2021 IEEE Symposium Series on Computational Intelligence (SSCI),
Journal Year:
2023,
Volume and Issue:
unknown, P. 1753 - 1758
Published: Dec. 5, 2023
Dynamic
Berth
Allocation
Problem
(DBAP)
is
an
essential
problem
in
container
terminal
operations.
Most
studies
focus
on
discrete
or
continuous
berths
DBAP.
However,
affected
by
the
geographical
conditions,
mixture
of
and
which
are
called
hybrid
often
appear
real
port
terminals.
Moreover,
arrival
time
vessels
fluctuant
due
to
influence
environmental
factors.
To
solve
such
a
Hybrid
(DHBAP)
under
vessels'
delay,
this
study
develops
proactive-reactive
approach.
Specifically,
we
establish
mixed-integer
programming
model
with
buffer
as
proactive
strategy
obtain
baseline
schedule.
Then,
propose
berth
reactive
(HBRS)
adjust
schedule
for
that
delayed.
get
better
solution
short
time,
genetic
algorithm
designed.
We
verify
effectiveness
proposed
HBRS
comparing
it
most
commonly
used
right-shift
strategy.
Experimental
results
show
longer
is,
robustness
but
total
vessel
terminals
will
also
increase.
Compared
strategy,
can
allocation
plan
similar
shorter
Transportation Research Part C Emerging Technologies,
Journal Year:
2023,
Volume and Issue:
158, P. 104447 - 104447
Published: Dec. 6, 2023
The
integrated
scheduling
of
quay
cranes,
internal
vehicles,
and
yard
cranes
in
container
terminals
aims
to
improve
port
operations
often
requires
robustness
under
uncertainty
with
cascade
effects.
In
terminal
operations,
equipment
operating
time
poses
challenges
effective
scheduling,
as
even
small
fluctuations
can
create
effects
throughout
the
rendering
original
schedule
ineffective.
This
research
develop
a
new
method
that
enables
balance
between
optimization
scheduling.
Additionally,
double-cycling
operation
mode
U-shaped
layout,
known
for
their
improved
efficiency
terminals,
are
gaining
increasing
attention
hence
incorporated
into
this
study.
It
creates
three-stage
hybrid
flow
shop
problem
bi-directional
flows,
waiting
time,
uncertain
time.
To
address
complex
problem,
mixed
integer
programming
model
is
proposed
characterize
an
index
based
on
network
structure
entropy
designed
evaluate
anti-cascade
effect
well
schedule.
makespan
serve
bi-objectives,
transforming
bi-objective
one.
non-dominated
sorting
genetic
algorithm-Ⅱ
appropriate
coding
decoding
rules
utilized
solve
obtain
set
Pareto
frontier
solutions.
feasibility
verified
through
real
case
analysis.
Specifically,
comparative
analysis
basic
stochastic
programming,
robust
optimization,
triangular
fuzzy
maximum
gap
used
demonstrate
effectiveness
method.
paper
also
provides
insightful
practical
implications
managers,
genericity
could
contribute
its
values
spreading
wider
scope
beneficiaries,
such
manufacturing
warehousing
distribution
management.
Journal of Marine Science and Engineering,
Journal Year:
2024,
Volume and Issue:
12(3), P. 376 - 376
Published: Feb. 22, 2024
In
this
study,
we
address
the
integrated
scheduling
problem
involving
quay
cranes
and
IGVs
in
automated
terminals.
We
construct
a
mixed-integer
planning
model
with
aim
of
minimizing
total
energy
consumption
during
crane
IGV
operations,
focusing
on
loading-operation
mode.
The
considers
impact
actual
stowage
container
ships
loading
order.
propose
dimension-by-dimension
mutation
sparrow
search
algorithm
to
optimize
model’s
solution
quality.
Building
upon
standard
algorithm,
incorporate
cat
mapping
enhance
diversity
initial
population.
To
improve
global
early
stage
local
later
introduce
an
adaptive
t-distribution
strategy.
Finally,
12
instances
counts
containing
30,
100,
250
were
designed
for
experiments
validate
effectiveness
algorithm.
demonstrate
that,
by
appropriately
increasing
number
cranes,
configuring
more
than
two
or
three
can
achieve
optimal
overall
operations.
IEEE Access,
Journal Year:
2024,
Volume and Issue:
12, P. 58801 - 58822
Published: Jan. 1, 2024
Container
terminals
(CTs)
play
a
crucial
role
within
the
global
supply
chain
in
context
of
container
transportation
business.
The
primary
obligation
associated
with
these
involves
ensuring
punctual
execution
vessel
operations,
while
strictly
adhering
to
Estimated
Time
Departure
(ETD)
for
vessels.
To
accomplish
this
goal,
it
is
develop
rigorous
and
exact
operating
strategies.
Nonetheless,
accurate
prediction
operation
times
CT
presents
significant
challenge
due
concurrent
involvement
various
Handling
Equipment
(CHE)
occurrence
unforeseen
situations.
address
issue,
study
proposes
novel
approach
called
Predictive
Discrete
Event
Simulation
(PDES)
that
utilizes
data
collected
from
predict
times.
PDES
an
advanced
builds
upon
widely
used
(DES)
technique
field
simulations.
It
specifically
designed
provide
precise
predictions
CTs,
where
multiple
events
take
place
concurrently.
paper
aims
overcome
shortcomings
current
simulation-based
approaches
CT.
These
often
rely
on
predefined
task
sequences
assumed
time
job
handling
CHE
their
scenarios,
which
can
result
reduced
accuracy
when
predicting
Through
resolution
issues,
proposed
exhibits
capacity
improve
predictive
performance.
enhance
performance
CTs
through
PDES,
two
are
introduced.
first
entails
application
Support
Vector
Machine
(SVM)
algorithms
purpose
This
further
augmented
by
integrating
DES
second
simulating
real-world
operational
scenarios
using
assignment.
assessed
utilization
gathered
Busan
Port
Terminal
(BPT)
South
Korea,
demonstrating
superior
compared
alternative
approaches.
