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» Generalized crowding for genetic algorithms
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GECCO
2005
Springer
100views Optimization» more  GECCO 2005»
15 years 3 months ago
Evolutionary tree genetic programming
We introduce a clustering-based method of subpopulation management in genetic programming (GP) called Evolutionary Tree Genetic Programming (ETGP). The biological motivation behin...
Ján Antolík, William H. Hsu
GECCO
2010
Springer
129views Optimization» more  GECCO 2010»
15 years 2 months ago
A probabilistic functional crossover operator for genetic programming
The original mechanism by which evolutionary algorithms were to solve problems was to allow for the gradual discovery of sub-solutions to sub-problems, and the automated combinati...
Josh C. Bongard
GECCO
2009
Springer
134views Optimization» more  GECCO 2009»
15 years 2 months ago
Estimating the distribution and propagation of genetic programming building blocks through tree compression
Shin et al [19] and McKay et al [15] previously applied tree compression and semantics-based simplification to study the distribution of building blocks in evolving Genetic Progr...
Robert I. McKay, Xuan Hoai Nguyen, James R. Cheney...
GECCO
2008
Springer
116views Optimization» more  GECCO 2008»
14 years 11 months ago
Stock trading strategies by genetic network programming with flag nodes
Genetic Network Programming (GNP) has been proposed as a graph-based evolutionary algorithm. GNP works well especially in dynamic environments due to its graph structures. In addi...
Shingo Mabu, Yan Chen, Etsushi Ohkawa, Kotaro Hira...
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GECCO
2007
Springer
168views Optimization» more  GECCO 2007»
15 years 4 months ago
Genetic multi-step search in interpolation and extrapolation domain
The deterministic Multi-step Crossover Fusion (dMSXF) is an improved crossover method of MSXF which is a promising method of JSP, and it shows high availability in TSP. Both of th...
Yoshiko Hanada, Tomoyuki Hiroyasu, Mitsunori Miki