Akkuş M., Yüzgeç U.
BSEU Journal of Engineering Research and Technology, cilt.1, sa.1, ss.31-41, 2020 (Hakemli Dergi)
Özet
In this
paper
, a
multi
-
objective
version of the Harris Hawk
Optimizer
algorithm (HHO)
is proposed,
which is
called
Multi
-
Objective Harris Hawk Optimization
(MOHHO).
In
the
MOHHO
algorithm,
p
reserving
the structure of the HHO algorithm, an archive
repository
has been added to the HHO algorithm to save and
retrieve t
he Pareto optimal results.
This
repository
is used for simulating the positions and solutions of the
hawks.
The
archive member in the least populat
ed
area
from th
is
archive
is
selected using the roulette wheel
process
.
Th
is
archive member
is utilized as the rabbit in the proposed MOHHO algorithm.
To show the
performance
of the
MOHHO
algorithm
, we have taken
u
nconstrained test functions
known as
ZDT
from the
literature.
For the multi objective benchmarks, t
he MOHHO
algorithm
was
compared with MOALO (Multi
-
objective
Ant
Lion
optimizer) and MODA (Multi
-
objective
Dragonfly optimizer) algorithms
.
Inverted
Generational Distance (IGD)
metric
was
used for
ZDT benchmark
comparison
studies
.
The comparison results
show that the proposed alg
orithm gives better results than the MOALO and MODA al
gorithms in terms of IGD
metric
for all test functions.