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» Adapting binary fitness functions in Genetic Algorithms
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SEAL
1998
Springer
15 years 1 months ago
Information Operator Scheduling by Genetic Algorithms
Abstract. In this paper, we discuss an approach to an operator scheduling problem in a large organization over time with the aim of maintaining service quality and reducing total l...
Takeshi Yamada, Kazuyuki Yoshimura, Ryohei Nakano
GECCO
2008
Springer
133views Optimization» more  GECCO 2008»
14 years 10 months ago
Using feature-based fitness evaluation in symbolic regression with added noise
Symbolic regression is a popular genetic programming (GP) application. Typically, the fitness function for this task is based on a sum-of-errors, involving the values of the depe...
Janine H. Imada, Brian J. Ross
ICIP
2010
IEEE
14 years 7 months ago
Sparse shapes prototype modeling using genetic algorithms
The process of finding representative shape patterns from sparse datasets is a challenging task: especially for non-rigid objects, shape deformations through time can produce very...
Stefano Maludrottu, Hany Sallam, Carlo S. Regazzon...
GECCO
2010
Springer
172views Optimization» more  GECCO 2010»
15 years 2 months ago
Designing better fitness functions for automated program repair
Evolutionary methods have been used to repair programs automatically, with promising results. However, the fitness function used to achieve these results was based on a few simpl...
Ethan Fast, Claire Le Goues, Stephanie Forrest, We...
NC
1998
138views Neural Networks» more  NC 1998»
14 years 11 months ago
Parallel Adaptive Genetic Algorithm
In this paper we introduce an efficient implementation of asynchronously parallel genetic algorithm with adaptive genetic operators. The classic genetic algorithm paradigm is exte...
Leo Budin, Marin Golub, Domagoj Jakobovic