Over the past two decades, the feedforward neural network (FNN) optimization has been a
key interest among the researchers and practitioners of multiple disciplines. The FNN …

Three main streams of evolutionary algorithms (EAs), probabilistic optimization algorithms
based on the model of natural evolution, are compared in this article: evolution strategies …

This article gives a comprehensive introduction into one of the main branches of
evolutionary computation–the evolution strategies (ES) the history of which dates back to the …

From the Publisher: With the publication of this book, Hans-Paul Schwefel has responded to
rapidly growing interest in Evolutionary Computation, a field that originated, in part, with his …

The field of evolutionary computation is expanding dramatically, fueled by the vast
investment that reflects the value of applying its techniques. Culling material from the …

Mutation is an important operator in genetic algorithms (GAs), as it ensures maintenance of
diversity in evolving populations of GAs. Real-parameter GAs (RGAs) handle real-valued …

Evolution strategies form a class of evolutionary optimization procedures the behavior of
which is comparatively well understood theoretically, at least for simple cases. An approach …

Self-adaptation is an essential feature of natural evolution. However, in the context of
function optimization, self-adaptation features of evolutionary search algorithms have been …

In this paper we introduce our asynchronous parallel genetic algorithm ASPARAGOS. The
two major extensions compared to genetic algorithms are the following. First, individuals live …

The vehicle routing problem with time windows (VRPTW) is an extension of the well-known
vehicle routing problem with a central depot. The objective is to design an optimal set of …