Adaptive random search for antenna optimization

Antenna optimization usually leads to a black-box optimization problem with many local minima. The presented algorithm combines random search with information about the optimization space, obtained after each trial, to find local minima quickly. The probability of splitting parts of the space is proportional to the reciprocal of the error function and is updated after each iteration. The algorithm can be used as a standalone optimization procedure or as a starting stage in hybrid optimization.