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» On the Brittleness of Evolutionary Algorithms
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RECOMB
2010
Springer
15 years 4 months ago
A New Genomic Evolutionary Model for Rearrangements, Duplications, and Losses That Applies across Eukaryotes and Prokaryotes
Background: Genomic rearrangements have been studied since the beginnings of modern genetics and models for such rearrangements have been the subject of many papers over the last ...
Yu Lin, Bernard M. E. Moret
EC
2011
240views ECommerce» more  EC 2011»
15 years 1 months ago
HypE: An Algorithm for Fast Hypervolume-Based Many-Objective Optimization
Abstract—In the field of evolutionary multi-criterion optimization, the hypervolume indicator is the only single set quality measure that is known to be strictly monotonic with ...
Johannes Bader, Eckart Zitzler
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
EVOW
2009
Springer
16 years 1 months ago
Evolutionary Optimization Guided by Entropy-Based Discretization
The Learnable Evolution Model (LEM) involves alternating periods of optimization and learning, performa extremely well on a range of problems, a specialises in achieveing good resu...
Guleng Sheri, David W. Corne
IAT
2008
IEEE
16 years 29 days ago
Competency-Based Intelligent Curriculum Sequencing: Comparing Two Evolutionary Approaches
The process of creating e-learning contents using reusable learning objects (LOs) can be broken down in two sub-processes: LOs finding and LO sequencing. Although semiautomatic to...
Luis de Marcos, Roberto Barchino, José-Javi...