Jumping Gene Computational Approach - Multiobjective Optimization Methodology: A Jumping Gene Approach - page 49

where. C 1 .and. C 2 .are.the.two.chromosomes.selected.for.jumping.operations,.
and. H 1 .and. H 2 .are.the.two.offspring.generated..The.value.of.β.is.computed.as

1/( 1)

(2 ) a

η +

if a < 0.5

C

β =

− 1/( η + 1)

[2(1 − a )] if a ≥ 0.5

C

. . (3.4)

where a ∈[0,1].is.a.randomly.generated.value,.and.η C .is.predeined.
Further. details. and. performance. comparisons. can. be. found. in. Ripon,.
Kwong.and.Man.[46].

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