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» The Spatially-Dispersed Genetic Algorithm
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GECCO
2000
Springer
101views Optimization» more  GECCO 2000»
14 years 1 months ago
Using Genetic Algorithms with Asexual Transposition
Traditional Genetic Algorithms (GA) use crossover and mutation as the main genetic operators to achieve population diversity. Previous work using a biologically inspired genetic o...
Anabela Simões, Ernesto Costa
AEI
1999
110views more  AEI 1999»
13 years 9 months ago
Self-tuning fuzzy controller design using genetic optimisation and neural network modelling
This article describes a new adaptive fuzzy logic control scheme. The proposed scheme is based on the structure of the self-tuning regulator and employs neural network and genetic...
Duc Truong Pham, Dervis Karaboga
CEC
2008
IEEE
14 years 4 months ago
Hyper-selection in dynamic environments
— In recent years, several approaches have been developed for genetic algorithms to enhance their performance in dynamic environments. Among these approaches, one kind of methods...
Shengxiang Yang, Renato Tinós
GECCO
2004
Springer
145views Optimization» more  GECCO 2004»
14 years 3 months ago
An Estimation of Distribution Algorithm Based on Maximum Entropy
Estimation of distribution algorithms (EDA) are similar to genetic algorithms except that they replace crossover and mutation with sampling from an estimated probability distributi...
Alden H. Wright, Riccardo Poli, Christopher R. Ste...
DEXAW
2008
IEEE
119views Database» more  DEXAW 2008»
14 years 4 months ago
Evolutionary Approaches to Linear Ordering Problem
Linear Ordering Problem (LOP) is a well know optimization problem attractive for its complexity (it is a NPhard problem), rich collection of testing data and variety of real world...
Václav Snásel, Pavel Krömer, Ja...