Overview of Multiobjective Optimization - Multiobjective Optimization Methodology: A Jumping Gene Approach - page 12

START

Rank assignment
based on Pareto
dominance

Set the required
parameters and
generation counter
g = 0

Yes

g = MAXIMUM
GENERATION?

Niche count calculation

No

Population initialization

Linearly scaled fitness
and shared fitness
assignment

Roulette wheel
selection

Objective value
evaluation

Crossover g = g + 1

Rank assignment
based on
Pareto dominance

Mutation

Output Pareto-optimal
solutions

Niche count calculation

Objective value
evaluation

Linearly scaled fitness
and shared fitness
assignment

END

Figure 2.1
Flowchart.of.MOGA.

f 2

A

Rank
value

F

E

A: 1
B: 1
C: 1
D: 2
E: 3
F: 5

B

D

C

f 1

Figure 2.2
Fonseca.and.Fleming's.ranking.scheme.for.minimization.problems.