Axioms,
Journal Year:
2023,
Volume and Issue:
12(7), P. 711 - 711
Published: July 22, 2023
One
of
the
critical
warehousing
processes
is
order-picking
process.
This
activity
consists
retrieving
items
from
their
storage
locations
to
fulfill
demand
specified
in
pick
lists.
Therefore,
location
assignment
affects
picking
time
and,
consequently,
reduces
operating
costs
warehouse.
work
presents
two
alternative
mixed-integer
linear
models
and
an
adaptive
multi-start
heuristic
(AMH)
for
solving
integrated
picker-routing
problem.
The
problem
considers
a
warehouse
with
general
layout
precedence
constraints
according
products
weight.
Experimental
confirms
efficiency
proposed
reformulations
since
we
found
out
total
334
tested
instances
optimal
solutions
51
new
cases
62
feasible
solutions.
AMH
improved
more
than
29%
best-known
required
average
execution
117
s.
Consequently,
our
algorithm
attractive
decision-making
tool
achieve
when
practical
situations
IEEE Internet of Things Journal,
Journal Year:
2024,
Volume and Issue:
11(9), P. 16314 - 16324
Published: March 22, 2024
With
the
development
of
robotics
and
Internet
Things,
robot-assisted
goods-to-person
order
picking
systems
become
popular
in
smart
warehouses.
Order
such
is
a
human-robot
collaborative
process,
where
robots
carry
pods
to
station
with
human
pickers
who
pick
demanded
goods
from
them
fulfill
orders.
In
it,
pod
selection,
robot
scheduling,
manual
are
highly
coupled
together
influence
efficiency
picking.
Their
joint
optimization
key
enhancing
operational
but
rarely
studied
existing
work.
fill
research
gap
meet
high
market
demand,
this
work
focuses
on
novel
problem.
A
mixed
integer
program
formulated
model
it
provide
an
exact
solution
method
for
small-scale
instances.
To
large-scale
problems
efficient
solutions
practical
application
scenarios,
we
propose
adaptive
large-neighborhood-based
tabu
search
algorithm.
Specifically,
large
neighborhood
designed
embedded
into
algorithm
two
mechanisms.
Experimental
results
indicate
that
presented
has
significant
advantages
solving
newly
proposed
It
substantially
outperforms:
1)
independent
use
or
search,
2)
Gurobi
subject
hour
execution
time,
3)
several
competitive
benchmark
newest
well-performing
algorithms.
Its
performance
implies
its
great
potential
Internet-of-Things-enabled
Production & Manufacturing Research,
Journal Year:
2023,
Volume and Issue:
11(1)
Published: March 30, 2023
A
literature
review
on
the
order
picking
process
in
warehouses
is
presented
for
delineating
trends
time
of
research
topics
this
field.
total
269
journal
papers
published
between
2007
and
2022
were
retrieved
from
Scopus.
After
a
methodological
classification,
descriptive
analyses
performed
authors,
journals,
subject
area
top
publishing
countries.
Bibliometric
tools
used
to
map
covered
by
reviewed
studies,
categorise
them
determine
possible
relationships.
Papers’
contents
evaluated
terms
eight
categories,
including
five
typical
issues
systems,
plus
three
aspects
dealing
with
characteristics
application.
Insights
about
extent
which
these
have
been
are
derived;
relationships
various
also
delineated.
Suggestions
future
activities
finally
deducted,
offering
researchers
practitioners
strong
bases
works
systems.
IEEE Access,
Journal Year:
2023,
Volume and Issue:
11, P. 55370 - 55379
Published: Jan. 1, 2023
Internet
of
Things
(IoT)
devices
are
becoming
increasingly
ubiquitous
in
daily
life.
They
utilized
various
sectors
like
healthcare,
manufacturing,
and
transportation.
The
main
challenges
related
to
IoT
the
potential
for
faults
occur
their
reliability.
In
classical
fault
detection,
client
device
must
upload
raw
information
central
server
training
model,
which
can
reveal
sensitive
business
information.
Blockchain
(BC)
technology
a
detection
algorithm
applied
overcome
these
challenges.
Generally,
fusion
BC
algorithms
give
secure
more
reliable
ecosystem.
Therefore,
this
study
develops
new
Assisted
Data
Edge
Verification
with
Consensus
Algorithm
Machine
Learning
(BDEV-CAML)
technique
Fault
Detection
purposes.
presented
BDEV-CAML
integrates
benefits
blockchain,
IoT,
ML
models
enhance
network's
trustworthiness,
efficacy,
security.
technology,
that
possess
significant
level
decentralized
decision-making
capability
attain
consensus
on
efficiency
intrablock
transactions.
For
network,
deep
directional
gated
recurrent
unit
(DBiGRU)
model
is
used.
Finally,
African
vulture
optimization
(AVOA)
optimal
hyperparameter
tuning
DBiGRU
helps
improving
rate.
A
detailed
set
experiments
were
carried
out
highlight
enhanced
performance
algorithm.
comprehensive
experimental
results
stated
improved
over
other
existing
maximum
accuracy
99.6%.
IEEE Transactions on Instrumentation and Measurement,
Journal Year:
2022,
Volume and Issue:
72, P. 1 - 11
Published: Dec. 8, 2022
Timely
and
accurate
fault
diagnosis
plays
a
critical
role
in
today's
smart
manufacturing
practices,
saving
invaluable
time
expenditure
on
maintenance
process.
To
date,
numerous
data-driven
approaches
have
been
introduced
for
equipment
diagnosis,
part
of
them
attempt
to
involve
knowledge
their
models.
However,
those
combinations
mainly
concentrate
feature
engineering
superposition
separate
results
without
considering
or
leveraging
the
relationship
between
collecting
sensor
data.
fill
this
gap,
research
proposes
residual-hypergraph
convolution
network
(Res-HGCN)
approach
that
holistically
embeds
equipment's
structure
operational
mechanisms
as
hypergraph
form
into
model,
reaction
among
components.
The
generic
model-based
construction
framework
is
first
introduced,
which
represents
synergetic
mechanism
complex
equipment.
Then,
multisensory
Res-HGCN
approach,
combining
residual
block
(HGCN),
presented
based
predefined
hypergraph.
Lastly,
case
study
turbofan
engine
conducted
compared
with
other
typical
methods
reveal
superiority
proposed
approach.
This
work
establishes
association
different
sensing
variables
through
mechanisms,
thus
integrating
advantages
data-driven-based
holistically.
It
envisioned
can
provide
insightful
many
integrated
scenarios.
