Grey system theory in supply chain: emerging hotspots and trends
Grey Systems Theory and Application,
Год журнала:
2025,
Номер
unknown
Опубликована: Янв. 18, 2025
Purpose
Supply
chains,
as
prototypical
uncertain
systems,
are
crucial
for
national
security
and
socioeconomic
development.
Grey
system
theory
(GST)
is
an
effective
tool
addressing
uncertainties
has
played
a
pivotal
role
in
related
research
within
the
supply
chain
domain.
This
study
aims
to
systematically
summarize
achievements
knowledge
structures
pertaining
GST
studies.
Current
potential
hotspots
also
analyzed.
Design/methodology/approach
CiteSpace
used
conduct
bibliometric
analysis
of
1,617
articles
sourced
from
Web
Science
(WOS).
The
current
state
structure
field.
A
strategic
diagram
incorporating
two
data
indicators,
namely,
novelty
concern,
constructed
based
on
keyword
clustering
identify
analyze
hotspots.
Findings
Studies
utilizing
guide
practices
have
attracted
interest
scholars
205
institutions
across
85
countries
regions
globally,
which
earned
recognition
183
high-level
academic
journals.
In
this
field,
School
Economics
Management
at
Nanjing
University
Aeronautics
Astronautics
stands
out
core
institution,
with
Professor
Deng
Julong,
who
founder
GST,
being
most
frequently
cited
scholar.
complex
equipment
drivers
challenges
management,
risk
closed-loop
operation
big
era.
addition,
emerging
include
digital
intelligent
logistics
technology,
sustainable
supplier
determinants
flexibility
contracts,
strategy,
purchase
grey
prediction
demand
consumption,
forecasting
economy
efficiency,
China-specific
issues
model
construction.
Originality/value
reveals
Previous
studies
primarily
relied
subjective
judgments,
lacked
empirical
support.
constructs
provide
more
objective
reliable
Язык: Английский
A model predictive control for a multi-chiller system in data center considering whole system energy conservation
Energy and Buildings,
Год журнала:
2024,
Номер
unknown, С. 114919 - 114919
Опубликована: Окт. 1, 2024
Язык: Английский
Analyzing and Forecasting Container Throughput With a Hybrid Decomposition‐Reconstruction‐Ensemble Method: A Study of Two China Ports
Journal of Forecasting,
Год журнала:
2025,
Номер
unknown
Опубликована: Янв. 5, 2025
ABSTRACT
Accurate
container
throughput
forecasting
is
critical
for
enhancing
port
efficiency
and
ensuring
global
trade
stability,
particularly
in
the
face
of
economic
uncertainties,
geopolitical
tensions,
supply
chain
disruptions.
Existing
methods
often
struggle
to
model
nonlinear,
nonstationary,
noise‐laden
characteristics
data,
creating
a
clear
gap
ability
provide
reliable
predictions.
To
address
this,
we
propose
novel
hybrid
model,
VMD‐ISE‐TCNT,
designed
tackle
these
challenges.
The
employs
variational
mode
decomposition
(VMD)
decompose
time
series
into
intrinsic
modes,
with
an
improved
signal
energy
(ISE)
criterion
automating
selection
optimal
numbers.
These
modes
are
categorized
low‐
high‐frequency
components
forecasted
separately
using
temporal
convolutional
networks
(TCNs),
leveraging
their
strength
capturing
multiscale
dependencies.
Theil
UII‐S
loss
function
integrated
enhance
robustness
by
prioritizing
proportional
accuracy
reducing
outlier
sensitivity.
Empirical
evaluations
24
years
data
from
China's
two
largest
ports—Shanghai
Shenzhen—demonstrate
superior
performance
VMD‐ISE‐TCNT
compared
traditional
benchmarks.
By
addressing
frequency‐specific
patterns
key
processes,
this
provides
scalable
interpretable
solution
advancing
operations
resilience
trade.
Язык: Английский
Selection of Green Recycling Suppliers for Shared Electric Bikes: A Multi-Criteria Group Decision-Making Method Based on the Basic Uncertain Information Generalized Power Weighted Average Operator and Basic Uncertain Information-Based Best–Middle–Worst TOPSIS Model
Sustainability,
Год журнала:
2024,
Номер
16(19), С. 8647 - 8647
Опубликована: Окт. 6, 2024
This
study
introduces
a
novel
multi-criteria
group
evaluation
approach
grounded
in
the
theory
of
basic
uncertain
information
(BUI)
to
facilitate
selection
green
recycling
suppliers
for
shared
electric
bikes.
Firstly,
comprehensive
index
system
is
established,
encompassing
capacity,
environmental
sustainability,
financial
strength,
maintenance
capabilities,
and
policy
support,
provide
solid
foundation
scientific
process.
Secondly,
generalized
power
weighted
average
(BUIGPWA)
operator
proposed
aggregate
with
BUI
pairs,
some
related
properties
are
investigated.
Furthermore,
information-based
best–middle–worst
TOPSIS
(BUI-BMW-TOPSIS)
model
incorporating
best,
middle,
worst
reference
points
enhance
decision-making
accuracy
proposed.
Ultimately,
by
integrating
BUIGPWA
aggregation
BUI-BMW-TOPSIS
handle
decision
information,
(MCGDM)
method
constructed
evaluate
Case
analyses
comparative
demonstrate
that
compared
BUIWA
operator,
yields
more
reliable
results
because
its
consideration
degree
support
among
decision-makers.
contrast
traditional
method,
incorporates
credibility
provided
decision-makers,
leading
trustworthy
outcomes.
Notably,
variations
attribute
weights
significantly
impact
results.
In
summary,
our
methods
excel
handling
complex
decisions,
boosting
rigor
reliability,
supporting
optimization
sustainability
bike
suppliers.
Язык: Английский
Forecasting national port cargo throughput movement using autoregressive models
Case Studies on Transport Policy,
Год журнала:
2024,
Номер
19, С. 101322 - 101322
Опубликована: Ноя. 10, 2024
Язык: Английский
Limited data-driven router bandwidth configuration for cyber physical internet
Expert Systems with Applications,
Год журнала:
2024,
Номер
unknown, С. 126003 - 126003
Опубликована: Ноя. 1, 2024
Язык: Английский
Human Vs. Machines: Who wins in semiconductor market forecasting?
Expert Systems with Applications,
Год журнала:
2024,
Номер
263, С. 125719 - 125719
Опубликована: Ноя. 13, 2024
The
experts
polled
by
the
World
Semiconductor
Trade
Statistics
(WSTS),
a
premier
provider
of
semiconductor
market
data
and
forecasts,
achieved
high
performance
in
terms
mean
error
measure
ranks
compared
to
data-driven
forecasts
trained
on
historic
up
until
official
WSTS
time
stamp.•
incorporation
additional
available
into
resulted
superior
models.
Язык: Английский