Biomedical Engineering Reference
In-Depth Information
START
Rank assignment
based on
Pareto dominance
Set the required
parameters
Update the
tabu list
Initialize the tabu
list to empty and
set
g
= 0
Get the non-
dominated solutions
Yes
g
= MAXIMUM
ITERATION?
Update the Pareto-
optimal set if the
new solution is better
No
Generation of
neighbors
Output Pareto-optimal
solutions
g
=
g
+ 1
Objective value
evaluation
END
Figure 2.14
Flowchart.of.MOTS.
can.be.avoided.as.new.neighbors.can.always.be.visited.even.if.they.are.not.
nondominated. solutions.. The. operations. of. MOTS. is. summarized. by. the.
lowchart.depicted.in
.
Figure 2.14
.
References
.
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LocalSearchinCombinatorialOptimization
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Wiley,.1997.
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2.. Anton,.H.,.
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Cruces,.1976.
.
4.. Bäck,. T.,.
Evolutionary Algorithms in Theory and Practice: Evolution Strategies,
Evolutionary Programming, Genetic Algorithms,
New. York:. Oxford. University.
Press,.1996.
.
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EvolutionaryComputation1:Basic
AlgorithmsandOperators
,.Bristol,.UK:.Institute.of.Physics,.2000.
.
6.. Bäck,. T.,. Fogel,. D.. B.,. Michalewicz,. Z.. (Eds.),.
Evolutionary Computation 2:
AdvancedAlgorithmsandOperators
,.Bristol,.UK:.Institute.of.Physics,.2000.
.
7.. Bäck,.T.,.Hammel,.U.,.Schwefel,.H..P.,.Evolutionary.computation:.Comments.on.
the.history.and.current.state,.
IEEETransactionsonEvolutionaryComputation
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3-17,.1997.
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