Heliyon,
Journal Year:
2024,
Volume and Issue:
10(10), P. e30757 - e30757
Published: May 1, 2024
Over
the
last
few
decades,
a
number
of
prominent
meta-heuristic
algorithms
have
been
put
forth
to
address
complex
optimization
problems.
However,
there
is
critical
need
enhance
these
existing
meta-heuristics
by
employing
variety
evolutionary
techniques
tackle
emerging
challenges
in
engineering
applications.
As
result,
this
study
attempts
boost
efficiency
recently
introduced
bio-inspired
algorithm,
Tunicate
Swarm
Algorithm
(TSA),
which
motivated
foraging
and
swarming
behaviour
bioluminescent
tunicates
residing
deep
sea.
Like
other
algorithms,
TSA
has
certain
limitations,
including
getting
trapped
local
optimal
values
lack
exploration
ability,
resulting
premature
convergence
when
dealing
with
highly
challenging
To
overcome
shortcomings,
novel
multi-strategy
ameliorated
TSA,
termed
Quasi-Oppositional
Chaotic
(QOCTSA),
proposed
as
an
enhanced
variant
TSA.
This
method
contributes
simultaneous
incorporation
Based
Learning
(QOBL)
Local
Search
(CLS)
mechanisms
effectively
balance
exploitation.
The
implementation
QOBL
improves
accuracy
rate,
while
inclusion
CLS
strategy
ten
chaotic
maps
exploitation
enhancing
search
ability
around
most
prospective
regions.
Thus,
QOCTSA
significantly
enhances
maintaining
diversification.
experimentations
are
conducted
on
set
thirty-three
diverse
functions:
CEC2005
CEC2019
test
functions,
well
several
real-world
statistical
graphical
outcomes
indicate
that
superior
exhibits
faster
rate
convergence.
Furthermore,
tests,
specifically
Wilcoxon
rank-sum
t-test,
reveal
outperforms
competing
domain
design
Scientific Reports,
Journal Year:
2023,
Volume and Issue:
13(1)
Published: March 30, 2023
Abstract
A
novel
bio-inspired
meta-heuristic
algorithm,
namely
the
American
zebra
optimization
algorithm
(AZOA),
which
mimics
social
behaviour
of
zebras
in
wild,
is
proposed
this
study.
are
distinguished
from
other
mammals
by
their
distinct
and
fascinating
character
leadership
exercise,
navies
baby
to
leave
herd
before
maturity
join
a
separate
with
no
family
ties.
This
departure
encourages
diversification
preventing
intra-family
mating.
Moreover,
convergence
assured
exercise
zebras,
directs
speed
direction
group.
lifestyle
indigenous
nature
main
inspiration
for
proposing
AZOA
algorithm.
To
examine
efficiency
CEC-2005,
CEC-2017,
CEC-2019
benchmark
functions
considered,
compared
several
state-of-the-art
algorithms.
The
experimental
outcomes
statistical
analysis
reveal
that
capable
attaining
optimal
solutions
maximum
while
maintaining
good
balance
between
exploration
exploitation.
Furthermore,
numerous
real-world
engineering
problems
have
been
employed
demonstrate
robustness
AZOA.
Finally,
it
anticipated
will
accomplish
domineeringly
forthcoming
advanced
CEC
complex
problems.
Scientific Reports,
Journal Year:
2023,
Volume and Issue:
13(1)
Published: Aug. 9, 2023
This
study
suggests
a
new
nature-inspired
metaheuristic
optimization
algorithm
called
the
red-tailed
hawk
(RTH).
As
predator,
has
hunting
strategy
from
detecting
prey
until
swoop
stage.
There
are
three
stages
during
process.
In
high
soaring
stage,
explores
search
space
and
determines
area
with
location.
low
moves
inside
selected
around
to
choose
best
position
for
hunt.
Then,
swings
hits
its
target
in
stooping
swooping
stages.
The
proposed
mimics
prey-hunting
method
of
solving
real-world
problems.
performance
RTH
been
evaluated
on
classes
first
class
includes
specific
kinds
problems:
22
standard
benchmark
functions,
including
unimodal,
multimodal,
fixed-dimensional
multimodal
IEEE
Congress
Evolutionary
Computation
2020
(CEC2020),
CEC2022.
is
compared
eight
recent
algorithms
confirm
contribution
these
considered
Farmland
Fertility
Optimizer
(FO),
African
Vultures
Optimization
Algorithm
(AVOA),
Mountain
Gazelle
(MGO),
Gorilla
Troops
(GTO),
COOT
algorithm,
Hunger
Games
Search
(HGS),
Aquila
(AO),
Harris
Hawks
(HHO).
results
regarding
accuracy,
robustness,
convergence
speed.
second
seven
engineering
problems
that
will
be
investigate
other
published
profoundly.
Finally,
proton
exchange
membrane
fuel
cell
(PEMFC)
extraction
parameters
performed
evaluate
complex
problem.
several
papers
approve
performance.
ultimate
each
ability
provide
higher
most
cases.
For
class,
mostly
got
optimal
solutions
functions
faster
provided
better
third
when
resolving
real
word
or
extracting
PEMFC
parameters.
