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GECCO
2007
Springer
151views Optimization» more  GECCO 2007»
15 years 3 months ago
Solving real-valued optimisation problems using cartesian genetic programming
Classical Evolutionary Programming (CEP) and Fast Evolutionary Programming (FEP) have been applied to realvalued function optimisation. Both of these techniques directly evolve th...
James Alfred Walker, Julian Francis Miller
GECCO
2007
Springer
187views Optimization» more  GECCO 2007»
15 years 3 months ago
Defining implicit objective functions for design problems
In many design tasks it is difficult to explicitly define an objective function. This paper uses machine learning to derive an objective in a feature space based on selected examp...
Sean Hanna
IJIT
2004
14 years 11 months ago
"Intuition" Operator: Providing Genomes with Reason
In this contribution, the use of a new genetic operator is proposed. The main advantage of using this operator is that it is able to assist the evolution procedure to converge fast...
Grigorios N. Beligiannis, Georgios A. Tsirogiannis...
CLUSTER
2008
IEEE
15 years 4 months ago
A comparison of search heuristics for empirical code optimization
—This paper describes the application of various search techniques to the problem of automatic empirical code optimization. The search process is a critical aspect of auto-tuning...
Keith Seymour, Haihang You, Jack Dongarra
IDA
2008
Springer
14 years 9 months ago
A comprehensive analysis of hyper-heuristics
Meta-heuristics such as simulated annealing, genetic algorithms and tabu search have been successfully applied to many difficult optimization problems for which no satisfactory pro...
Ender Özcan, Burak Bilgin, Emin Erkan Korkmaz