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.
The paper is structured as follows:
Section 2 presents an example how the experimental setup for an optimization algorithm written in JAVA can
be specified in the SPOT framework.