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» Dynamic populations in genetic algorithms
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GECCO
2006
Springer
130views Optimization» more  GECCO 2006»
15 years 4 months ago
An efficient multi-objective evolutionary algorithm with steady-state replacement model
The generic Multi-objective Evolutionary Algorithm (MOEA) aims to produce Pareto-front approximations with good convergence and diversity property. To achieve convergence, most mu...
Dipti Srinivasan, Lily Rachmawati
CEC
2007
IEEE
15 years 4 months ago
A versatile quantum-inspired evolutionary algorithm
Abstract-- This study points out some weaknesses of existing Quantum-Inspired Evolutionary Algorithms (QEA) and explains in particular how hitchhiking phenomenons can slow down the...
Michael Defoin-Platel, Stefan Schliebs, Nikola Kas...
WWW
2003
ACM
16 years 1 months ago
An Evolutionary Approach to Web Request Prediction
This paper proposes an evolutionary algorithm that evolves a population of finite state automata to exploit user navigational path behavior to predict, in real-time, future reques...
Dario Bonino, Fulvio Corno, Giovanni Squillero
103
Voted
CEC
2009
IEEE
15 years 7 months ago
A Bacterial Evolutionary Algorithm for automatic data clustering
This paper describes an evolutionary clustering algorithm, which can partition a given dataset automatically into the optimal number of groups through one shot of optimization. The...
Swagatam Das, Archana Chowdhury, Ajith Abraham
97
Voted
GECCO
2003
Springer
15 years 5 months ago
Pruning Neural Networks with Distribution Estimation Algorithms
Abstract. This paper describes the application of four evolutionary algorithms to the pruning of neural networks used in classification problems. Besides of a simple genetic algor...
Erick Cantú-Paz