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» An Introduction to Evolutionary Programming
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GECCO
2006
Springer
139views Optimization» more  GECCO 2006»
15 years 3 months ago
Genetic programming: optimal population sizes for varying complexity problems
The population size in evolutionary computation is a significant parameter affecting computational effort and the ability to successfully evolve solutions. We find that population...
Alan Piszcz, Terence Soule
AOSD
2009
ACM
15 years 6 months ago
Automated test data generation for aspect-oriented programs
Despite the upsurge of interest in the Aspect-Oriented Programming (AOP) paradigm, there remain few results on test data generation techniques for AOP. Furthermore, there is no wo...
Mark Harman, Fayezin Islam, Tao Xie, Stefan Wapple...
GECCO
2005
Springer
159views Optimization» more  GECCO 2005»
15 years 5 months ago
Resource-limited genetic programming: the dynamic approach
Resource-Limited Genetic Programming is a bloat control technique that imposes a single limit on the total amount of resources available to the entire population, where resources ...
Sara Silva, Ernesto Costa
GECCO
2010
Springer
220views Optimization» more  GECCO 2010»
15 years 3 months ago
Interday foreign exchange trading using linear genetic programming
Foreign exchange (forex) market trading using evolutionary algorithms is an active and controversial area of research. We investigate the use of a linear genetic programming (LGP)...
Garnett Carl Wilson, Wolfgang Banzhaf
GECCO
2008
Springer
116views Optimization» more  GECCO 2008»
15 years 27 days 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...