Evolutionary computation has started to receive significant attention during the last decade,
although the origins can be traced back to the late 1950's. This article surveys the history as …

Abstract Knowledge extraction through machine learning techniques has been successfully
applied in a large number of application domains. However, apart from the required …

A comprehensive guide to a powerful new analytical tool by two of its foremost innovators
The past decade has witnessed many exciting advances in the use of genetic algorithms …

All metaheuristic optimization algorithms require some initialization, and the initialization for
such optimizers is usually carried out randomly. However, initialization can have some …

We propose a genetic-based expectation-maximization (GA-EM) algorithm for learning
Gaussian mixture models from multivariate data. This algorithm is capable of selecting the …

Evolution strategies are a class of general optimisation algorithms which are applicable to
functions that are multimodal, non-differentiable, or even discontinuous. Although …

A simple and efficient algorithm based on evolutionary strategies is proposed for the solution
of the economic dispatch (ED) problem with noncontinuous and nonsmooth/nonconvex cost …

Priority-dispatching rules have been studied for many decades, and they form the backbone
of much industrial scheduling practice. Developing new dispatching rules for a given …

This paper presents a genetic‐algorithm driven, cognitive radio decision engine that
determines the optimal radio transmission parameters for single and multicarrier systems …

The aim of this paper is to give a survey on the development and applications of
evolutionary multi-agent systems (EMAS). The paper starts with a general introduction …