Introduction

This article illustrates how an existing algorithm can be tuned using the SPOT framework. The SPOT package can be installed from within R using the

command. Alternatively, SPOT can downloaded from the comprehensive R archive network at http://CRAN.R-project.org/package=SPOT. The latter procedure is recommended for the experienced R user only. SPOT is one possible implementation of the sequential parameter optimization (SPO) framework introduced in Bartz-Beielstein (2006). For a detailed documentation of the functions from the SPOT package, the reader is referred to the package help manuals.

The performance of modern search heuristics such as evolution strategies(ES), differential evolution (DE), or simulated annealing (SANN) relies crucially on their parametrizations--or, statistically speaking, on their factor settings. The term algorithm design summarizes factors that influence the behavior (performance) of an algorithm, whereas problem design refers to factors from the optimization (simulation) problem. Population size in ES is one typical factor which belongs to the algorithm design, the search space dimension belongs to the problem design.