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» Variable Length Genomes for Evolutionary Algorithms
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EMO
2005
Springer
76views Optimization» more  EMO 2005»
14 years 12 days ago
Photonic Device Design Using Multiobjective Evolutionary Algorithms
Abstract. The optimization and design of two different types of photonic devices - a Fibre Bragg Grating and a Microstructured Polymer Optical Fibre is presented in light of multi...
Steven Manos, Leon Poladian, Peter J. Bentley, Mar...
RECOMB
2012
Springer
11 years 9 months ago
A Model for Biased Fractionation after Whole Genome Duplication
Background: Paralog reduction, the loss of duplicate genes after whole genome duplication (WGD) is a pervasive process. Whether this loss proceeds gene by gene or through deletion...
David Sankoff, Chunfang Zheng, Baoyong Wang
EC
2006
136views ECommerce» more  EC 2006»
13 years 6 months ago
Error Thresholds in Genetic Algorithms
The error threshold of replication is an important notion of the quasispecies evolution model; it is a critical mutation rate (error rate) beyond which structures obtained by an e...
Gabriela Ochoa
BIBE
2007
IEEE
169views Bioinformatics» more  BIBE 2007»
14 years 1 months ago
Combining Semantics, Context, and Statistical Evidence in Genomics Literature Search
—We present an information retrieval model for combining evidence from concept-based semantics, term statistics, and context for improving search precision of genomics literature...
Jay Urbain, Nazli Goharian, Ophir Frieder
GECCO
2009
Springer
14 years 1 months ago
The relationship between evolvability and bloat
Bloat is a common problem with Evolutionary Algorithms (EAs) that use variable length representation. By creating unnecessarily large individuals it results in longer EA runtimes ...
Jeffrey K. Bassett, Mark Coletti, Kenneth A. De Jo...