Engineering Computations,
Год журнала:
2025,
Номер
unknown
Опубликована: Фев. 10, 2025
Purpose
The
fishing
cat's
unique
hunting
strategies,
including
ambush,
detection,
diving
and
trapping,
inspired
the
development
of
a
novel
metaheuristic
optimization
algorithm
named
Fishing
Cat
Optimizer
(FCO).
purpose
this
paper
is
to
introduce
FCO,
offering
fresh
perspective
on
demonstrating
its
potential
for
solving
complex
problems.
Design/methodology/approach
FCO
structures
process
into
four
distinct
phases.
Each
phase
incorporates
tailored
search
strategy
enrich
diversity
population
attain
an
optimal
balance
between
extensive
global
exploration
focused
local
exploitation.
Findings
To
assess
efficacy
algorithm,
we
conducted
comparative
analysis
with
state-of-the-art
algorithms,
COA,
WOA,
HHO,
SMA,
DO
ARO,
using
test
suite
comprising
75
benchmark
functions.
findings
indicate
that
achieved
results
88%
functions,
whereas
SMA
which
ranked
second,
excelled
only
21%
Furthermore,
secured
average
ranking
1.2
across
sets
CEC2005,
CEC2017,
CEC2019
CEC2022,
superior
convergence
capability
robustness
compared
other
comparable
algorithms.
Research
limitations/implications
Although
performs
excellently
in
single-objective
problems
constrained
problems,
it
also
has
some
shortcomings
defects.
First,
structure
relatively
there
are
many
parameters.
value
parameters
certain
impact
Second,
computational
complexity
high.
When
high-dimensional
takes
more
time
than
algorithms
such
as
GWO
WOA.
Third,
although
multimodal
rarely
obtains
theoretical
solution
when
combinatorial
Practical
implications
applied
five
common
engineering
design
Originality/value
This
innovatively
proposes
mimics
mechanisms
cats,
strategies
lurking,
perceiving,
rapid
precise
trapping.
These
abstracted
closely
connected
iterative
stages,
corresponding
in-depth
exploration,
multi-dimensional
fine
developmental
localized
refinement
contraction
search.
enables
efficient
fine-tuning
environments,
significantly
enhancing
algorithm's
adaptability
efficiency.
Materials Testing,
Год журнала:
2023,
Номер
65(12), С. 1767 - 1775
Опубликована: Окт. 13, 2023
Abstract
Nature-inspired
metaheuristic
algorithms
are
gaining
popularity
with
their
easy
applicability
and
ability
to
avoid
local
optimum
points,
they
spreading
wide
application
areas.
Meta-heuristic
optimization
used
achieve
an
design
in
engineering
problems
aiming
obtain
lightweight
designs.
In
this
article,
structural
methods
the
process
of
achieving
a
seat
bracket.
As
result
topology
optimization,
new
concept
bracket
was
created
shape
optimization.
mass
stress
values
obtained
depending
on
variables,
constraint,
objective
functions
were
by
using
artificial
neural
networks.
The
problem
based
minimization
is
solved
applying
dandelion
algorithm
verified
finite
element
analysis.
Materials Testing,
Год журнала:
2024,
Номер
66(4), С. 544 - 552
Опубликована: Янв. 24, 2024
Abstract
Nature-inspired
metaheuristic
optimization
algorithms
have
many
applications
and
are
more
often
studied
than
conventional
techniques.
This
article
uses
the
mountain
gazelle
optimizer,
a
recently
created
algorithm,
artificial
neural
network
to
optimize
mechanical
components
in
relation
vehicle
component
optimization.
The
family
formation,
territory-building,
food-finding
strategies
of
gazelles
serve
as
major
inspirations
for
algorithm.
In
order
various
engineering
challenges,
base
algorithm
(MGO)
is
hybridized
with
Nelder–Mead
(HMGO-NM)
current
work.
considered
was
applied
solve
four
different
categories,
namely
automobile,
manufacturing,
construction,
tasks.
Moreover,
obtained
results
compared
terms
statistics
well-known
algorithms.
findings
show
dominance
over
rest
optimizers.
being
said
HMGO
can
be
common
range
industrial
real-world
problems.
Materials Testing,
Год журнала:
2024,
Номер
66(9), С. 1439 - 1448
Опубликована: Май 24, 2024
Abstract
Optimization
techniques
play
a
pivotal
role
in
enhancing
the
performance
of
engineering
components
across
various
real-world
applications.
Traditional
optimization
methods
are
often
augmented
with
exploitation-boosting
due
to
their
inherent
limitations.
Recently,
nature-inspired
algorithms,
known
as
metaheuristics
(MHs),
have
emerged
efficient
tools
for
solving
complex
problems.
However,
these
algorithms
face
challenges
such
imbalance
between
exploration
and
exploitation
phases,
slow
convergence,
local
optima.
Modifications
incorporating
oppositional
techniques,
hybridization,
chaotic
maps,
levy
flights
been
introduced
address
issues.
This
article
explores
application
recently
developed
crayfish
algorithm
(COA),
assisted
by
artificial
neural
networks
(ANN),
design
optimization.
The
COA,
inspired
foraging
migration
behaviors,
incorporates
temperature-dependent
strategies
balance
phases.
Additionally,
ANN
augmentation
enhances
algorithm’s
accuracy.
COA
method
optimizes
components,
including
cantilever
beams,
hydrostatic
thrust
bearings,
three-bar
trusses,
diaphragm
springs,
vehicle
suspension
systems.
Results
demonstrate
effectiveness
achieving
superior
solutions
compared
other
emphasizing
its
potential
diverse
Materials Testing,
Год журнала:
2024,
Номер
66(7), С. 1063 - 1073
Опубликована: Апрель 30, 2024
Abstract
In
this
article,
a
newly
developed
optimization
approach
based
on
mathematics
technique
named
the
geometric
mean
algorithm
is
employed
to
address
challenge
of
robot
gripper,
airplane
bracket,
and
suspension
arm
automobiles,
followed
by
an
additional
three
engineering
problems.
Accordingly,
other
challenges
are
ten-bar
truss,
three-bar
tubular
column,
spring
systems.
As
result,
demonstrates
promising
statistical
outcomes
when
compared
well-established
algorithms.
Additionally,
it
requires
less
iteration
achieve
global
optimum
solution.
Furthermore,
exhibits
minimal
deviations
in
results,
even
techniques
produce
better
or
similar
outcomes.
This
suggests
that
proposed
paper
can
be
effectively
utilized
for
wide
range
critical
industrial
real-world
challenges.
Materials Testing,
Год журнала:
2024,
Номер
66(5), С. 696 - 704
Опубликована: Фев. 19, 2024
Abstract
Thin-walled
structures
are
one
of
the
important
safety
components
used
in
vehicles.
They
placed
front
parts
vehicles
to
minimize
impacts
that
occur
event
a
collision,
and
they
absorb
impact
force
by
changing
shape
collision.
Crash
boxes
have
high-impact
absorption,
low
weight,
low-cost
expectations.
In
design
crash
boxes,
thin-walled
preferred
due
their
high
deformation
capability.
this
study,
additive
manufacturing
method
was
produce
structures.
were
produced
methods
using
PLA
ABS
materials.
The
manufactured
tested
an
test.
experimental
results,
energy
absorption
ability
from
materials
examined,
fragility
observed.
results
verified
finite
element
analysis
made
Materials Testing,
Год журнала:
2024,
Номер
66(8), С. 1230 - 1240
Опубликована: Июль 5, 2024
Abstract
This
paper
introduces
a
novel
approach,
the
Modified
Electric
Eel
Foraging
Optimization
(EELFO)
algorithm,
which
integrates
artificial
neural
networks
(ANNs)
with
metaheuristic
algorithms
for
solving
multidisciplinary
design
problems
efficiently.
Inspired
by
foraging
behavior
of
electric
eels,
algorithm
incorporates
four
key
phases:
interactions,
resting,
hunting,
and
migrating.
Mathematical
formulations
each
phase
are
provided,
enabling
to
explore
exploit
solution
spaces
effectively.
The
algorithm’s
performance
is
evaluated
on
various
real-world
optimization
problems,
including
weight
engineering
components,
economic
pressure
handling
vessels,
cost
welded
beams.
Comparative
analyses
demonstrate
superiority
MEELFO
in
achieving
optimal
solutions
minimal
deviations
computational
effort
compared
existing
methods.
Materials Testing,
Год журнала:
2024,
Номер
66(2), С. 198 - 206
Опубликована: Янв. 8, 2024
Abstract
One
of
the
most
researched
technologies
among
used
for
producing
complex
and
diverse
parts
today
is
additive
manufacturing.
In
manufacturing,
production
can
be
carried
out
using
thermoplastic
metal
materials
without
requiring
an
additional
process.
Among
manufacturing
technologies,
Fused
Filament
Fabrication
(FFF)
method
widely
worldwide
due
to
its
affordability
broad
application
area.
FFF
a
in
which
part
formation
achieved
by
depositing
melted
on
each
other.
recent
years,
polymer
such
as
polylactic
acid
(PLA),
polyethylene
terephthalate
glycol
(PETG),
acrylonitrile
butadiene
styrene
(ABS)
have
been
frequently
many
industrial
areas
because
they
are
lightweight,
inexpensive,
sustainable,
provide
sufficient
strength
engineering
applications.
This
study
conducted
tensile,
three-point
bending,
Charpy,
compression
tests
PLA,
PETG,
ABS
at
angles
15°–75°
30°–60°,
results
were
compared.
Materials Testing,
Год журнала:
2024,
Номер
66(6), С. 876 - 882
Опубликована: Март 13, 2024
Abstract
Nowadays,
the
need
for
new
technologies
is
increasing,
especially
to
find
solutions
inadequacies
in
production
of
complex
structures.
The
additive
manufacturing
methods
developed
facilitate
parts
and
move
technology
forward
with
factors
such
as
cost
efficiency.
With
optimization
designed
by
methods,
it
possible
obtain
optimum
product
even
most
At
end
process,
final
desired
properties
obtained
a
result
part
size
tolerance
precision
optimizations.
In
this
study,
lattice
applied
passenger
aircraft
bracket.
It
aimed
reduce
weight
and,
at
same
time,
increase
efficiency
optimizing
For
purpose,
Altair
Inspire
program
was
used,
variation
mass,
displacement,
safety
coefficient,
stress
values
according
different
structures
were
investigated.
Materials Testing,
Год журнала:
2024,
Номер
66(6), С. 847 - 855
Опубликована: Март 22, 2024
Abstract
In
recent
years,
additive
manufacturing
(AM)
technologies
have
been
used
in
many
industries,
such
as
automotive,
defense,
space,
and
aviation.
Depending
on
the
development
of
this
technology,
effect
relationship
between
parameters,
raster
angles,
production
speed,
melting
temperature
during
materials,
has
an
important
issue
mechanical
properties
materials.
study,
effects
±45°
0–90°
angles
15
%
short
carbon
fiber
reinforced
polyethylenetereflatate
(CF15PET)
30
glass
polypropylene
(GF30PP)
materials
were
investigated.
As
a
result
it
was
determined
that
different
affect
both
