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GECCO
2008
Springer
116views Optimization» more  GECCO 2008»
13 years 8 months ago
A novel methodology for diversity preservation in evolutionary algorithms
In this paper we describe an improvement of an entropy-based diversity preservation approach for evolutionary algorithms. This approach exploits the information contained not only...
Giovanni Squillero, Alberto Paolo Tonda
GECCO
2007
Springer
174views Optimization» more  GECCO 2007»
14 years 1 months ago
Heuristic speciation for evolving neural network ensemble
Speciation is an important concept in evolutionary computation. It refers to an enhancements of evolutionary algorithms to generate a set of diverse solutions. The concept is stud...
Shin Ando
GECCO
2006
Springer
130views Optimization» more  GECCO 2006»
13 years 11 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
GECCO
2008
Springer
120views Optimization» more  GECCO 2008»
13 years 8 months ago
A robust evolutionary framework for multi-objective optimization
Evolutionary multi-objective optimization (EMO) methodologies, suggested in the beginning of Nineties, focussed on the task of finding a set of well-converged and well-distribute...
Kalyanmoy Deb
PRL
2006
105views more  PRL 2006»
13 years 7 months ago
Parisian camera placement for vision metrology
This paper presents a novel camera network design methodology based on the Parisian evolutionary computation approach. This methodology proposes to partition the original problem ...
Enrique Dunn, Gustavo Olague, Evelyne Lutton