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» Solving iterated functions using genetic programming
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CPHYSICS
2006
127views more  CPHYSICS 2006»
13 years 7 months ago
GenAnneal: Genetically modified Simulated Annealing
A modification of the standard Simulated Annealing (SA) algorithm is presented for finding the global minimum of a continuous multidimensional, multimodal function. We report resu...
Ioannis G. Tsoulos, Isaac E. Lagaris
GECCO
2008
Springer
141views Optimization» more  GECCO 2008»
13 years 8 months ago
Potential fitness for genetic programming
We introduce potential fitness, a variant of fitness function that operates in the space of schemata and is applicable to tree-based genetic programing. The proposed evaluation ...
Krzysztof Krawiec, PrzemysBaw Polewski
PPSN
2010
Springer
13 years 5 months ago
Using Co-solvability to Model and Exploit Synergetic Effects in Evolution
Abstract. We introduce, analyze, and experimentally examine co-solvability, an ability of a solution to solve a pair of fitness cases (tests). Based on this concept, we devise a co...
Krzysztof Krawiec, Pawel Lichocki
CEC
2010
IEEE
13 years 5 months ago
Active Learning Genetic programming for record deduplication
The great majority of genetic programming (GP) algorithms that deal with the classification problem follow a supervised approach, i.e., they consider that all fitness cases availab...
Junio de Freitas, Gisele L. Pappa, Altigran Soares...
EVOW
2004
Springer
14 years 23 days ago
Solving the Vehicle Routing Problem by Using Cellular Genetic Algorithms
Cellular Genetic Algorithms (cGAs) are a subclass of Genetic Algorithms (GAs) in which the population diversity and exploration are enhanced thanks to the existence of small overla...
Enrique Alba, Bernabé Dorronsoro