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» The Spatially-Dispersed Genetic Algorithm
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GECCO
2007
Springer
124views Optimization» more  GECCO 2007»
15 years 8 months ago
Fitness-proportional negative slope coefficient as a hardness measure for genetic algorithms
The Negative Slope Coefficient (nsc) is an empirical measure of problem hardness based on the analysis of offspring-fitness vs. parent-fitness scatterplots. The nsc has been teste...
Riccardo Poli, Leonardo Vanneschi
GECCO
2006
Springer
190views Optimization» more  GECCO 2006»
15 years 8 months ago
Design synthesis of microelectromechanical systems using genetic algorithms with component-based genotype representation
An automated design synthesis system based on a multi-objective genetic algorithm (MOGA) has been developed for the optimization of surface-micromachined MEMS devices. A hierarchi...
Ying Zhang, Raffi R. Kamalian, Alice M. Agogino, C...
CSC
2006
15 years 5 months ago
A New Migration Model For Distributed Genetic Algorithms
Genetic algorithms are heuristic search algorithm used in science, engineering and many other areas. They are powerful but slow because of their evolutionary nature that mimics th...
Taisir Eldos
CEC
2010
IEEE
15 years 5 months ago
Automatic construction of image transformation algorithms using feature based genetic image network
Image processing and recognition technologies are becoming increasingly important. Automatic construction methods for image transformation algorithms proposed to date approximate a...
Yuta Nakano, Shinichi Shirakawa, Noriko Yata, Tomo...
GECCO
2008
Springer
103views Optimization» more  GECCO 2008»
15 years 5 months ago
Empirical investigations on parallel competent genetic algorithms
This paper empirically investigates parallel competent genetic algorithms (cGAs) [4]. cGAs, such as BOA [21], LINCGA [15], D5 -GA [28], can solve GA-difficult problems by automati...
Miwako Tsuji, Masaharu Munetomo, Kiyoshi Akama