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» Removing the Genetics from the Standard Genetic Algorithm
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GECCO
2005
Springer
108views Optimization» more  GECCO 2005»
14 years 2 months ago
Evolving recurrent models using linear GP
Turing complete Genetic Programming (GP) models introduce the concept of internal state, and therefore have the capacity for identifying interesting temporal properties. Surprisin...
Xiao Luo, Malcolm I. Heywood, A. Nur Zincir-Heywoo...
GECCO
1999
Springer
115views Optimization» more  GECCO 1999»
14 years 27 days ago
A Diversity Study in Genetic Algorithms for Job Shop Scheduling Problems
This paper deals with the study of population diversity in Genetic Algorithms for Job Shop Scheduling Problems. A definition of population diversity at the phenotype level and a ...
Carlos A. Brizuela, Nobuo Sannomiya
EVOW
2009
Springer
14 years 3 months ago
Prediction of Interday Stock Prices Using Developmental and Linear Genetic Programming
A developmental co-evolutionary genetic programming approach (PAM DGP) is compared to a standard linear genetic programming (LGP) implementation for trading of stocks across market...
Garnett Carl Wilson, Wolfgang Banzhaf
EUROGP
2003
Springer
119views Optimization» more  EUROGP 2003»
14 years 1 months ago
Maximum Homologous Crossover for Linear Genetic Programming
We introduce a new recombination operator, the Maximum Homologous Crossover for Linear Genetic Programming. In contrast to standard crossover, it attempts to preserve similar struc...
Michael Defoin-Platel, Manuel Clergue, Philippe Co...
CEC
2009
IEEE
14 years 1 months ago
Distributed genetic algorithm using automated adaptive migration
—We present a new distributed genetic algorithm that can be used to extract useful information from distributed, large data over the network. The main idea of the proposed algori...
Hyunjung Lee, Byonghwa Oh, Jihoon Yang, Seonho Kim