More than a decade after the first extensive overview on parameter control, we revisit the
field and present a survey of the state-of-the-art. We briefly summarize the development of …

The issue of controlling values of various parameters of an evolutionary algorithm is one of
the most important and promising areas of research in evolutionary computation: it has a …

Evolutionary algorithms (EAs) are robust stochastic optimisers that perform well over a wide
range of problems. Their robustness, however, may be affected by several adjustable …

Parameterized evolutionary algorithms (EAs) have been a standard part of the Evolutionary
Computation community from its inception. The widespread use and applicability of EAs is …

The issue of setting the values of various parameters of an evolutionary algorithm is crucial
for good performance. In this paper we discuss how to do this, beginning with the issue of …

Tuning the parameters of an evolutionary algorithm (EA) to a given problem at hand is
essential for good algorithm performance. Optimizing parameter values is, however, a non …

Finding appropriate parameter values for evolutionary algorithms (EA) is one of the
persisting grand challenges of the evolutionary computing (EC) field. In general, EC …

In this paper we present a conceptual framework for parameter tuning, provide a survey of
tuning methods, and discuss related methodological issues. The framework is based on a …

Parameter control is a key issue to enhance performances of Genetic Algorithms (GA).
Although many studies exist on this problem, it is rarely addressed in a general way …

This paper presents a systematic literature review on general parameter control for
evolutionary and swarm-based algorithms. General methods can be applied to any …