Sciweavers

SOCO
2010
Springer
12 years 11 months ago
Designing multilayer perceptrons using a Guided Saw-tooth Evolutionary Programming Algorithm
In this paper, a diversity generating mechanism is proposed for an Evolutionary Programming (EP) algorithm that determines the basic structure of Multilayer Perceptron classifiers ...
Pedro Antonio Gutiérrez, César Herv&...
GPEM
2010
89views more  GPEM 2010»
13 years 2 months ago
Variable population size and evolution acceleration: a case study with a parallel evolutionary algorithm
Abstract With current developments of parallel and distributed computing, evolutionary algorithms have benefited considerably from parallelization techniques. Besides improved com...
Ting Hu, Simon Harding, Wolfgang Banzhaf
SAC
2008
ACM
13 years 3 months ago
Dynamic populations in genetic algorithms
Biological populations are dynamic in both space and time, that is, the population size of a species fluctuates across their habitats over time. There are rarely any static or fix...
Zhanshan (Sam) Ma, Axel W. Krings
FOGA
1998
13 years 5 months ago
Understanding Interactions among Genetic Algorithm Parameters
Genetic algorithms (GAs) are multi-dimensional and stochastic search methods, involving complex interactions among their parameters. For last two decades, researchers have been tr...
Kalyanmoy Deb, Samir Agrawal
FLAIRS
2003
13 years 5 months ago
Sample Complexity of Real-Coded Evolutionary Algorithms
Researchers studying Evolutionary Algorithms and their applications have always been confronted with the sample complexity problem. The relationship between population size and gl...
Jian Zhang 0007, Xiaohui Yuan, Bill P. Buckles
FLAIRS
2004
13 years 5 months ago
Multimodal Function Optimization Using Local Ruggedness Information
In multimodal function optimization, niching techniques create diversification within the population, thus encouraging heterogeneous convergence. The key to the effective diversif...
Jian Zhang 0007, Xiaohui Yuan, Bill P. Buckles
GECCO
2006
Springer
139views Optimization» more  GECCO 2006»
13 years 8 months ago
Genetic programming: optimal population sizes for varying complexity problems
The population size in evolutionary computation is a significant parameter affecting computational effort and the ability to successfully evolve solutions. We find that population...
Alan Piszcz, Terence Soule
GECCO
2006
Springer
129views Optimization» more  GECCO 2006»
13 years 8 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
GECCO
2003
Springer
118views Optimization» more  GECCO 2003»
13 years 9 months ago
Population Sizing Based on Landscape Feature
Abstract. Population size for EvolutionaryAlgorithms is usually an empirical parameter. We study the population size from aspects of fitness landscapes’ ruggedness and Probably ...
Jian Zhang, Xiaohui Yuan, Bill P. Buckles
GECCO
2003
Springer
101views Optimization» more  GECCO 2003»
13 years 9 months ago
Population Implosion in Genetic Programming
With the exception of a small body of adaptive-parameter literature, evolutionary computation has traditionally favored keeping the population size constant through the course of t...
Sean Luke, Gabriel Catalin Balan, Liviu Panait