Electronics,
Journal Year:
2023,
Volume and Issue:
12(20), P. 4198 - 4198
Published: Oct. 10, 2023
The
aim
of
this
work
is
to
obtain
multi-objective
linear
programming
algorithms
that
can
be
used
solve
the
global
problem
multi-object
safety
control
processes
in
order
minimize
risk
collisions.
In
optimization
models,
satisfactory
trade-off
assesses
and
resolves
conflict
between
different
objectives.
A
comparison
single-,
bi-,
tri-objective
allows
us
adapt
appropriate
method
conditions
process.
An
important
outcome
present
research
demonstration
greater
effectiveness
bi-
compared
single-objective
optimization,
reflecting
compromises
taken
into
account
when
choosing
objects
achieving
a
minimum
collision
passing
them.
PLoS ONE,
Journal Year:
2024,
Volume and Issue:
19(8), P. e0308474 - e0308474
Published: Aug. 19, 2024
This
research
article
presents
the
Multi-Objective
Hippopotamus
Optimizer
(MOHO),
a
unique
approach
that
excels
in
tackling
complex
structural
optimization
problems.
The
(HO)
is
novel
meta-heuristic
methodology
draws
inspiration
from
natural
behaviour
of
hippos.
HO
built
upon
trinary-phase
model
incorporates
mathematical
representations
crucial
aspects
Hippo's
behaviour,
including
their
movements
aquatic
environments,
defense
mechanisms
against
predators,
and
avoidance
strategies.
conceptual
framework
forms
basis
for
developing
multi-objective
(MO)
variant
MOHO,
which
was
applied
to
optimize
five
well-known
truss
structures.
Balancing
safety
precautions
size
constraints
concerning
stresses
on
individual
sections
constituent
parts,
these
problems
also
involved
competing
objectives,
such
as
reducing
weight
structure
maximum
nodal
displacement.
findings
six
popular
methods
were
used
compare
results.
Four
industry-standard
performance
measures
this
comparison
qualitative
examination
finest
Pareto-front
plots
generated
by
each
algorithm.
average
values
obtained
Friedman
rank
test
analysis
unequivocally
showed
MOHO
outperformed
other
resolving
significant
quickly.
In
addition
finding
preserving
more
Pareto-optimal
sets,
recommended
algorithm
produced
excellent
convergence
variance
objective
decision
fields.
demonstrated
its
potential
navigating
objectives
through
diversity
analysis.
Additionally,
swarm
effectively
visualize
MOHO's
solution
distribution
across
iterations,
highlighting
superior
behaviour.
Consequently,
exhibits
promise
valuable
method
issues.
Scientific Reports,
Journal Year:
2024,
Volume and Issue:
14(1)
Published: Dec. 30, 2024
The
study
suggests
a
better
multi-objective
optimization
method
called
2-Archive
Multi-Objective
Cuckoo
Search
(MOCS2arc).
It
is
then
used
to
improve
eight
classical
truss
structures
and
six
ZDT
test
functions.
aims
minimize
both
mass
compliance
simultaneously.
MOCS2arc
an
advanced
version
of
the
traditional
(MOCS)
algorithm,
enhanced
through
dual
archive
strategy
that
significantly
improves
solution
diversity
performance.
To
evaluate
effectiveness
MOCS2arc,
we
conducted
extensive
comparisons
with
several
established
algorithms:
MOSCA,
MODA,
MOWHO,
MOMFO,
MOMPA,
NSGA-II,
DEMO,
MOCS.
Such
comparison
has
been
made
various
performance
metrics
compare
benchmark
efficacy
proposed
algorithm.
These
comprehensively
assess
algorithms'
abilities
generate
diverse
optimal
solutions.
statistical
results
demonstrate
superior
evidenced
by
Additionally,
Friedman's
&
Wilcoxon's
corroborate
finding
consistently
delivers
compared
others.
show
highly
effective
improved
algorithm
for
structure
optimization,
offering
significant
promising
improvements
over
existing
methods.
Biomimetics,
Journal Year:
2023,
Volume and Issue:
8(2), P. 241 - 241
Published: June 7, 2023
Metamaterials
have
unique
physical
properties.
They
are
made
of
several
elements
and
structured
in
repeating
patterns
at
a
smaller
wavelength
than
the
phenomena
they
affect.
Metamaterials'
exact
structure,
geometry,
size,
orientation,
arrangement
allow
them
to
manipulate
electromagnetic
waves
by
blocking,
absorbing,
amplifying,
or
bending
achieve
benefits
not
possible
with
ordinary
materials.
Microwave
invisibility
cloaks,
invisible
submarines,
revolutionary
electronics,
microwave
components,
filters,
antennas
negative
refractive
index
utilize
metamaterials.
This
paper
proposed
an
improved
dipper
throated-based
ant
colony
optimization
(DTACO)
algorithm
for
forecasting
bandwidth
metamaterial
antenna.
The
first
scenario
tests
covered
feature
selection
capabilities
binary
DTACO
dataset
that
was
being
evaluated,
second
illustrated
algorithm's
regression
skills.
Both
scenarios
part
studies.
state-of-the-art
algorithms
DTO,
ACO,
particle
swarm
(PSO),
grey
wolf
optimizer
(GWO),
whale
(WOA)
were
explored
compared
algorithm.
basic
multilayer
perceptron
(MLP)
regressor
model,
support
vector
(SVR)
random
forest
(RF)
model
contrasted
optimal
ensemble
DTACO-based
proposed.
In
order
assess
consistency
developed,
statistical
research
use
Wilcoxon's
rank-sum
ANOVA
tests.
Computer Modeling in Engineering & Sciences,
Journal Year:
2023,
Volume and Issue:
139(3), P. 2557 - 2604
Published: Dec. 26, 2023
This
research
paper
presents
a
novel
optimization
method
called
the
Synergistic
Swarm
Optimization
Algorithm
(SSOA).The
SSOA
combines
principles
of
swarm
intelligence
and
synergistic
cooperation
to
search
for
optimal
solutions
efficiently.A
mechanism
is
employed,
where
particles
exchange
information
learn
from
each
other
improve
their
behaviors.This
enhances
exploitation
promising
regions
in
space
while
maintaining
exploration
capabilities.Furthermore,
adaptive
mechanisms,
such
as
dynamic
parameter
adjustment
diversification
strategies,
are
incorporated
balance
exploitation.By
leveraging
collaborative
nature
integrating
cooperation,
aims
achieve
superior
convergence
speed
solution
quality
performance
compared
algorithms.The
effectiveness
proposed
investigated
solving
23
benchmark
functions
various
engineering
design
problems.The
experimental
results
highlight
potential
addressing
challenging
problems,
making
it
tool
wide
range
applications
beyond.Matlab
codes
available
at:
https://www.mathworks.com/matlabcentral/fileexchange/153466-synergistic
