Introduction - Multiobjective Optimization Methodology: A Jumping Gene Approach - page 1

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Introduction
1.1 BackgroundonGeneticAlgorithms
The.genetic.algorithm.(GA).was.first.proposed.by.John.Holland.[30].in.the.
late.1960s..As.a.major.family.in.evolutionary.algorithms,.it.was.inspired.by.
the.natural.phenomenon.of.biological.evolution,.relying.on.the.principle.of.
“survival.of.the.fittest.”.The.basic.flowchart.of.a.conventional.GA.is.given.in.
Figure 1.1 . .A.GA.process.begins.with.a.random.population.in.which.poten-
tial. solutions. are. encoded. into. chromosomes.. By. evaluating. each. chromo-
some.against.the.objective.functions,.its.goodness,.represented.by.a.fitness.
value,. can. be. determined.. Based. on. the. fitness. value,. some. chromosomes.
are. then. selected. to. form. a. mating. pool. that. will. undergo. genetic. opera-
tions,.namely,.crossover.and.mutation,.to.produce.some.new.solutions..The.
chromosomes.(called.the.parents).in.the.mating.pool.exchange.their.genes.
to.generate.new.chromosomes.via.crossover,.while.some.genes.are.changed.
by.a.random.process.called.mutation..These.two.operations.keep.the.balance.
between.the.exploration.and.exploitation.of.solutions.so.that.a.GA.can.form.
better.solutions.based.on.acquired.information.and.some.random.processes..
The. newly. formed. chromosomes. are. then. assessed. by. objective. functions,.
and.fitness.values.are.assigned..Usually,.fitter.offspring.will.replace.some.or.
all.of.the.old.ones.such.that.a.new.population.is.obtained..This.genetic.cycle.
is.repeated.until.some.criteria.are.met..Further.operational.details.of.GA.can.
be.found.in.[41].
After.about.30.years.of.development.worldwide,.the.GA.has.been.success-
fully. applied. to. various. real-world. applications. [3].. These. areas. include.
physics,. chemistry,. engineering,. medicine,. business. and. management,.
inance.and.trade,.and.more. . Table 1.1 . presents.a.summary.of.the.work..This.
list. is. by. no. means. exhaustive,. but. it. should. provide. an. impression. of. how.
GAs.have.influenced.the.scientific.world.through.research.and.applications.
According. to. the. nature. of. the. problems,. these. applications. can. also. be.
classified.as.single-.or.multiple-objective.optimization..For.single-objective.
optimization,.only.one.objective.is.targeted,.while.there.are.several.in.mul-
tiobjective.optimization..A.unique.global.solution.is.commonly.expected.in.
the.former,.but.a.set.of.global.solutions.should.result.from.the.latter.
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