International Journal of Advanced Technology and Engineering Exploration,
Journal Year:
2024,
Volume and Issue:
11(116)
Published: July 31, 2024
The
production
of
renewable
energy
offers
several
benefits,
such
as
meeting
the
increasing
demand
for
electricity,
facilitating
growth
clean
companies,
and
enhancing
integration
nonconventional
sources
into
existing
power
grid.Solar
wind
are
viable
alternatives
due
to
their
well-established
technological
advancements
support
they
receive
from
government
via
various
initiatives.To
meet
peak
consumer
demand,
International Journal of Systems Science,
Journal Year:
2023,
Volume and Issue:
55(4), P. 814 - 832
Published: Dec. 28, 2023
The
sparrow
search
algorithm
(SSA)
is
an
efficient
swarm-intelligence-based
that
has
made
some
significant
advances
since
its
introduction
in
2020.
A
detailed
overview
of
the
basic
SSA
and
several
SSA-based
variants
presented
this
paper.
To
be
specific,
first,
principle
introduced
including
mechanism
implementation
process.
Second,
many
improved
SSAs
are
reviewed
hybrid,
chaotic,
adaptive,
binary
multi-objective
SSAs.
In
addition,
applications
real
scenarios
such
as
machine
learning
areas,
energy
systems,
path
planning
image
processing.
Finally,
further
research
directions
discussed.
This
survey
paper
aims
to
provide
a
timely
review
on
latest
developments
Journal of Industrial and Management Optimization,
Journal Year:
2025,
Volume and Issue:
0(0), P. 0 - 0
Published: Jan. 1, 2025
In
real-world
production
inventory
systems,
uncertainties
related
to
demand,
production,
defectiveness,
and
costs
pose
significant
challenges.
These
uncertainties—arising
from
incomplete
information,
unpredictability,
complexity,
or
system
variability—complicate
decision-making
planning.
To
address
these
challenges,
various
methodologies,
including
interval,
fuzzy,
stochastic,
fuzzy-stochastic
approaches,
have
been
developed.
The
interval-based
approach,
in
particular,
provides
a
practical
way
represent
uncertainty,
encompassing
factors
like
epistemic
which
arises
inherent
randomness
variability.
This
study
introduces
green
model
within
an
framework,
incorporating
interval-valued
representations
of
defective
rates
stochastic
demand.
Differential
equations
governing
levels
are
formulated
interval
form
solved
using
advanced
parametric
techniques.
Unlike
traditional
models
that
focus
on
cost
minimization
profit
maximization,
this
paper
adopts
optimization
approach
centered
the
profit-cost
ratio
function,
reflecting
negative
relationship
between
rate
hand
sharpening
manufacturer's
goal.
also
explores
business
practice
'buy
now,
pay
later'
(BNPL),
technically
delay-in-payments
is
used
boost
sales.
BNPL
scheme
integrated
into
model,
problem
through
center-radius
technique.
Metaheuristic
algorithms
employed
derive
optimal
solution.
A
numerical
example
validates
while
sensitivity
analyses
explore
variations
algorithmic
parameters.
Statistical
analysis
ANOVA
tests
further
supports
findings.
case
illustrates
how
concept
can
be
practice,
with
Maple
Python.
comprehensive
highlights
model's
effectiveness
managing
uncertainty
optimizing
performance
systems.
Biomimetics,
Journal Year:
2023,
Volume and Issue:
8(8), P. 615 - 615
Published: Dec. 15, 2023
In
the
realm
of
computational
problem-solving,
search
for
efficient
algorithms
tailored
real-world
engineering
challenges
and
software
requirement
prioritization
is
relentless.
This
paper
introduces
Multi-Learning-Based
Reptile
Search
Algorithm
(MLBRSA),
a
novel
approach
that
synergistically
integrates
Q-learning,
competitive
learning,
adaptive
learning
techniques.
The
essence
multi-learning
lies
in
harnessing
strengths
these
individual
paradigms
to
foster
more
robust
versatile
mechanism.
Q-learning
brings
advantage
reinforcement
enabling
algorithm
make
informed
decisions
based
on
past
experiences.
On
other
hand,
an
element
competition,
ensuring
best
solutions
are
continually
evolving
adapting.
Lastly,
ensures
remains
flexible,
adjusting
traditional
(RSA)
parameters.
application
MLBRSA
numerical
benchmarks
few
problems
demonstrates
its
ability
find
optimal
complex
problem
spaces.
Furthermore,
when
applied
complicated
task
prioritization,
showcases
capability
rank
requirements
effectively,
critical
functionalities
addressed
promptly.
Based
results
obtained,
stands
as
evidence
potential
multi-learning,
offering
promising
solution
software-centric
challenges.
Its
adaptability,
competitiveness,
experience-driven
it
valuable
tool
researchers
practitioners.
