2022 IEEE 18th International Conference on Automation Science and Engineering (CASE),
Journal Year:
2021,
Volume and Issue:
unknown, P. 1467 - 1472
Published: Aug. 23, 2021
This
paper
studies
an
integration
of
the
forward
products
flow,
as
in
vehicle
routing
problem
with
cross-docking
(VRPCD),
and
reverse
VRP
(VRP-RCD),
namely
(VRP-FRCD).
It
is
modelled
a
mixed-integer
linear
programming
model
that
covers
four-level
supply
chain
network,
including
suppliers,
retailers,
outlets,
cross-dock
facility.
The
objective
to
determine
appropriate
number
vehicles
used
complete
delivery
process,
together
route
sequence
every
vehicle,
such
total
fixed
distance-related
costs
are
minimized.
In
order
solve
problem,
two-phase
matheuristic
developed.
first
phase
focuses
on
finding
many
combinations
possible.
implemented
by
adaptive
large
neighborhood
search
(ALNS)
algorithm.
Subsequently,
set
partitioning
formulation
formulated
solved
second
best
combination
over
all
routes
found
minimizes
cost.
performance
solving
newly
developed
benchmark
instances
compared
against
those
CPLEX
pure
ALNS
Experimental
results
suggest
more
powerful
beneficial
than
both
obtain
high-quality
solutions
within
acceptable
computational
time.
Synthesis lectures on operations research and applications,
Journal Year:
2023,
Volume and Issue:
unknown, P. 1 - 64
Published: Jan. 1, 2023
We
identify
135
articles
published
in
scholarly,
academic
journals
from
January
2005
to
June
2022
that
survey
various
aspects
of
the
Vehicle
Routing
Problem
(VRP)
ranging
exact
and
heuristic
solution
methods
new
problem
variants
such
as
drone
routing
research
areas
green
routing.
catalog
classify
these
articles,
make
key
observations
about
publication
history
overall
contributions,
trends
VRP
practice.
Our
book
should
be
valuable
researchers
practioners
with
ongoing
or
unfolding
efforts
into
VRP.
Research Square (Research Square),
Journal Year:
2025,
Volume and Issue:
unknown
Published: April 28, 2025
Abstract
This
study
initially
surveys
one
of
the
most
popular
operations
research
models
known
as
vehicle
routing
problem
(VRP)
and
expresses
its
weakness
confronting
real-world
situations.
For
this,
purpose
present
article
expands
dimensions
under
from
two
to
three
dimensions.
The
third
dimension
is
considered
route
slope
because
role
in
increasing
transportation
cost.
To
solve
this
problem,
a
new
mixed
integer
programming
soft
(VSRP)
proposes
optimizing
class
problems
three-dimensional
cartesian
coordinate
system.
compare
VSRP
vs
VRP,
several
numerical
cases
are
examined.
Computational
results
show
that
using
will
decrease
total
cost
all
cases.
In
addition,
graphically
projected
routes
selected
sequencing
have
lower
than
by
VRP
models.
example,
cases,
we
faced
with
5.2%
286%
improvement
lowering
based
on
defined
index.
Applied Sciences,
Journal Year:
2024,
Volume and Issue:
14(16), P. 7135 - 7135
Published: Aug. 14, 2024
Vehicle
routing
problems
(VRPs)
are
challenging
problems.
Many
variants
of
the
VRP
have
been
proposed.
However,
few
studies
on
combined
robustness
and
just-in-time
(JIT)
requirements
with
uncertainty.
To
solve
problem,
this
paper
proposes
just-in-time-based
robust
multiobjective
vehicle
problem
time
windows
(JIT-RMOVRPTW)
for
assembly
workshop.
Based
conflict
between
uncertain
JIT
requirements,
a
strategy
was
measure
solution,
metric
designed
as
objective.
Afterwards,
two-stage
nondominated
sorting
ant
colony
algorithm
deep
reinforcement
learning
(NSACOWDRL)
In
stage
I,
ACO
combines
NSGA-III
to
obtain
Pareto
frontier.
model,
pheromone
update
transfer
probability
formula
were
designed.
DDQN
introduced
local
search
which
trains
networks
through
solutions
participate
in
probabilistic
selection
sorting.
II,
frontier
quantified
feasibility
by
Monte
Carlo
simulation,
tested
diversity-robust
based
uniformly
distributed
weights
solution
space
select
that
take
diversity
into
account.
The
effectiveness
NSACOWDRL
demonstrated
comparative
experiments
other
algorithms
instances.
impact
is
analyzed
effect
further
discussed.
PeerJ Computer Science,
Journal Year:
2023,
Volume and Issue:
9, P. e1541 - e1541
Published: Sept. 1, 2023
Due
to
situational
fluidity
and
intrinsic
uncertainty
of
emergency
response,
there
needs
be
a
fast
vehicle
routing
algorithm
that
meets
the
constraints
situation,
thus
receiving-staging-storing-distributing
(RSSD)
was
developed.
Benchmarking
quality
this
satisficing
is
important
understand
consequences
not
engaging
with
NP-Hard
task
problem.
This
benchmarking
will
inform
whether
RSSD
producing
acceptable
consistent
solutions
used
in
decision
support
systems
for
response
planning.
We
devise
metrics
domain
space
planning,
medical
countermeasure
dispensing
order
assess
solutions.
conduct
experiments
perform
statistical
analyses
algorithm’s
compared
best
known
selected
capacitated
problem
(CVRP)
benchmark
instances.
The
results
these
indicate
even
though
does
engage
finding
optimal
route
solutions,
it
behaves
manner
across
range
instances
attributes.
