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» The Crowding Approach to Niching in Genetic Algorithms
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GECCO
2010
Springer
207views Optimization» more  GECCO 2010»
14 years 2 months ago
Generalized crowding for genetic algorithms
Crowding is a technique used in genetic algorithms to preserve diversity in the population and to prevent premature convergence to local optima. It consists of pairing each offsp...
Severino F. Galán, Ole J. Mengshoel
GECCO
2010
Springer
140views Optimization» more  GECCO 2010»
13 years 10 months ago
Shared memory genetic algorithms in a multi-agent context
In this paper we present a concurrent implementation of genetic algorithms designed for shared memory architectures intended to take advantage of multi-core processor platforms. O...
Dana Vrajitoru
GECCO
2006
Springer
145views Optimization» more  GECCO 2006»
14 years 1 months ago
Immune anomaly detection enhanced with evolutionary paradigms
The paper presents an approach based on principles of immune systems to the anomaly detection problem. Flexibility and efficiency of the anomaly detection system are achieved by b...
Marek Ostaszewski, Franciszek Seredynski, Pascal B...
SYNASC
2005
IEEE
170views Algorithms» more  SYNASC 2005»
14 years 3 months ago
Density Based Clustering with Crowding Differential Evolution
The aim of this work is to analyze the applicability of crowding differential evolution to unsupervised clustering. The basic idea of this approach, interpreting the clustering pr...
Daniela Zaharie
EC
2002
228views ECommerce» more  EC 2002»
13 years 9 months ago
Improved Sampling of the Pareto-Front in Multiobjective Genetic Optimizations by Steady-State Evolution: A Pareto Converging Gen
Previous work on multiobjective genetic algorithms has been focused on preventing genetic drift and the issue of convergence has been given little attention. In this paper, we pre...
Rajeev Kumar, Peter Rockett