Biomedical Engineering Reference
In-Depth Information
START
Randomly select a
chromosome k
No
i = k ?
Yes
Randomly generate new
insertion positions for both
chromosomes i and k
Randomly generate a new
insertion position
Cut the transposon j from
the original position
Cut the transposons j and l
lfrom the original positions
of the chromosomes i and k,
respectively
Paste the transposon into
the new position
Exchange the two
transposons between the
two chromosomes and paste
them into the new positions
END
Figure 3.12
Flowchart.of.the.cut-and-paste.operation..(From.Chan,.T..M.,.Man,.K..F.,.Kwong,.S.,.Tang,.K..S.,.
A.jumping.gene.paradigm.for.evolutionary.multiobjective.optimization,. IEEETransactionson
EvolutionaryComputation ,.12(2),.143-159,.2008.)
translocation.can.simply.be.treated.as.special.cases.of.copy-and-paste.and.cut-
and-paste.transpositions,.respectively..Compared.with.Simoes's.definition.of.a.
transposon,.all.genes.have.an.equal.chance.to.be.selected.in.our.JG.approach.
without.bias..In.Simoes's.definition,.the.length.and.the.location.of.the.transpo-
son.are.determined.by.the.presence.of.flanking.sequences,.while.they.can.be.
any.values.predefined.or.randomly.chosen.under.our.proposed.JG.framework..
Although. Simoes's. flanking. sequences. are. randomly. selected,. because. the.
transposon.is.defined.as.the.segment.between.two.identical.or.reverse.flanking.
sequences,.some.genes.will.never.become.a.transposon.to.pass.on.their.genetic.
information.if.such.identical.or.reverse.sequence.cannot.be.found.
3.4 Real-CodingJumpingOperations
As.mentioned.in.Section.3.3.1,.the.transposon.can.be.of.any.data.type,.and.
the.designed.JG.operations.can.also.be.dealt.with.a.GA.using.different.cod-
ing.schemes..However,.precautions.should.be.taken.for.a.nonbinary.type.of.
 
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