Advancing Truss Structure Optimization— A Multi-Objective Weighted Average Algorithm with Enhanced Convergence and Diversity
Results in Engineering,
Год журнала:
2025,
Номер
unknown, С. 104241 - 104241
Опубликована: Фев. 1, 2025
Язык: Английский
MaOSSA: A New High-Efficiency Many-Objective Salp Swarm Algorithm with Information Feedback Mechanism for Industrial Engineering Problems
Results in Engineering,
Год журнала:
2025,
Номер
unknown, С. 104372 - 104372
Опубликована: Фев. 1, 2025
Язык: Английский
Investigating the Impact of Spring Support Stiffness on Dynamic Buckling of Imperfect Steel Trusses
Results in Engineering,
Год журнала:
2025,
Номер
unknown, С. 104490 - 104490
Опубликована: Фев. 1, 2025
Язык: Английский
Multi objective elk herd optimization for efficient structural design
Scientific Reports,
Год журнала:
2025,
Номер
15(1)
Опубликована: Апрель 6, 2025
This
research
presents
an
advancement
of
the
Elk
Herd
Optimization
targeting
specific
real-world
multi-objective
optimization
problems,
this
algorithm
is
stated
as
(MOEHO).
MOEHO
exploits
reproductive
behaviour
among
elk
herds
for
balancing
exploration
and
exploitation
within
procedure
toward
diversification
convergence.
The
performed
better
over
set
small-to-medium
scale
structural
design
problems
thus
widely
applicable
in
engineering
design.
Further,
when
compared
with
eight
benchmark
truss
structures
against
five
well-established
algorithms
has
outperformed
them
perspective
performance
parameters
like
Spacing
(SP),
Hypervolume
(HV)
Inverted
Generational
Distance
(IGD).
More
concrete
statistical
analysis
through
Friedman
rank
test
also
ascertains
robustness
efficiency
algorithm,
especially
at
high
complexities
optimization.
attracts
attention
to
ability
such
which
maintains
a
balance
between
exploitation.
Computational
qualitatively
diversifying
solutions
along
Pareto
front,
makes
it
complex
applications.
Further
into
extension
applicability
on
more
dimensional
applied
even
energy
systems
Язык: Английский
A metaheuristic optimization framework inspired by virus mutations and its ability to optimize the structural design of 2D and 3D steel frames compared to other methods
Results in Engineering,
Год журнала:
2025,
Номер
unknown, С. 105020 - 105020
Опубликована: Апрель 1, 2025
Язык: Английский
A new multi objective crested porcupines optimization algorithm for solving optimization problems
Scientific Reports,
Год журнала:
2025,
Номер
15(1)
Опубликована: Апрель 24, 2025
This
paper
presents
a
new
multi-objective
optimization
algorithm
called
the
Multi-Objective
Crested
Porcupines
Optimization
(MOCPO)
Algorithm,
which
uses
an
elitist,
non-dominated
sorting
and
crowding
distance
mechanism.
MOCPO
is
motivated
by
predator-prey
behavior
of
crested
porcupines
based
on
newly
proposed
Algorithm.
formulated
to
efficiently
manage
conflicting
objectives
in
problems.
Through
use
mechanisms,
promotes
solution
diversity
convergence
towards
Pareto
front.
employs
Information
Feedback
Mechanism
(IFM)
enhanced
updating
strategy
enhance
control.
The
performance
tested
variety
benchmark
problems,
including
ZDT
DTLZ
series,
as
well
real-world
engineering
design
problems
from
RWMOP
suite.
These
test
represent
with
linear,
nonlinear,
continuous,
discrete
nature.
compared
state-of-the-art
algorithms
like
Gradient
Based
Optimizer
(MOGBO),
Preference
inspired
Differential
Evolution
(Pre-DEMO),
Exponential
Distribution
Algorithm
(MOEDO),
Pivot
Evolutionary
(Pi-MOEA),
Clustering
aided
Grid
(ClGrMOEA).
Qualitative
quantitative
analyses
using
standard
metrics
show
effectiveness
algorithm.
Experimental
results
verify
that
provides
substantial
improvements
diversity,
making
it
viable
choice
for
solving
complex
Язык: Английский