A taxonomy of global optimization methods based on response surfaces

This paper presents a taxonomy of existing approaches for using response su rfaces for global optimization. Each method is illustrated with a simple nu merical example that brings out its advantages and disadvantages. The centr al theme is that methods that seem quite reasonable often have non-obvious failure modes. Understanding these failure modes is essential for the devel opment of practical algorithms that fulfill the intuitive promise of the re sponse surface approach.