Performing Experiments Using the
Sequential Parameter Optimization Toolbox SPOT

Thomas Bartz-Beielstein

Department of Computer Science,

Cologne University of Applied Sciences,

Abstract:

The sequential parameter optimization (SPOT) package for R (R Development Core Team, 2008) is a toolbox for tuning and understanding simulation and optimization algorithms. Model-based investigations are common approaches in simulation and optimization. Sequential parameter optimization has been developed, because there is a strong need for sound statistical analysis of simulation and optimization algorithms. SPOT includes methods for tuning based on classical regression and analysis of variance techniques; tree-based models such as CART and random forest; Gaussian process models (Kriging), and combinations of different meta-modeling approaches. This article exemplifies how experiments can be performed using the SPOT framework.





bartz 2010-07-08