Several
real-world
problems
can
be
modeled
as
optimization
in
which
multiple
conflicting
objectives
must
optimized
simultaneously.
Evolutionary
algorithms
(EA)
are
able
to
identify
a
set
of
non-dominated
solutions
(Pareto
front)
and
commonly
used
solve
these
problems.
Hybrid
EAs
that
combine
various
techniques
leverage
the
strengths
each
method
involved,
enhancing
their
overall
effectiveness.
This
study
evaluates
performance
well-known
NSGA-III
hybridized
with
Differential
Evolution,
Sine
Cosine,
Arithmetic
on
based
applications
three,
four
five
objective
functions,
extracted
from
CEC
2021
competition.
Performance
comparisons
between
hybrid
original
versions
were
conducted
using
IGD+
HyperVolume
indicators.
Statistical
analysis
via
Wilcoxon
test
revealed
significant
improvements
when
version
is
considered.
Automation in Construction,
Год журнала:
2024,
Номер
166, С. 105630 - 105630
Опубликована: Июль 23, 2024
This
paper
presents
an
optimization
framework
for
steel
trusses.
The
authors
implemented
a
penalty-based
approach
to
optimise
the
size,
shape,
and
topology
based
on
dynamic
grouping
strategy
address
constructability
challenges.
main
contribution
of
is
use
damped
exponential
penalties.
ensures
optimal
designs
by
balancing
structural
complexity,
through
standardization
in
design,
minimizing
total
number
members
variety
sections,
with
overall
cost.
also
detailed
analysis
that
underscores
sensitivity
convergence
algorithmic
hyperparameters,
emphasizing
role
cross-section
assignments
stabilization
truss
piece
counts.
validated
trussed
roof
structure
findings
from
single
optimization.
best
proved
be
Howe
configuration,
highlighting
its
efficiency
meeting
defined
objective
function.
Journal of Optimization,
Год журнала:
2024,
Номер
2024(1)
Опубликована: Янв. 1, 2024
The
multiobjective
(MO)
optimizers
show
great
promise
in
solving
constrained
engineering
structural
problems.
This
paper
introduces
a
MO
version
of
the
Brown
Bear
Optimization
(BBO)
algorithm,
inspired
by
foraging
behavior
brown
bears.
proposed
Multiobjective
(MOBBO)
algorithm
is
applied
to
five
optimization
problems,
including
10‐bar,
25‐bar,
60‐bar,
72‐bar,
and
942‐bar
trusses,
aiming
minimize
both
mass
maximum
nodal
deflection
simultaneously.
Comparative
evaluations
against
six
benchmark
algorithms
demonstrate
MOBBO’s
superior
convergence,
solution
diversity,
effectiveness
addressing
highly
hypervolume
(HV)
inverted
generational
distance
(IGD)
metrics
place
MOBBO
first
rank
according
Friedman
test,
with
an
average
standard
deviation
0.0002.
Moreover,
spacing‐to‐extent
(STE)
(GD)
second.
final
test
highlights
overall
dominance,
achieving
rank.
Best
Pareto
plots,
diversity
graphs,
box
plot
analyses
further
suggest
performance
convergence
compared
existing
algorithms.
Therefore,
can
be
effectively
various
tasks
industry,
offering
refined
global
solutions
contributing
valuable
insights
field
Ain Shams Engineering Journal,
Год журнала:
2024,
Номер
15(10), С. 102982 - 102982
Опубликована: Авг. 2, 2024
The
integration
of
metaheuristics
with
machine
learning
methodologies
presents
significant
advantages,
particularly
in
optimization
and
computational
intelligence.
This
amalgamation
leverages
the
global
search
capabilities
alongside
pattern
recognition
predictive
prowess
learning,
facilitating
enhanced
convergence
rates
solution
quality
complex
problem
spaces.
Quantum
Long
Short-Term
Memory
(QLSTM)
emerges
as
a
highly
efficient
deep
model
tailored
to
tackle
such
intricate
engineering
problems.
QLSTM's
architecture,
comprising
data
encoding,
variational,
quantum
measurement
layers,
facilitates
effective
encoding
processing
civil
data,
leading
heightened
prediction
accuracy.
However,
task
determining
optimal
values
for
QLSTM
parameters
challenges
due
its
NP-problem
nature
time-consuming
characteristics.
To
address
this,
we
propose
an
alternative
technique
optimize
based
on
modified
Electric
Eel
Foraging
Optimization
(MEEFO).
MEEFO
is
version
original
EEFO
that
applies
triangular
mutation
operators
boost
capability
traditional
EEFO.
Thus,
optimizes
boosts
performance.
validate
efficacy
our
proposed
method,
conduct
comprehensive
experiments
utilizing
five
real-world
datasets
related
construction
structure
engineering.
evaluation
outcomes
unequivocally
demonstrate
MMEFO
significantly
enhances
performance
QLSTM.
The
most
commonly
used
objective
function
in
structural
optimization
is
weight
minimization.
Nodal
displacements,
compliance,
the
first
natural
frequency
of
vibration,
critical
load
factor
concerning
global
stability,
and
others
can
also
be
considered
additional
functions.
This
paper
aims
to
propose
seven
innovative
many-objective
problems
(MOSOPs)
applied
25-,
56-,
72-,
120-,
582-bar
trusses,
not
yet
presented
literature,
which
main
objectives,
addition
structure’s
weight,
refer
structures’
vibrational
stability
aspects.
These
characteristics
are
essential
designing
models,
such
as
frequencies
vibration
factors
stability.
Such
new
MOSOPs
have
more
than
three
functions
called
problems.
chosen
difference
between
some
its
factors.
sizing
design
variables
cross-sectional
areas
bars
(continuous
or
discrete).
methodology
involves
finite
element
method
(FEM)
obtain
constraints
multi-objective
evolutionary
algorithms
(MOEAs)
based
on
differential
evolution
solve
analyzed
this
study.
In
addition,
multi-criteria
decision-making
(MCDM)
adopted
extract
solutions
from
Pareto
fronts
according
artificial
decision-maker’s
(DM)
preference
scenarios,
complete
data
for
each
solution
provided.
For
MOSOP
with
functions,
it
possible
observe
variations
final
weights
optimum
designs,
considering
hypothetic
21.09%
(25-bar
truss),
289.73%
(56-bar
70.46%
(72-bar
45.35%
(120-bar
74.92%
(582-bar
truss).
Aerospace,
Год журнала:
2025,
Номер
12(2), С. 101 - 101
Опубликована: Янв. 30, 2025
This
study
proposes
a
design
procedure
for
the
multi-objective
aeroelastic
optimization
of
tow-steered
composite
wing
structure
that
operates
at
transonic
speed.
The
aerodynamic
influence
coefficient
matrix
is
generated
using
doublet
lattice
method,
with
steady-state
component
further
refined
through
high-fidelity
computational
fluid
dynamics
(CFD)
analysis
to
enhance
accuracy
in
conditions.
Finite
element
(FEA)
used
perform
structural
analysis.
A
problem
formulated
structure,
where
objective
functions
are
designed
mass
and
critical
speed,
constraints
include
limits.
comparative
eight
state-of-the-art
algorithms
conducted
evaluate
their
performance
solving
this
problem.
Among
them,
Multi-Objective
Multi-Verse
Optimization
(MOMVO)
algorithm
stands
out,
demonstrating
superior
achieving
best
results
task.
Buildings,
Год журнала:
2025,
Номер
15(6), С. 877 - 877
Опубликована: Март 12, 2025
As
the
operation
of
buildings
becomes
more
efficient,
carbon
emissions
generated
by
other
phases
building’s
life
cycle
should
also
be
mitigated
to
address
climate
crisis.
In
this
sense,
structural
systems
play
an
essential
role
in
total
embedded
construction.
This
paper
presents
approach
conceptual
design
development
truss
structures
based
on
material
quantity
and
carbon.
For
this,
a
multi-objective
optimization
process
enables
integration
different
criteria,
such
as
performance,
shape
complexity,
utilization
ratio,
rationalization.
The
procedure
is
implemented
Rhino/Grasshopper
using
parametric
model
that
designer
can
adjust
according
project
requirements.
was
applied
two
study
cases
consisting
long-span
roof
structures.
results
show
mass
decreased
over
50%
after
implementing
present
approach.
They
indicate
tend
increase
when
augmenting
cross-section
rationalization;
however,
displacements
have
opposite
response.
Furthermore,
it
found
some
topologies
perform
better
regarding
first
objectives
(material
emissions).
proposed
workflow
allowed
for
assessment
rationalization
levels
maintain
reduction
these
variables
while
enabling
suitable
construction,
helping
improve
energy
efficiency
driven
perspective.
