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GECCO
2005
Springer
131views Optimization» more  GECCO 2005»
16 years 17 days ago
Genetic algorithms for the sailor assignment problem
This paper examines a real-world application of genetic algorithms – solving the United States Navy’s Sailor Assignment Problem (SAP). The SAP is a complex assignment problem ...
Deon Garrett, Joseph Vannucci, Rodrigo Silva, Dipa...
GECCO
2005
Springer
158views Optimization» more  GECCO 2005»
16 years 17 days ago
Applying both positive and negative selection to supervised learning for anomaly detection
This paper presents a novel approach of applying both positive selection and negative selection to supervised learning for anomaly detection. It first learns the patterns of the n...
Xiaoshu Hang, Honghua Dai
GECCO
2005
Springer
129views Optimization» more  GECCO 2005»
16 years 17 days ago
Evolutionary change in developmental timing
This paper presents a mutation-based evolutionary algorithm that evolves genotypic genes for regulating developmental timing of phenotypic values. The genotype sequentially genera...
Kei Ohnishi, Kaori Yoshida
211
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GECCO
2005
Springer
153views Optimization» more  GECCO 2005»
16 years 17 days ago
Evolving neural network ensembles for control problems
In neuroevolution, a genetic algorithm is used to evolve a neural network to perform a particular task. The standard approach is to evolve a population over a number of generation...
David Pardoe, Michael S. Ryoo, Risto Miikkulainen
GECCO
2005
Springer
131views Optimization» more  GECCO 2005»
16 years 17 days ago
Multipopulation cooperative coevolutionary programming (MCCP) to enhance design innovation
This paper describes the development of an evolutionary algorithm called Multipopulation Cooperative Coevolutionary Programming (MCCP) that extends Genetic Programming (GP) to sea...
Emily M. Zechman, S. Ranji Ranjithan