International journal of engineering. Transactions B: Applications,
Journal Year:
2023,
Volume and Issue:
36(11), P. 2038 - 2051
Published: Jan. 1, 2023
The
importance
of
employing
appropriate
pricing
strategies
for
perishable
products
within
the
supply
chain
cannot
be
overstated.
Pricing
is
a
cross-functional
driver
each
chain,
playing
an
irrefutable
role
in
success
and
profitability
alongside
other
factors
such
as
inventory
production
policies
which
has
been
investigated
this
research.
research
emphasizes
significant
profitability,
along
with
interplay
control,
highlighting
their
collective
influence
on
financial
outcomes,
subject
dynamic
multi-product,
multi-period
problem
three-level
garnered
relatively
limited
attention.
study
focuses
optimizing
integrated
production-distribution
system
multiple
producers
distribution
centers
serving
specific
customer
groups.
Direct
shipments
between
centers,
retailers
are
optimized
using
vehicle
routing
approach.
A
mixed-integer
programming
model
formulated,
genetic
algorithm-based
metaheuristic
approach
proposed.
BARON
solver
was
initially
used
to
solve
two
simplified
test
problems,
results
compared
self-designed
algorithm
implemented
C#.
After
confirming
efficiency
effectiveness
our
(GA),
investigation
further
extended
encompass
five
distinct
comprising
nine
sub-problems.
GA
demonstrates
its
power
adaptability
by
providing
high-quality
solutions
efficiently
reasonable
computational
time.
Complex System Modeling and Simulation,
Journal Year:
2024,
Volume and Issue:
4(2), P. 184 - 209
Published: June 1, 2024
Remanufacturing
is
regarded
as
a
sustainable
manufacturing
paradigm
of
energy
conservation
and
environment
protection.
To
improve
the
efficiency
remanufacturing
process,
this
work
investigates
an
integrated
scheduling
problem
for
disassembly
reprocessing
in
where
product
structures
uncertainty
are
taken
into
account.
First,
stochastic
programming
model
developed
to
minimize
maximum
completion
time
(makespan).
Second,
Q-learning
based
hybrid
meta-heuristic
(Q-HMH)
specially
devised.
In
each
iteration,
method
employed
adaptively
choose
premium
algorithm
from
four
candidate
ones,
including
genetic
(GA),
artificial
bee
colony
(ABC),
shuffled
frog-leaping
(SFLA),
simulated
annealing
(SA)
methods.
At
last,
simulation
experiments
carried
out
by
using
sixteen
instances
with
different
scales,
three
state-of-the-art
algorithms
literature
exact
solver
CPLEX
chosen
comparisons.
By
analyzing
results
average
relative
percentage
deviation
(RPD)
metric,
we
find
that
Q-HMH
outperforms
its
rivals
9.79%-26.76%.
The
comparisons
verify
excellent
competitiveness
solving
concerned
problems.
Processes,
Journal Year:
2023,
Volume and Issue:
11(8), P. 2462 - 2462
Published: Aug. 16, 2023
Disassembly
sequence
planning
(DSP)
is
a
key
approach
for
optimizing
various
industrial
equipment-maintenance
processes.
Finding
fast
and
effective
DSP
solutions
plays
an
important
role
in
improving
maintenance
efficiency
quality.
However,
when
disassembling
equipment,
there
are
many
uncertainties
that
can
have
detrimental
impact
on
the
disassembly
subsequent
work.
Therefore,
this
paper
proposes
multi-objective
problem
uncertain
environment
addresses
process
through
stochastic
planning,
with
objectives
of
minimizing
time
enhancing
responsiveness
to
priority
components.
Due
complexity
problem,
improved
peafowl
optimization
algorithm
(IPOA)
proposed
efficient
problem-solving.
The
specifically
designed
incorporates
four
customized
mechanisms:
peafowls’
courtship
behavior,
adaptive
behavior
female
peafowls
proximity,
search
chicks,
interactive
among
male
peafowls.
These
mechanisms
enable
optimal
or
near-optimal
solutions.
Through
comparisons
real-world
case
other
advanced
algorithms,
superiority
IPOA
solving
problems
demonstrated.
This
research
contributes
quality,
bringing
positive
impacts
equipment
maintenance.
Processes,
Journal Year:
2023,
Volume and Issue:
11(11), P. 3057 - 3057
Published: Oct. 24, 2023
Disassembly
plays
a
pivotal
role
in
the
maintenance
of
industrial
equipment.
However,
intricate
nature
machinery
and
effects
wear
tear
introduce
inherent
uncertainty
into
disassembly
process.
The
inadequacy
representing
this
within
equipment
has
posed
an
ongoing
challenge
contemporary
research.
This
study
centers
on
sequence
planning
(DSP)
context
maintenance,
with
primary
aim
to
mitigate
adverse
uncertainty.
To
effectively
address
challenge,
we
multi-objective
DSP
problem
utilize
triangular
fuzzy
numbers
from
logic
manage
throughout
Our
objectives
encompass
minimizing
time,
reducing
tool
changes
directional
reversals,
improving
responsiveness
emergency
needs.
Recognizing
complexities
problem,
present
innovative
enhanced
water
wave
optimization
(EWWO)
algorithm,
integrating
propagation,
refraction,
breaking
operators
alongside
novel
local
search
strategies.
Through
rigorous
validation
real-world
cases,
not
only
demonstrate
algorithm’s
potential
solving
challenges
but
also
underscore
its
exceptional
performance
producing
high-quality
efficient
solutions.
In
comparison
other
algorithms,
EWWO
provides
significant
advantages
evaluation
metrics,
including
Hypervolume
(HV),
Spread,
CPU
time.
Moreover,
application
offers
comprehensive
solutions,
empowering
decision
makers
make
informed
choices
diverse
scenarios.
findings
lead
conclusion
that
research
substantial
support
for
addressing
field
significantly
enhance
efficiency
quality
processes.
Processes,
Journal Year:
2024,
Volume and Issue:
12(10), P. 2253 - 2253
Published: Oct. 15, 2024
The
rapid
advancement
of
industrial
processes
makes
ensuring
the
stability
equipment
a
critical
factor
in
improving
production
efficiency
and
safeguarding
operational
safety.
Fault
warning
systems,
as
key
technological
means
to
enhance
stability,
are
increasingly
gaining
attention
across
industries.
However,
structures
functions
become
complex,
traditional
fault
methods
face
challenges
such
limited
prediction
accuracy
difficulties
meeting
real-time
requirements.
To
address
these
challenges,
this
paper
proposes
an
innovative
hybrid
method.
proposed
approach
integrates
multi-strategy
improved
red
deer
optimization
algorithm
(MIRDA),
mechanism,
bidirectional
long
short-term
memory
network
(BiLSTM).
Firstly,
(RDA)
is
enhanced
through
improvements
population
initialization
strategy,
adaptive
optimal
guidance
chaos
regulation
factor,
double-sided
mirror
reflection
theory,
thereby
enhancing
its
performance.
Subsequently,
MIRDA
employed
optimize
hyperparameters
BiLSTM
model
incorporating
mechanism.
A
predictive
then
constructed
based
on
optimized
Attention-BiLSTM,
which,
combined
with
sliding
window
approach,
provides
robust
support
for
threshold
identification.
algorithm’s
efficacy
demonstrated
application
real-world
gas-fired
power
plant
cases.
Comparative
analyses
other
advanced
algorithms
reveal
superior
robustness
efficiently
issuing
warnings.
This
research
not
only
more
reliable
safeguard
stable
operation
but
also
pioneers
new
avenue
metaheuristic
algorithms.
