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GECCO
2008
Springer
278views Optimization» more  GECCO 2008»
13 years 10 months ago
Elitism reduces bloat in genetic programming
Elitism is commonly used in generational GP to ensure that the best individuals discovered in a generation are not lost, and are made available for possible further improvements t...
Riccardo Poli, Nicholas Freitag McPhee, Leonardo V...
CCGRID
2009
IEEE
14 years 4 months ago
Reliability-Oriented Genetic Algorithm for Workflow Applications Using Max-Min Strategy
— To optimize makespan and reliability for workflow applications, most existing works use list heuristics rather than genetic algorithms (GAs) which can usually give better solut...
Xiaofeng Wang, Rajkumar Buyya, Jinshu Su
GECCO
2007
Springer
179views Optimization» more  GECCO 2007»
14 years 3 months ago
Evolutionary selection of minimum number of features for classification of gene expression data using genetic algorithms
Selecting the most relevant factors from genetic profiles that can optimally characterize cellular states is of crucial importance in identifying complex disease genes and biomark...
Alper Küçükural, Reyyan Yeniterzi...
GECCO
2006
Springer
186views Optimization» more  GECCO 2006»
14 years 1 months ago
Characterizing large text corpora using a maximum variation sampling genetic algorithm
An enormous amount of information available via the Internet exists. Much of this data is in the form of text-based documents. These documents cover a variety of topics that are v...
Robert M. Patton, Thomas E. Potok
GECCO
2010
Springer
163views Optimization» more  GECCO 2010»
14 years 1 months ago
Factors affecting the use of genetic algorithms in test suite augmentation
Test suite augmentation techniques are used in regression testing to help engineers identify code elements affected by changes, and generate test cases to cover those elements. R...
Zhihong Xu, Myra B. Cohen, Gregg Rothermel