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GECCO
1999
Springer
103views Optimization» more  GECCO 1999»
13 years 9 months ago
Homologous Crossover in Genetic Programming
In recent years, the genetic programming crossover operator has been criticized on both theoretical and empirical grounds. This paper introduces a new crossover operator for linea...
Frank D. Francone, Markus Conrads, Wolfgang Banzha...
EUROGP
2003
Springer
119views Optimization» more  EUROGP 2003»
13 years 10 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...
GECCO
2004
Springer
13 years 10 months ago
Crossover, Population Dynamics, and Convergence in the GAuGE System
This paper presents a study of the effectiveness of a recently presented crossover operator for the GAuGE system. This crossover, unlike the traditional crossover employed previou...
Miguel Nicolau, Conor Ryan
CEC
2005
IEEE
13 years 10 months ago
Single parent genetic programming
The most controversial part of genetic programming is its highly disruptive and potentially innovative subtree crossover operator. The clearest problem with the crossover operator...
Wendy Ashlock, Dan Ashlock
EUROGP
2007
Springer
144views Optimization» more  EUROGP 2007»
13 years 11 months ago
Fitness Landscape Analysis and Image Filter Evolution Using Functional-Level CGP
This work analyzes fitness landscapes for the image filter design problem approached using functional-level Cartesian Genetic Programming. Smoothness and ruggedness of fitness l...
Karel Slaný, Lukás Sekanina
CEC
2007
IEEE
13 years 11 months ago
An efficient Genetic Algorithm with uniform crossover for the multi-objective Airport Gate Assignment Problem
—Genetic Algorithms (GAs) have a good potential of solving the Gate Assignment Problem (GAP) at airport terminals, and the design of feasible and efficient evolutionary operators...
Xiao-Bing Hu, Ezequiel A. Di Paolo
GECCO
2009
Springer
13 years 11 months ago
The relationship between evolvability and bloat
Bloat is a common problem with Evolutionary Algorithms (EAs) that use variable length representation. By creating unnecessarily large individuals it results in longer EA runtimes ...
Jeffrey K. Bassett, Mark Coletti, Kenneth A. De Jo...