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GECCO
2007
Springer
130views Optimization» more  GECCO 2007»
14 years 1 months ago
Variable discrimination of crossover versus mutation using parameterized modular structure
Recent work has provided functions that can be used to prove a principled distinction between the capabilities of mutation-based and crossover-based algorithms. However, prior fun...
Rob Mills, Richard A. Watson
GECCO
2004
Springer
106views Optimization» more  GECCO 2004»
14 years 26 days ago
Mutation Rates in the Context of Hybrid Genetic Algorithms
Traditionally, the mutation rates of genetic algorithms are fixed or decrease over the generations. Although it seems to be reasonable for classical genetic algorithms, it may not...
Seung-Hee Bae, Byung Ro Moon
GECCO
2003
Springer
122views Optimization» more  GECCO 2003»
14 years 21 days ago
The Virtual Gene Genetic Algorithm
This paper presents the virtual gene genetic algorithm (vgGA) which is a generalization of traditional genetic algorithms that use binary linear chromosomes. In the vgGA, tradition...
Manuel Valenzuela-Rendón
GECCO
2005
Springer
131views Optimization» more  GECCO 2005»
14 years 1 months ago
EA models and population fixed-points versus mutation rates for functions of unitation
Using a dynamic systems model for the Simple Genetic Algorithm due to Vose[1], we analyze the fixed point behavior of the model without crossover applied to functions of unitation...
J. Neal Richter, John Paxton, Alden H. Wright
CEC
2005
IEEE
13 years 9 months ago
A new approach to dynamics analysis of genetic algorithms without selection
Abstract- Theoretical analysis of the dynamics of evolutionary algorithms is believed to be very important to understand the search behavior of evolutionary algorithms and to devel...
Tatsuya Okabe, Yaochu Jin, Bernhard Sendhoff