Scientific Reports,
Год журнала:
2025,
Номер
15(1)
Опубликована: Март 27, 2025
Abstract
Enterprise
Development
Optimizer
(EDO)
is
a
meta-heuristic
algorithm
inspired
by
the
enterprise
development
process
with
strong
global
search
capability.
However,
analysis
of
EDO
shows
that
it
suffers
from
defects
rapidly
decreasing
population
diversity
and
weak
exploitation
ability
when
dealing
complex
optimization
problems,
while
its
algorithmic
structure
has
room
for
further
enhancement
in
process.
In
order
to
solve
these
challenges,
this
paper
proposes
multi-strategy
optimizer
called
MSEDO
based
on
basic
EDO.
A
leader-based
covariance
learning
strategy
proposed,
aiming
strengthen
quality
agents
alleviate
later
stage
through
guiding
role
dominant
group
modifying
leader.
To
dynamically
improve
local
capability
algorithm,
fitness
distance-based
leader
selection
proposed.
addition,
reconstructed
diversity-based
restart
presented.
The
utilized
assist
jump
out
optimum
stuck
stagnation.
Ablation
experiments
verify
effectiveness
strategies
algorithm.
performance
confirmed
comparing
five
different
types
improved
metaheuristic
algorithms.
experimental
results
CEC2017
CEC2022
show
effective
escaping
optimums
favorable
exploration
capabilities.
ten
engineering
constrained
problems
competently
real-world
problems.
Biomimetics,
Год журнала:
2025,
Номер
10(1), С. 31 - 31
Опубликована: Янв. 6, 2025
In
recent
years,
unmanned
aerial
vehicle
(UAV)
technology
has
advanced
significantly,
enabling
its
widespread
use
in
critical
applications
such
as
surveillance,
search
and
rescue,
environmental
monitoring.
However,
planning
reliable,
safe,
economical
paths
for
UAVs
real-world
environments
remains
a
significant
challenge.
this
paper,
we
propose
multi-strategy
improved
red-tailed
hawk
(IRTH)
algorithm
UAV
path
real
environments.
First,
enhance
the
quality
of
initial
population
by
using
stochastic
reverse
learning
strategy
based
on
Bernoulli
mapping.
Then,
is
further
through
dynamic
position
update
optimization
mean
fusion,
which
enhances
exploration
capabilities
helps
it
explore
promising
solution
spaces
more
effectively.
Additionally,
proposed
an
method
frontier
updates
trust
domain,
better
balances
exploitation.
To
evaluate
effectiveness
algorithm,
compare
with
11
other
algorithms
IEEE
CEC2017
test
set
perform
statistical
analysis
to
assess
differences.
The
experimental
results
demonstrate
that
IRTH
yields
competitive
performance.
Finally,
validate
applicability
scenarios,
apply
path-planning
problem
practical
environments,
achieving
successfully
performing
UAVs.
Sensors,
Год журнала:
2025,
Номер
25(7), С. 2336 - 2336
Опубликована: Апрель 7, 2025
The
rapid
expansion
of
unmanned
aerial
vehicle
(UAV)
applications
in
complex
environments
presents
significant
challenges
3D
path
planning,
particularly
overcoming
the
limitations
traditional
methods
for
dynamic
obstacle
avoidance
and
computational
efficiency.
To
address
these
challenges,
this
study
introduces
an
adaptive
whale
optimization
algorithm
(DBO-AWOA),
which
incorporates
chaotic
mapping,
nonlinear
convergence
factors,
inertia
mechanisms,
dung
beetle
optimizer-inspired
reproductive
behaviors.
Specifically,
utilizes
ICMIC
mapping
to
enhance
initial
population
diversity,
a
cosine-based
factor
balance
exploration
exploitation,
hybrid
strategy
inspired
by
optimizer
mitigate
stagnation
local
optima.
When
evaluated
on
CEC2017
benchmark
suite,
DBO-AWOA
demonstrates
superior
precision
robustness,
achieving
lowest
minimum
average
values
across
72%
test
functions.
In
path-planning
simulations
within
mountainous
environments,
generates
smoother,
shorter,
safer
trajectories
compared
existing
variants,
with
fitness
reduced
5-25%.
Although
slight
instability
highly
functions,
its
overall
performance
marks
improvement
global
UAV
planning.
Vibration,
Год журнала:
2025,
Номер
8(1), С. 3 - 3
Опубликована: Янв. 15, 2025
In
mechanical
engineering,
the
building
industry,
and
many
other
branches
of
vibration
machines
are
widely
used,
in
which
circular
directed
oscillations
predominate
form
movement
working
equipment.
This
article
examines
methods
for
generating
asymmetric
oscillations,
estimated
by
a
numerical
parameter,
namely
coefficient
asymmetry
magnitude
driving
force
when
changing
direction
action
motion
within
each
period
oscillations.
It
is
shown
that
vibrations,
devices
consisting
vibrators
called
stages.
These
stages
total
force.
The
behavior
vibrations
equipment
machine
described
analytical
equations,
represent
certain
laws
system.
presents
analysis
obtaining
two-stage,
three-stage,
four-stage
device
with
An
methodology
generalized
law
performed
based
on
application
polyharmonic
oscillation
synthesis
methods.
method
forming
coefficients
terms
Fourier
series
has
limited
capabilities.
develops,
substantiates,
calculating
designing
value
given
wide
range
rational
designs
machines.
proposed
accompanied
example
an
equal
to
10.
Research Square (Research Square),
Год журнала:
2025,
Номер
unknown
Опубликована: Янв. 20, 2025
Abstract
With
the
rapid
advancement
of
Unmanned
Aerial
Vehicle
(UAV)
technology,
trajectory
planning
has
become
a
focus
research.
This
paper
proposes
three-dimensional
path
method
for
UAV
based
on
an
improved
Exponential-triangle
Optimization
Algorithm
(IETO).
By
constructing
multi-objective
optimization
function
that
considers
factors
such
as
length,
flight
altitude,
and
turning
angle,
comprehensive
evaluation
quality
is
able
to
be
achieved.
The
IETO
algorithm
incorporates
interval-constrained
logistic
chaotic
mapping,
dynamic
reverse
learning
strategy,
adaptive
artificial
bee
colony
(ABC)
escape
mechanism
within
ETO
algorithm.
These
enhancements
prevent
premature
convergence
local
optima.
Through
benchmark
tests
CEC2017
test
set
simulations
in
peak
threat
environments,
demonstrated
superior
robustness.
Compared
mainstream
algorithms
like
GWO
GJO,
achieves
best
performance
62%
tests.
It
also
demonstrates
exceptional
solving
complex
functions,
effectively
balances
exploration
exploitation
capabilities.
In
mountainous
generates
smoothest
paths
with
lowest
costs
quickly
converges
optimal
solution.
Biomimetics,
Год журнала:
2025,
Номер
10(5), С. 260 - 260
Опубликована: Апрель 23, 2025
In
real-world
applications,
many
complex
problems
can
be
formulated
as
mathematical
optimization
challenges,
and
efficiently
solving
these
is
critical.
Metaheuristic
algorithms
have
proven
highly
effective
in
addressing
a
wide
range
of
engineering
issues.
The
differentiated
creative
search
recently
proposed
evolution-based
meta-heuristic
algorithm
with
certain
advantages.
However,
it
also
has
limitations,
including
weakened
population
diversity,
reduced
efficiency,
hindrance
comprehensive
exploration
the
solution
space.
To
address
shortcomings
DCS
algorithm,
this
paper
proposes
multi-strategy
(MSDCS)
based
on
collaborative
development
mechanism
evaluation
strategy.
First,
that
organically
integrates
estimation
distribution
to
compensate
for
algorithm's
insufficient
ability
its
tendency
fall
into
local
optimums
through
guiding
effect
dominant
populations,
improve
quality
efficiency
at
same
time.
Secondly,
new
strategy
realize
coordinated
transition
between
exploitation
fitness
distance.
Finally,
linear
size
reduction
incorporated
DCS,
which
significantly
improves
overall
performance
by
maintaining
large
initial
stage
enhance
capability
extensive
space,
then
gradually
decreasing
later
capability.
A
series
validations
was
conducted
CEC2018
test
set,
experimental
results
were
analyzed
using
Friedman
Wilcoxon
rank
sum
test.
show
superior
MSDCS
terms
convergence
speed,
stability,
global
optimization.
addition,
successfully
applied
several
constrained
problems.
all
cases,
outperforms
basic
fast
strong
robustness,
emphasizing
efficacy
practical
applications.
