The two-echelon truck-unmanned ground vehicle routing problem with time-dependent travel times
Yuanhan Wei,
No information about this author
Yong Wang,
No information about this author
Xiangpei Hu
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et al.
Transportation Research Part E Logistics and Transportation Review,
Journal Year:
2025,
Volume and Issue:
194, P. 103954 - 103954
Published: Jan. 8, 2025
Language: Английский
Exploring the nexus between rural economic digitalization and agricultural carbon emissions: A multi-scale analysis across 1607 counties in China
Langang Feng,
No information about this author
Wenli Yang,
No information about this author
Jin Hu
No information about this author
et al.
Journal of Environmental Management,
Journal Year:
2024,
Volume and Issue:
373, P. 123497 - 123497
Published: Dec. 5, 2024
Language: Английский
The On-Demand Delivery Problem: Assignment of Orders to Warehouses and Couriers
Published: Jan. 1, 2025
Language: Английский
Integrated food delivery problem considering both single-order and multiple order deliveries
Computers & Industrial Engineering,
Journal Year:
2024,
Volume and Issue:
196, P. 110458 - 110458
Published: Aug. 8, 2024
Language: Английский
Bayesian Modeling of Travel Times on the Example of Food Delivery: Part 2—Model Creation and Handling Uncertainty
Electronics,
Journal Year:
2024,
Volume and Issue:
13(17), P. 3418 - 3418
Published: Aug. 28, 2024
The
e-commerce
sector
is
in
a
constant
state
of
growth
and
evolution,
particularly
within
its
subdomain
online
food
delivery.
As
such,
ensuring
customer
satisfaction
critical
for
companies
working
this
field.
One
way
to
achieve
by
providing
an
accurate
delivery
time
estimation.
While
can
track
couriers
via
GPS,
they
often
lack
real-time
data
on
traffic
road
conditions,
complicating
predictions.
To
address
this,
range
statistical
machine
learning
techniques
are
employed,
including
neural
networks
specialized
expert
systems,
with
different
degrees
success.
issue
models
their
heavy
dependence
vast,
high-quality
data.
mitigate
issue,
we
propose
two
Bayesian
generalized
linear
predict
the
Utilizing
combination
predictor
variables,
generate
practical
outputs
Hamiltonian
Monte
Carlo
sampling
method.
These
offer
balance
generality
adaptability,
allowing
tuning
knowledge.
They
were
compared
PSIS-LOO
criteria
WAIC.
results
show
that
both
accurately
estimated
times
from
dataset
while
maintaining
numerical
stability.
A
model
more
variables
proved
be
accurate.
Language: Английский
A hybrid heuristic algorithm for the fuzzy open vehicle routing problem with risk preference
Journal of Industrial and Management Optimization,
Journal Year:
2024,
Volume and Issue:
0(0), P. 0 - 0
Published: Jan. 1, 2024
Language: Английский
Meal pickup and delivery problem with appointment time and uncertainty in order cancellation
Transportation Research Part E Logistics and Transportation Review,
Journal Year:
2024,
Volume and Issue:
193, P. 103845 - 103845
Published: Nov. 6, 2024
Language: Английский
Waiting Strategy for the Dynamic Meal Delivery Routing Problem with Time-Sensitive Customers Using a Hybrid Adaptive Genetic Algorithm and Adaptive Large Neighborhood Search Algorithm
Systems,
Journal Year:
2024,
Volume and Issue:
12(5), P. 170 - 170
Published: May 10, 2024
In
this
paper,
we
study
the
dynamic
meal
delivery
routing
problem
(MDRP)
with
time-sensitive
customers.
The
multi-objective
MDRP
optimization
model
is
developed
to
maximize
customer
satisfaction
and
minimize
delay
penalty
cost
riding
cost.
To
solve
MDRP,
a
novel
waiting
strategy
proposed
divide
into
series
of
static
subproblems.
This
utilizes
decision
threshold
determine
rerouting
points
based
on
number
orders.
Meanwhile,
priority
introduced
accelerate
assignment
decisions
for
orders
from
customers
high
time
sensitivity.
For
each
subproblem,
hybrid
AGA–ALNS
algorithm
that
incorporates
adaptive
genetic
large
neighborhood
search
improve
both
global
local
capabilities
algorithm.
We
validate
performance
through
numerical
instances.
addition,
managerial
insights
are
obtained
sensitivity
analysis
experiments.
Language: Английский