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GECCO
2008
Springer
116views Optimization» more  GECCO 2008»
13 years 5 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»
13 years 11 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 8 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 5 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 4 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