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GECCO
2006
Springer
124views Optimization» more  GECCO 2006»
15 years 3 months ago
Rotated test problems for assessing the performance of multi-objective optimization algorithms
This paper presents four rotatable multi-objective test problems that are designed for testing EMO (Evolutionary Multiobjective Optimization) algorithms on their ability in dealin...
Antony W. Iorio, Xiaodong Li
GECCO
2010
Springer
244views Optimization» more  GECCO 2010»
15 years 2 days ago
Implicit fitness and heterogeneous preferences in the genetic algorithm
This paper takes an economic approach to derive an evolutionary learning model based entirely on the endogenous employment of genetic operators in the service of self-interested a...
Justin T. H. Smith
BMCBI
2006
94views more  BMCBI 2006»
14 years 12 months ago
Novel knowledge-based mean force potential at the profile level
Background: The development and testing of functions for the modeling of protein energetics is an important part of current research aimed at understanding protein structure and f...
Qiwen Dong, Xiaolong Wang, Lei Lin
GECCO
2009
Springer
131views Optimization» more  GECCO 2009»
15 years 4 months ago
Application of a simple binary genetic algorithm to a noiseless testbed benchmark
One of the earliest evolutionary computation algorithms, the genetic algorithm, is applied to the noise-free BBOB 2009 testbed. It is adapted to the continuous domain by increasin...
Miguel Nicolau
68
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GECCO
2005
Springer
139views Optimization» more  GECCO 2005»
15 years 5 months ago
Alternative implementations of the Griewangk function
The well-known Griewangk function, used for evaluation of evolutionary algorithms, becomes easier as the number of dimensions grows. This paper suggests three alternative implemen...
Artem Sokolov, L. Darrell Whitley, Monte Lunacek