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» Initial Population for Genetic Algorithms: A Metric Approach
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CSMR
2003
IEEE
13 years 10 months ago
Moving to Smaller Libraries via Clustering and Genetic Algorithms
There may be several reasons to reduce a software system to its bare bone removing the extra fat introduced during development or evolution. Porting the software system on embedde...
Giuliano Antoniol, Massimiliano Di Penta, Markus N...
GECCO
2005
Springer
110views Optimization» more  GECCO 2005»
13 years 10 months ago
Towards identifying populations that increase the likelihood of success in genetic programming
This paper presents a comprehensive, multivariate account of how initial population material is used over the course of a genetic programming run as while various factors influenc...
Jason M. Daida
SIGADA
2004
Springer
13 years 10 months ago
Comparative analysis of genetic algorithm implementations
Genetic Algorithms provide computational procedures that are modeled on natural genetic system mechanics, whereby a coded solution is “evolved” from a set of potential solutio...
Robert Soricone, Melvin Neville
ITRE
2005
IEEE
13 years 10 months ago
Structure learning of Bayesian networks using a semantic genetic algorithm-based approach
A Bayesian network model is a popular technique for data mining due to its intuitive interpretation. This paper presents a semantic genetic algorithm (SGA) to learn a complete qual...
Sachin Shetty, Min Song
GECCO
2005
Springer
159views Optimization» more  GECCO 2005»
13 years 10 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