Tuning Simulated Annealing Using the Sequential Parameter Optimization Toolbox spot

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 metamodeling approaches. This article exemplifies how an existing optimization algorithms, namely simulated annealing, can be tuned using the spot framework