Systems,
Год журнала:
2024,
Номер
12(11), С. 472 - 472
Опубликована: Ноя. 5, 2024
As
the
decarbonization
strategies
of
automated
container
terminals
(ACTs)
continue
to
advance,
electrically
powered
Battery-Automated
Guided
Vehicles
(B-AGVs)
are
being
widely
adopted
in
ACTs.
The
U-shaped
ACT,
as
a
novel
layout,
faces
higher
AGV
energy
consumption
due
its
deep
yard
characteristics.
A
key
issue
is
how
adopt
charging
suited
varying
conditions
reduce
operational
capacity
loss
caused
by
charging.
This
paper
proposes
simulation-based
optimization
method
for
ACTs
based
on
an
improved
Proximal
Policy
Optimization
(PPO)
algorithm.
Firstly,
Gated
Recurrent
Unit
(GRU)
structures
incorporated
into
PPO
capture
temporal
correlations
state
information.
To
effectively
limit
policy
update
magnitudes
PPO,
we
improve
clipping
function.
Secondly,
simulation
model
established
mimicking
process
Lastly,
iterative
training
proposed
conducted
model.
experimental
results
indicate
that
converges
faster
than
standard
and
Deep
Q-network
(DQN).
When
comparing
method-based
threshold
with
fixed
strategy
across
six
different
scenarios
rates,
demonstrates
better
adaptability
terminal
condition
variations
two-thirds
scenarios.
International Journal of Production Research,
Год журнала:
2024,
Номер
unknown, С. 1 - 16
Опубликована: Апрель 15, 2024
An
efficient
and
effective
spare
parts
supply
chain
management
is
crucial
to
ensure
highly
available
production
systems.
However,
achieving
such
a
challenging
due
the
intrinsic
characteristics
of
parts.
Traditional
chains
(TSPSCs)
adopt
large
inventories
tackle
characteristics,
with
disadvantages
in
terms
high
inventory
costs.
Recently,
Additive
Manufacturing
(AM)
has
shown
breakthrough
potential,
allowing
transition
from
TSPSCs
digital
(DSPSCs),
where
are
no
longer
stored
amounts
but
digitally
produced
only
when
needed.
despite
DSPSCs
benefits,
complete
still
far
becoming
reality.
Indeed,
hindering
lack
expertise
three
main
areas,
i.e.
how
design,
operate,
control
monitor
DSPSC.
With
this
position
paper,
we
envision
twin
(DT)
could
overcome
these
issues,
enabling
full
Moreover,
work
further
concretely
suggests
DT
be
developed,
providing
basis
for
developing
both
theoretical
practical
knowledge
necessary
render
Sensors,
Год журнала:
2024,
Номер
24(18), С. 6069 - 6069
Опубликована: Сен. 19, 2024
There
is
a
growing
need
to
implement
modern
technologies,
such
as
digital
twinning,
improve
the
efficiency
of
transport
fleet
maintenance
processes
and
maintain
company
operational
capacity
at
required
level.
A
comprehensive
review
existing
literature
conducted
address
this,
offering
an
up-to-date
analysis
relevant
content
in
this
field.
The
methodology
employed
systematic
using
Primo
multi-search
tool,
adhering
Preferred
Reporting
Items
for
Systematic
Reviews
Meta-Analyses
(PRISMA)
guidelines.
selection
criteria
focused
on
English
studies
published
between
2012
2024,
resulting
201
highly
papers.
These
papers
were
categorized
into
seven
groups:
(a)
air
transportation,
(b)
railway
(c)
land
transportation
(road),
(d)
in-house
logistics,
(e)
water
intermodal
(f)
supply
chain
operation,
(g)
other
applications.
notable
strength
study
its
use
diverse
scientific
databases
facilitated
by
tool.
Additionally,
bibliometric
was
performed,
revealing
evolution
DT
applications
over
past
decade
identifying
key
areas
predictive
maintenance,
condition
monitoring,
decision-making
processes.
This
highlights
varied
levels
adoption
across
different
sectors
underscores
promising
future
development,
particularly
underrepresented
domains
like
chains
transport.
paper
identifies
significant
research
gaps,
including
integration
challenges,
real-time
data
processing,
standardization
needs.
Future
directions
are
proposed,
focusing
enhancing
diagnostics,
automating
processes,
optimizing
inventory
management.
also
outlines
framework
systems,
detailing
components
functionalities
essential
effective
findings
provide
roadmap
innovations
improvements
within
industry.
ends
with
conclusions
directions.
IET Intelligent Transport Systems,
Год журнала:
2025,
Номер
19(1)
Опубликована: Янв. 1, 2025
ABSTRACT
Automated
guided
vehicles
(AGVs)
serve
as
pivotal
equipment
for
horizontal
transportation
in
automated
container
terminals
(ACTs),
necessitating
the
optimization
of
AGV
scheduling.
The
dynamic
nature
port
operations
introduces
uncertainties
energy
consumption,
while
battery
constraints
pose
significant
operational
challenges.
However,
limited
research
has
integrated
charging
and
discharging
behaviors
into
operations.
This
study
innovatively
proposes
an
scheduling
model
that
incorporates
a
resilient
adaptive
strategy,
adjusting
balance
between
vehicle
completion
tasks,
enabling
AGVs
to
complete
fixed
tasks
shortest
time.
Differing
from
most
existing
primarily
based
on
OR‐typed
algorithms,
this
reinforcement
learning‐based
method.
Finally,
series
numerical
experiments,
which
is
real
large‐scale
terminal
Pearl
River
Delta
(PRD)
region
Southern
China,
are
conducted
verify
effectiveness
efficiency
algorithm.
Some
beneficial
management
insights
obtained
sensitivity
analysis
practitioners.
Notably,
paramount
observation
efficacy
does
not
necessarily
correlate
positively
with
their
number.
Instead,
it
follows
“U‐shaped”
curve
trend,
indicating
optimal
range
beyond
performance
diminishes.
IGI Global eBooks,
Год журнала:
2025,
Номер
unknown, С. 99 - 130
Опубликована: Май 2, 2025
Background
Information:
Data-driven
supply
chains
and
real-time
simulations
involving
digital
twins
are
transforming
the
sector.
Nevertheless,
existing
optimisation
techniques
usually
do
not
pay
much
heed
to
sustainability
or
resilience.
Through
enhancing
twin
systems
using
leading-edge
methods
in
this
work,
gap
has
been
filled.
Objectives:
The
main
aim
of
study
is
optimizing
efficiency
chain
with
application
GA,
ABM,
MDP,
SA
enhance
operational
efficiency,
cost
savings,
carbon
emissions
while
improving
Methods:
strategy
includes
agent-based
modeling,
stochastic
analysis,
Markov
decision
processes,
genetic
algorithm
optimization.
Results:
integrated
approach
86.5%
resilience,
18.7%
reduction,
93.2%
were
attained.
Conclusion:
study,
thus
concludes
by
how
well
work
together
balancing
sustainability.
MANAGEMENT CONTROL,
Год журнала:
2025,
Номер
1, С. 211 - 236
Опубликована: Апрель 1, 2025
This
study
explores
the
existing
literature
to
better
understand
how
Digital
Twins
(DTs)
have
been
analyzed
in
perspective
of
measuring
and
reporting
carbon
footprint
port
systems.
The
also
analyzes
greenhouse
gas
(GHG)
accounting
can
contribute
feed
DTs
information
system
regarding
values
emissions
from
mooring,
unmooring
manoeuvring
operations
at
ship-port
interface.
Although
several
studies
explored
implementation
new
technologies
improve
technical
efficiency
ports
their
effects
on
emissions,
others
GHG
for
measurement
latter,
it
remains
uncertain
be
integrated
with
predictive
analytics
interface
operations.
conducts
a
review
dataset
47
articles
Scopus
database
Google
Scholar,
published
1990
2024.
results
highlight
that,
since
2015,
research
has
highlighted
key
role
reducing
achieving
Sustainable
Development
Goals
(SDGs),
particularly
SDG7.
To
best
our
knowledge,
this
is
first
that
analyses,
according
holistic
approach,
digital
systems
virtual
representations
(GHG
accounting)
environmental
sustainability
support
public
management
decisions.
provides
different
analysis
decarbonization
sector,
theoretical
practical
implications
response
UN
2030
Agenda
its
SDGs.
WMU Journal of Maritime Affairs,
Год журнала:
2024,
Номер
unknown
Опубликована: Авг. 22, 2024
Abstract
This
paper
examines
the
role
of
digital
twins
(DTs)
in
promoting
sustainability
within
seaport
operations
and
logistics.
DTs
have
emerged
as
promising
tools
for
enhancing
performance.
Despite
recognized
potential
seaports,
there
is
a
paucity
research
on
their
practical
implementation
impact
sustainability.
Through
systematic
literature
review,
this
study
seeks
to
elucidate
how
contribute
seaports
identify
future
applications.
We
reviewed
categorized
68
conceptual
applications
into
ten
core
areas
that
effectively
support
economic,
social,
environmental
objectives
seaports.
Furthermore,
proposes
five
preliminary
where
implementations
are
currently
lacking.
The
primary
findings
indicate
can
enhance
by
facilitating
real-time
monitoring
decision-making,
improving
safety
security,
optimizing
resource
utilization,
collaboration
communication,
supporting
development
ecosystem.
Additionally,
addresses
challenges
associated
with
DT
implementation,
including
high
costs,
conflicting
stakeholder
priorities,
data
quality
availability,
model
validation.
concludes
discussion
implications
managers
policymakers.
