Systems Science & Control Engineering,
Год журнала:
2024,
Номер
12(1)
Опубликована: Авг. 1, 2024
Bald
Eagle
Search
(BES)
is
a
recent
and
highly
successful
swarm-based
metaheuristic
algorithm
inspired
by
the
hunting
strategy
of
bald
eagles
in
capturing
prey.
With
its
remarkable
ability
to
balance
global
local
searches
during
optimization,
BES
effectively
addresses
various
optimization
challenges
across
diverse
domains,
yielding
nearly
optimal
results.
This
paper
offers
comprehensive
review
research
on
BES.
Beginning
with
an
introduction
BES's
natural
inspiration
conceptual
framework,
it
explores
modifications,
hybridizations,
applications
domains.
Then,
critical
evaluation
performance
provided,
offering
update
effectiveness
compared
recently
published
algorithms.
Furthermore,
presents
meta-analysis
developments
outlines
potential
future
directions.
As
swarm-inspired
algorithms
become
increasingly
important
tackling
complex
problems,
this
study
valuable
resource
for
researchers
aiming
understand
algorithms,
mainly
focusing
comprehensively.
It
investigates
evolution,
exploring
solving
intricate
fields.
Engineering Applications of Artificial Intelligence,
Год журнала:
2022,
Номер
117, С. 105622 - 105622
Опубликована: Ноя. 25, 2022
The
aim
of
this
study
was
to
gather,
discuss,
and
compare
recently
developed
metaheuristics
understand
the
pace
development
in
field
make
some
recommendations
for
research
community
practitioners.
By
thoroughly
comprehensively
searching
literature
narrowing
search
results,
we
created
with
a
list
57
novel
metaheuristic
algorithms.
Based
on
availability
source
code,
reviewed
analysed
optimization
capability
26
these
algorithms
through
series
experiments.
We
also
evaluated
exploitation
exploration
capabilities
by
using
50
unimodal
functions
multimodal
functions,
respectively.
In
addition,
assessed
balance
29
shifted,
rotated,
composite,
hybrid
CEC-BC-2017
benchmark
functions.
Moreover,
applicability
four
real-world
constrained
engineering
problems.
To
rank
algorithms,
performed
nonparametric
statistical
test,
Friedman
mean
test.
results
declared
that
GBO,
PO,
MRFO
have
better
capabilities.
found
MPA,
FBI,
HBO
be
most
balanced.
Finally,
based
problems,
HBO,
MA
are
suitable.
Collectively,
confidently
recommend
