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» New topologies for genetic search space
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CEC
2003
IEEE
15 years 2 months ago
Homology gives size control in genetic programming
Abstract- The Maximum Homologous Crossover attempts to preserve similar structures from parents by aligning them according to their homology. In this paper, it is successfully test...
Michael Defoin-Platel, Manuel Clergue, Philippe Co...
GECCO
2007
Springer
177views Optimization» more  GECCO 2007»
15 years 3 months ago
Evolving problem heuristics with on-line ACGP
Genetic Programming uses trees to represent chromosomes. The user defines the representation space by defining the set of functions and terminals to label the nodes in the trees. ...
Cezary Z. Janikow
114
Voted
ICMLA
2004
14 years 11 months ago
A new discrete binary particle swarm optimization based on learning automata
: The particle swarm is one of the most powerful methods for solving global optimization problems. This method is an adaptive algorithm based on social-psychological metaphor. A po...
Reza Rastegar, Mohammad Reza Meybodi, Kambiz Badie
GECCO
2007
Springer
174views Optimization» more  GECCO 2007»
15 years 3 months ago
Geometric crossovers for real-code representation
Geometric crossover is a representation-independent generalization of the class of traditional mask-based crossover for binary strings. It is based on the distance of the search s...
Yourim Yoon, Yong-Hyuk Kim, Alberto Moraglio, Byun...
GECCO
2003
Springer
137views Optimization» more  GECCO 2003»
15 years 2 months ago
The Spatially-Dispersed Genetic Algorithm
Abstract. Spatially structured population models improve the performance of genetic algorithms by assisting the selection scheme in maintaining diversity. A significant concern wi...
Grant Dick