In
order
to
solve
the
problem
of
subtraction-average-based
optimizer
(SABO),
which
is
difficult
effectively
balance
local
development
and
global
search
capability,
golden
sine
SABO
integrating
multiple
strategies
(GSABO)
proposed.
The
improved
Sine
chaos
mapping
introduced
refine
population
initialization
strategy
in
enrich
diversity
improve
algorithm's
accuracy
speed.
position
update
method
by
algorithm
further
enhance
capability
SABO.
specific
implementation
steps
GSABO
are
described
detail,
optimization
ability
tested
using
23
benchmark
functions.
test
results
show
that
able
compared
with
current
novel
algorithms,
has
more
excellent
performance
under
most
Energy Sources Part A Recovery Utilization and Environmental Effects,
Journal Year:
2025,
Volume and Issue:
47(1), P. 1789 - 1803
Published: Jan. 5, 2025
Maximum
power
point
tracking
(MPPT)
control
techniques
are
commonly
employed
to
maximize
the
benefits
and
enhance
operational
efficiency
of
photovoltaic
systems
in
challenging
outdoor
environments.
However,
when
array
is
subjected
partial
shading
conditions,
conventional
MPPT
methods
exhibit
inadequate
global
maximum
(GMPP)
performance.
To
this
end,
study,
an
effective
method
for
proposed
based
on
a
hybrid
improved
whale
particle
swarm
optimization
algorithm
(IWPOA).
The
integrates
advantages
Improved
Whale
Optimization
Algorithm
(IWOA)
Particle
Swarm
(PSO)
with
additional
stochastic
elements.
Validation
analysis
under
variety
conditions
reveals
that
IWPOA
significantly
improves
MPPT,
achieving
speed
approximately
0.13
s,
which
represents
18.75–53.57%
enhancement
over
other
comparative
algorithms.
mean
accuracy
99.21%,
it
offers
superior
stability,
making
suitable
diverse
applications
MPPT.
Biomimetics,
Journal Year:
2024,
Volume and Issue:
9(7), P. 399 - 399
Published: July 1, 2024
The
recently
introduced
coati
optimization
algorithm
suffers
from
drawbacks
such
as
slow
search
velocity
and
weak
precision.
An
enhanced
called
CMRLCCOA
is
proposed.
Firstly,
the
Sine
chaotic
mapping
function
used
to
initialize
a
way
obtain
better-quality
populations
increase
diversity
of
population.
Secondly,
generated
candidate
solutions
are
updated
again
using
convex
lens
imaging
reverse
learning
strategy
expand
range.
Thirdly,
Lévy
flight
increases
step
size,
expands
range,
avoids
phenomenon
convergence
too
early.
Finally,
utilizing
crossover
can
effectively
reduce
blind
spots,
making
particles
constantly
close
global
optimum
solution.
four
strategies
work
together
enhance
efficiency
COA
boost
precision
steadiness.
performance
evaluated
on
CEC2017
CEC2019.
superiority
comprehensively
demonstrated
by
comparing
output
with
previously
submitted
algorithms.
Besides
results
iterative
curves,
boxplots
nonparametric
statistical
analysis
illustrate
that
competitive,
significantly
improves
accuracy,
well
local
optimal
solutions.
usefulness
proven
through
three
engineering
application
problems.
A
mathematical
model
hypersonic
vehicle
cruise
trajectory
problem
developed.
result
less
than
other
comparative
algorithms
shortest
path
length
for
this
obtained.
