99 search results - page 11 / 20 » Evolving Crossover Operators for Function Optimization |
GECCO
2006
Springer
13 years 11 months ago
2006
Springer
The importance of mutation varies across evolutionary computation domains including: genetic programming, evolution strategies, and genetic algorithms. In the genetic programming ...
GECCO
2004
Springer
14 years 26 days ago
2004
Springer
Abstract. This work introduces a new evolutionary algorithm that adapts the operator probabilities (rates) while evolves the solution of the problem. Each individual encodes its ge...
GECCO
2006
Springer
13 years 11 months ago
2006
Springer
This research examines the behavior of inoperative code (introns) in the evolution of genetically robust solutions. Genetically robust solutions are solutions that are less likely...
CEC
2010
IEEE
13 years 5 months ago
2010
IEEE
In this work we examined the performance of two evolutionary algorithms, a genetic algorithm (GA) and particle swarm optimization (PSO), in the estimation of the parameters of a mo...
GECCO
2005
Springer
14 years 1 months ago
2005
Springer
The paper presents an extension of Vose’s Markov chain model for genetic algorithm (GA). The model contains not only standard genetic operators such as mutation and crossover bu...