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GECCO
2006
Springer
156views Optimization» more  GECCO 2006»
13 years 11 months ago
Improving GP classifier generalization using a cluster separation metric
Genetic Programming offers freedom in the definition of the cost function that is unparalleled among supervised learning algorithms. However, this freedom goes largely unexploited...
Ashley George, Malcolm I. Heywood
GECCO
2010
Springer
188views Optimization» more  GECCO 2010»
13 years 10 months ago
Benchmarking real-coded genetic algorithm on noisy black-box optimization testbed
Originally, genetic algorithms were developed based on the binary representation of candidate solutions in which each conjectured solution is a fixed-length string of binary numb...
Thanh-Do Tran, Gang-Gyoo Jin
TR
2008
78views more  TR 2008»
13 years 7 months ago
MOMS-GA: A Multi-Objective Multi-State Genetic Algorithm for System Reliability Optimization Design Problems
A custom genetic algorithm was developed and implemented to solve multiple objective multi-state reliability optimization design problems. Many real-world engineering design proble...
Heidi A. Taboada, Jose F. Espiritu, David W. Coit
ESCIENCE
2007
IEEE
13 years 11 months ago
Grid-Enabling an Efficient Algorithm for Demanding Global Optimization Problems in Genetic Analysis
Abstract. We study the implementation on grid systems of an efficient algorithm for demanding global optimization problems. Specifically, we consider problems arising in the geneti...
Mahen Jayawardena, Sverker Holmgren
GECCO
2004
Springer
14 years 23 days ago
The Royal Road Not Taken: A Re-examination of the Reasons for GA Failure on R1
Previous work investigating the performance of genetic algorithms (GAs) has attempted to develop a set of fitness landscapes, called “Royal Roads” functions, which should be id...
Brian Howard, John Sheppard