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FPGA
2006
ACM
224views FPGA» more  FPGA 2006»
13 years 11 months ago
Flexible implementation of genetic algorithms on FPGAs
In this paper, we propose a technique to flexibly implement genetic algorithms for various problems on FPGAs. For the purpose, we propose a basic architecture for GA which consist...
Tatsuhiro Tachibana, Yoshihiro Murata, Naoki Shiba...
GECCO
2004
Springer
126views Optimization» more  GECCO 2004»
14 years 1 months ago
A Gene Based Adaptive Mutation Strategy for Genetic Algorithms
In this study, a new mechanism that adapts the mutation rate for each locus on the chromosomes, based on feedback obtained from the current population is proposed. Through tests us...
Sima Uyar, Sanem Sariel, Gülsen Eryigit
GECCO
2005
Springer
153views Optimization» more  GECCO 2005»
14 years 1 months 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
152views Optimization» more  GECCO 2005»
14 years 1 months ago
A multi-objective genetic algorithm for robust design optimization
Real-world multi-objective engineering design optimization problems often have parameters with uncontrollable variations. The aim of solving such problems is to obtain solutions t...
Mian Li, Shapour Azarm, Vikrant Aute
CDC
2009
IEEE
217views Control Systems» more  CDC 2009»
13 years 9 months ago
Discrete invasive weed optimization algorithm: application to cooperative multiple task assignment of UAVs
This paper presents a novel discrete population based stochastic optimization algorithm inspired from weed colonization. Its performance in a discrete benchmark, timecost trade-off...
Mohsen Ramezani Ghalenoei, Hossein Hajimirsadeghi,...