared for accuracy and speed.