Tuning Simulated Annealing Using the Sequential Parameter Optimization Toolbox SPOT
Keywords: spotSannIntro

# Tuning Simulated Annealing 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 an existing optimization algorithms, namely simulated annealing, can be tuned using the SPOT framework

- Introduction
- The SPOT Interface to SANN
- SANN
- SPOT files
  - Experimental Setup
  - Files Used During the Tuning Process
  - SPOT Configuration
    - Setup of the CONF for the SANN
  - The Region of Interest
    - Setup of the ROI for the SANN
  - The Algorithm and Problem Design File
    - Setup of the APD for the SANN
- Running SPOT--Automatic Tuning of SANN
- Summary
- Bibliography
- About this document ...