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IDA
2002
Springer
15 years 6 months ago
Evolutionary model selection in unsupervised learning
Feature subset selection is important not only for the insight gained from determining relevant modeling variables but also for the improved understandability, scalability, and pos...
YongSeog Kim, W. Nick Street, Filippo Menczer
AISB
1994
Springer
15 years 10 months ago
Formal Memetic Algorithms
Abstract. A formal, representation-independent form of a memetic algorithm-a genetic algorithm incorporating local search--is introduced. A generalisedform of N-point crossover is ...
Nicholas J. Radcliffe, Patrick D. Surry
SAC
2008
ACM
15 years 6 months ago
Dynamic populations in genetic algorithms
Biological populations are dynamic in both space and time, that is, the population size of a species fluctuates across their habitats over time. There are rarely any static or fix...
Zhanshan (Sam) Ma, Axel W. Krings
HM
2007
Springer
118views Optimization» more  HM 2007»
16 years 20 days ago
Evolutionary Clustering Search for Flowtime Minimization in Permutation Flow Shop
This paper deals with the Permutation Flow Shop scheduling problem with the objective of minimizing total flow time, and therefore reducing in-process inventory. A new hybrid meta...
Geraldo Ribeiro Filho, Marcelo Seido Nagano, Luiz ...
CEC
2005
IEEE
16 years 4 days ago
Hybrid evolutionary static scheduling for heterogeneous systems
Abstract- The complexity of the static scheduling problem on heterogeneous resources has motivated the development of low complexity heuristics such as list scheduling. However, th...
Cristina Boeres, Eyder Rios, Luiz Satoru Ochi