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 …

Particle Swarm Optimization for Single Objective Continuous Space Problems: A Review Page 1
Particle Swarm Optimization for Single Objective Continuous Space Problems: A Review …

SHADE is an adaptive DE which incorporates success-history based parameter adaptation
and one of the state-of-the-art DE algorithms. This paper proposes L-SHADE, which further …

This is the second edition of our 2003 book. It is primarily a book for lecturers and graduate
and undergraduate students. To this group the book offers a thorough introduction to …

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 …

An evolutionary recurrent network which automates the design of recurrent neural/fuzzy
networks using a new evolutionary learning algorithm is proposed in this paper. This new …

This paper studies static and dynamic decentralized versions of the search model known as
cellular genetic algorithm (cGA), in which individuals are located in a specific topology and …

Artificial immune systems (AIS) can be defined as computational systems inspired by
theoretical immunology, observed immune functions, principles and mechanisms in order to …

The social foraging behavior of Escherichia coli bacteria has been used to solve
optimization problems. This paper proposes a hybrid approach involving genetic algorithms …

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 …