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GECCO
2008
Springer
124views Optimization» more  GECCO 2008»
14 years 11 months ago
Introducing MONEDA: scalable multiobjective optimization with a neural estimation of distribution algorithm
In this paper we explore the model–building issue of multiobjective optimization estimation of distribution algorithms. We argue that model–building has some characteristics t...
Luis Martí, Jesús García, Ant...
GECCO
2006
Springer
220views Optimization» more  GECCO 2006»
15 years 1 months ago
Comparing evolutionary algorithms on the problem of network inference
In this paper, we address the problem of finding gene regulatory networks from experimental DNA microarray data. We focus on the evaluation of the performance of different evoluti...
Christian Spieth, Rene Worzischek, Felix Streicher...
GECCO
2007
Springer
209views Optimization» more  GECCO 2007»
15 years 4 months ago
Kernel based automatic clustering using modified particle swarm optimization algorithm
This paper introduces a method for clustering complex and linearly non-separable datasets, without any prior knowledge of the number of naturally occurring clusters. The proposed ...
Ajith Abraham, Swagatam Das, Amit Konar
CEC
2007
IEEE
15 years 4 months ago
On the analysis of average time complexity of estimation of distribution algorithms
— Estimation of Distribution Algorithm (EDA) is a well-known stochastic optimization technique. The average time complexity is a crucial criterion that measures the performance o...
Tianshi Chen, Ke Tang, Guoliang Chen, Xin Yao
GECCO
2006
Springer
129views Optimization» more  GECCO 2006»
15 years 1 months ago
Revisiting evolutionary algorithms with on-the-fly population size adjustment
In an evolutionary algorithm, the population has a very important role as its size has direct implications regarding solution quality, speed, and reliability. Theoretical studies ...
Fernando G. Lobo, Cláudio F. Lima