Stochastic Global Optimization Methods. Part 2. Multi Level Methods

摘要

In Part II of the paper, two stochastic methods for global optimization are described that, with probability 1, find all relevant local minima of the objective function with the smallest possible number of local searches. The computational performance of these methods is examined, both analytically and empirically.